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Radioengineering

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Proceedings of Czech and Slovak Technical Universities

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December 2022, Volume 31, Number 4 [DOI: 10.13164/re.2022-]

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Q. Ma, H. Tie, B. Zhou [references] [full-text] [DOI: 10.13164/re.2022.0455] [Download Citations]
Compact LTCC Balun using L-C Embraced Structure for 128 MHz 3T MRI Applications

A compact lumped-element balun is proposed for 128 MHz frequency 3 Tesla (T) magnetic resonance imaging (MRI) applications. The miniaturization is achieved by the inductor-capacitor (L-C) embraced structure, which places vertically-interdigital-capacitor (VIC) inside spiral inductor for higher integration. The L-C surrounded structure only takes up one element’s area without increasing the number of substrate layers. The balun is built on a 10-layer thickness low temperature co-fired ceramic (LTCC) substrate and has the smallest reported size of only 0.007×0.008 × 0.0009 λg. Moreover, the proposed balun also has a 2nd-order harmonic suppression of 32 dB. Furthermore, comparisons and discussions are also implemented.

  1. DIANAT, A., ATTARAN, A., MUSCEDERE, R., et al. PCB fabricated passive RF balun for 3 T MRI applications. In IEEE Canadian Conference of Electrical and Computer Engineering (CCECE). Edmonton (AB, Canada), 2019, p. 1–4. DOI: 10.1109/CCECE.2019.8861585
  2. DIANAT, A., ATTARAN, A., MUSCEDERE, R., et al. A nonmagnetic RF balun designed at 128 MHz centre frequency for 3 T MRI scanners, In IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). London (ON, Canada), 2020, p. 1–4. DOI: 10.1109/CCECE47787.2020.9255767
  3. ZHU, Y., SAPPO, C. R., GRISSOM, W. A., et al. Dual-tuned lattice balun for multi-nuclear MRI and MRS. IEEE Transactions on Medical Imaging, 2022, vol. 41, no. 6, p. 1420–1430. DOI: 10.1109/TMI.2022.3140717
  4. KUMAR, S., YOON, J. S., KIM, J. M., et al. Whole-brain imaging with receive-only multichannel top-hat dipole antenna RF coil at 7 T MRI. Journal of the Korean Physical Society, 2022, vol. 80, no. 9, p. 920–927. DOI: 10.1007/s40042-021-00334-5
  5. GILBERT, K. M., DUBOVAN, P. I., GATI, J. S., et al. Integration of an RF coil and commercial field camera for ultrahigh-field MRI. Magnetic Resonance in Medicine, 2022, vol. 87, no. 5, p. 2551–2565. DOI: 10.1002/mrm.29130
  6. LIU, Q., HUIYU, D., QING, Z., et al. Design and study of the customized breast receiving coil for interventional MRI at 0.35 T. In IEEE International Conference on Medical Imaging Physics and Engineering (ICMIPE). Hefei (China), 2021, p. 1–6. DOI: 10.1109/ICMIPE53131.2021.9698907
  7. FUJIMOTO, K., ZAIDI, T. A., LAMPMAN, D., et al. Comparison of SAR distribution of hip and knee implantable devices in 1.5 T conventional cylindrical‐bore and 1.2 T open‐bore vertical MRI systems. Magnetic Resonance in Medicine, 2022, vol. 87, no. 3, p. 1515–1528. DOI: 10.1002/mrm.29007
  8. KAWAHARA, K., UMEDA, Y., TAKANO, K. A broadband active balun with inductor-less active peaking and imbalance correction. In IEEE International Midwest Symposium on Circuits and Systems (MWSCAS). Lansing (MI, USA), 2021, p. 749–752. DOI: 10.1109/MWSCAS47672.2021.9531759
  9. YANG, Y., WU, Y., ZHUANG, Z., et al. An ultraminiaturized bandpass filtering Marchand balun chip with spiral coupled lines based on GaAs integrated passive device technology. IEEE Transactions on Plasma Science, 2020, vol. 48, no. 9, p. 3067 to 3075. DOI: 10.1109/TPS.2020.3019308
  10. WANG, C., KIM, N. Y. High performance WLAN balun using integrated passive technology on SI‐GaAs substrate. Microwave and Optical Technology Letters, 2012, vol. 54, no. 5, p. 1301 to 1305. DOI: 10.1002/mop.26801
  11. TA, H. H., PHAM, A. V. A compact broadband balun on multilayer organic substrate. Microwave and Optical Technology Letters, 2013, vol. 55, no. 8, p. 1957–1959. DOI: 10.1002/mop.27670
  12. PIATNITSA, V., KHOLODNYAK, D., KAPITANOVA, P., et al. Right/left-handed transmission line LTCC directional couplers. In European Microwave Conference. Munich (Germany), 2007, p. 636–639. DOI: 10.1109/EUMC.2007.4405272
  13. LI, B., DAI, Y. Design of the micro lumped balun based on LTCC technology. In 2016 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM). Nanjing (China), 2016, p. 1–3. DOI: 10.1109/iWEM.2016.7505039
  14. BRZEZINA, G., ROY, L. A miniature lumped element LTCC quadrature hybrid coupler for GPS applications. In IEEE Antennas and Propagation Society International Symposium. San Diego (CA, USA), 2008, p. 1–4. DOI: 10.1109/APS.2008.4619925
  15. BRZEZINA, G., ROY, L., MACEACHERN, L. Design enhancement of miniature lumped-element LTCC bandpass filters. IEEE Transactions on Microwave Theory and Techniques, 2009, vol. 57, no. 4, p. 815–823. DOI: 10.1109/TMTT.2009.2015035
  16. YE, Y., LI, L., GU, J., et al. Compact wideband lumped balun with out-of-band suppression using tail inductor. Electronics Letters, 2013, vol. 49, no. 19, p. 1232–1234. DOI: 10.1049/el.2013.1408
  17. Microwave Office, Applied Wave Research Corporation, El Segundo, CA. https://www.awr.com/
  18. AXIEM, Applied Wave Research Corporation, El Segundo, CA. https://www.cadence.com/zh_TW/home/tools/system-analysis/rf-microwave-design/awr-axiem-analysis.html

Keywords: Compact; balun; LTCC; MRI

A. Oncu, A. G. Aydin, Y. Erdogan, A. Akdogan [references] [full-text] [DOI: 10.13164/re.2022.0460] [Download Citations]
Mode-S Radar Interrogation Algorithm Design for Dense Air Traffic Environment

The increasing trend in air traffic density will continue in the near future with the addition of different aerial vehicles. Before the Mode-S protocol, Mode A and Mode C were in use; however, the Mode A/C configuration was only usable in sparsely dense air traffic. One of the useful features of Mode-S is the ability of probabilistic interrogation. However, there has not yet been a sophisticated algorithm for many close aircraft. Considering a futuristic air environment with a swarm of drones and airbuses equipped with transponders, we utilized the probabilistic interrogation feature of Mode-S and designed an algorithm. The proposed algorithm is able to collect close aircraft information in a relatively short time. There has also been created a high-level Mode-S uplink and downlink communication simulator in order to exchange all-call communication and record the algorithm’s performance in terms of time and number of interrogations sent.

  1. BAKER, J. L, ORLANDO, V.A., LINK, W.B., et al. Mode S system design and architecture. Proceedings of the IEEE, 1989, vol. 77, no. 11, p. 1684–1694. DOI: 10.1109/5.47731
  2. INTERNATIONAL TELECOMMUNICATION UNION. Reception of Automatic Dependent Surveillance Broadcast via Satellite and Compatibility Studies with Incumbent Systems in the Frequency Band 1 087.7-1 092.3 MHz. Geneva: ITU, 2017. Report ITU-R M.2413-0
  3. BEASLEY, B. Understanding Mode S Technology. [Online] Cited 2012-10-10 Available at AvionTEq: https://www.avionteq.com/document/Understanding-Mode-S-technology.pdf
  4. EUROPEAN ORGANIZATION FOR THE SAFETY OF AIR NAVIGATION. Conflict-Free Direct Routings in European Airspace. March 1997. EEC Report No. 308.
  5. STANDFUSS, T., SCHULTZ, M. Performance assessment of European air navigation service providers. In 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC). London (UK), 2018, p. 1–10. DOI: 10.1109/DASC.2018.8569839
  6. EUROPEAN ORGANIZATION FOR THE SAFETY OF AIR NAVIGATION. EUROCONTROL Annual Report 2016. 3 August 2017.
  7. EUROPEAN ORGANIZATION FOR THE SAFETY OF AIR NAVIGATION. EUROCONTROL Five-Year Forecast 2020-2024. 4 November 2020.
  8. EUROPEAN ORGANIZATION FOR THE SAFETY OF AIR NAVIGATION. EUROCONTROL Data Snapshot #8 on the Costs of Air Traffic Management in Europe. 23 March 2021.
  9. CABALLERO, R. M. UAS Bulletin #2. In European Civil Aviation Conference (ECAC). France, December 2021.
  10. HAESSIG, D. A., OGAN, R. T., OLIVE, M. “Sense and avoid” - What’s required for aircraft safety. In IEEE Southeastcon. Norfolk (VA, USA), 2016, p. 1–8. DOI: 10.1109/SECON.2016.7506724
  11. MINUCCI, F., VINOGRADOV, E., POLLIN, S. Avoiding collisions at any (low) cost: ADS-B like position broadcast for UAVs. IEEE Access, 2020, vol. 8, p. 121843–121857. DOI: 10.1109/ACCESS.2020.3007315
  12. JONAS, P., JANCIK, M., HOLODA, S., et al. Impact of SUAS equipped with ADS-B on 1090 MHz environment. In 2020 New Trends in Civil Aviation (NTCA). Prague (Czech Republic), 2020, p. 63–67. DOI: 10.23919/NTCA50409.2020.9291095
  13. BATUWANGALA, E., KISTAN, T., GARDI, A., et al. Certification challenges for next-generation avionics and air traffic management systems. IEEE Aerospace and Electronic Systems Magazine, 2018, vol. 33, no. 9, p. 44–53. DOI: 10.1109/MAES.2018.160164
  14. DOOLE, M., ELLERBROEK, J., HOEKSTRA, J. M. Investigation of merge assist policies to improve safety of drone traffic in a constrained urban airspace. Aerospace, 2022, vol. 9, p. 1–25. DOI: 10.3390/aerospace9030120
  15. KELLERMANN, R., BIEHLE, T., FISCHER, L. Drones for parcel and passenger transportation: A literature review. Transportation Research Interdisciplinary Perspectives, 2020, vol. 4, p. 1–13. DOI: 10.1016/j.trip.2019.100088
  16. SHRESTHA, R., BAJRACHARYA, R., KIM, S. 6G enabled unmanned aerial vehicle traffic management: A perspective. IEEE Access, 2021, vol. 9, p. 91119–91136. DOI: 10.1109/ACCESS.2021.3092039
  17. YOO, L. S., LEE, J. H., KO, S. H., et al. A drone fitted with a magnetometer detects landmines. IEEE Geoscience and Remote Sensing Letters, 2020, vol. 17, no. 12, p. 2035–2039. DOI: 10.1109/LGRS.2019.2962062
  18. JAN, S. U., KHAN, H. U. Identity and aggregate signature-based authentication protocol for IoD deployment military drone. IEEE Access, 2021, vol. 9, p. 130247–130263. DOI: 10.1109/ACCESS.2021.3110804
  19. KOGA, T., MORI, K. Autonomous lockout map construction technique for secondary surveillance radar Mode S network. In 2010 IEEE Radar Conference. Arlington (VA, USA), 2010, p. 1439–1443. DOI: 10.1109/RADAR.2010.5494389
  20. SUN, J. The 1090 Megahertz Riddle: A Guide to Decoding Mode S and ADS-B Signals. Delft: TU Delft OPEN Publishing, 2021. ISBN: 978-94-6366-402-8 DOI: 10.34641/mg.11
  21. EUROPEAN ORGANIZATION FOR THE SAFETY OF AIR NAVIGATION. Principles of Mode S Operation and Interrogator Codes. 2003, March 18.
  22. MATEU, J. RADIOLOCATION: Secondary Surveillance RADAR (SSR), Air Traffic Control Radar Beacon System(ATCRBS). [Online] 2016. Retrieved from Universidad Politecnica de Catalunya Barcelonatech: UPCommons: https://upcommons.upc.edu/bitstream/handle/2117/340881/SSR.pdf?sequence=1&isAllowed=y
  23. SUN, J., VU, H., ELLERBROEK, J., et al. pyModeS: Decoding Mode-S surveillance data for open air transportation research. IEEE Transactions on Intelligent Transportation Systems, 2020, vol. 21, no. 7, p. 2777–2786. DOI: 10.1109/TITS.2019.2914770
  24. EUROPEAN ORGANIZATION FOR THE SAFETY OF AIR NAVIGATION. MODE-S Specific Services and Data Link Test Bench. 1998, April.
  25. KOGA, T. Classification of Mode S transponders by datalink capability. In 2014 Integrated Communications, Navigation and Surveillance Conference (ICNS) Conference Proceedings. Herndon (VA, USA), 2014, p. O3-1–O3-7. DOI: 10.1109/ICNSurv.2014.6820008
  26. BODART, J. Mode S Surveillance Principle. [Online] Cited 2019-02-26. Available at EUROCONTROL: https://www.icao.int/MID/Documents/2019/MICA/MICA-MID%20-%20WP%2002%20-%20Mode%20S%20Surveillance%20Principle.pdf
  27. EUROPEAN ORGANIZATION FOR THE SAFETY OF AIR NAVIGATION. EUROCONTROL Specification for European Mode S Station (EMS). 2021, December 14.
  28. BODART, J. Radar Programming (MIP). [Online] Published 2019-02-26. Available at EUROCONTROL: https://www.icao.int/MID/Documents/2019/MICA/MICA-MID%20-%20WP%2012%20-%20Radar%20programming%20-%20MIP.pdf#search=radar%20programming%20MIP
  29. EUROPEAN ORGANIZATION FOR THE SAFETY OF AIR NAVIGATION. Mode S transponder in an airport/A-SMGCS environment - Clarification. [Online] Published 2005-05-03. Available at: https://www.eurocontrol.int/publication/mode-s-transponder-airporta-smgcs-environment-clarification
  30. PAYDAR, M. SSR Mode S Coordination Issues. [Online] Published 2010-08. Available at ICAO.INT: https://www.icao.int/WACAF/Documents/Meetings/2011/asi_ws/pp1_ssr_modes_coordination.pdf
  31. BRIA, O. N., GIACOMANTONE, J., VILLAGARCIA WANZA, H. A. Interleaving scheduling algorithm for SLM transactions in Mode S surveillance radar. In XXIV Congreso Argentino de Ciencias de la Computacion. La Plata (Argentina), 2018, p. 1–16. ISBN: 978-950-658-472-6 DOI: 10.1007/978-3-030-20787-8_21
  32. MAZUCH, P., KLECUN, R. Identification of an aircraft with the mode-S. Acta Avionica, 2013, vol. XV, no. 27, p. 1–6. ISSN: 1335-9479
  33. KOGA, T., UEJIMA, K. Results of validation of SSR mode S interrogator identifier code coordination. In 2009 IEEE/AIAA 28th Digital Avionics Systems Conference. Orlando (FL, USA), 2009, p. 4.D.6-1–4.D.6-7. DOI: 10.1109/DASC.2009.5347481
  34. SCHAFER, M., STROHMEIER, M., SMITH, M., et al. OpenSky report 2016: Facts and figures on SSR mode S and ADS-B usage. In 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC). Sacramento (CA, USA), 2016, p. 1–9. DOI: 10.1109/DASC.2016.7778030

Keywords: Garbling, lockout, Mode-S, stochastic interrogation

L. Zou, X. Wang, L. Zhang, H. Gao [references] [full-text] [DOI: 10.13164/re.2022.0468] [Download Citations]
Enhanced SIMO Radar System Based on Time-Frequency Correlation for Target Localization Applications

This study developed a novel S-band radar system for planar location applications. High-resolution range imaging and target angle estimation were achieved by using a stepped frequency continuous wave (SFCW) signal and single input multiple output (SIMO) architecture with a linear sparse array layout, respectively. An improved time-frequency method was utilized to link the independent range profile and angle spectrum results to obtain the plane positions of the targets. The radar hardware was composed of the antenna array with one transmit element and five receive elements, an RF transceiver, and a signal processing component. Under the proposed waveform parameters and signal processing scheme, a 16-ms process cycle, 0.3-m ranging error, and 0.4° angle estimation error for target positioning were achieved in field tests. These results demonstrate the effectiveness and advantages of the proposed radar system.

  1. MA, Y. G., HONG, H., ZHU, X. H. Multiple moving-target indication for urban sensing using change detection-based compressive sensing. IEEE Geoscience and Remote Sensing Letters, 2021, vol. 18, no. 3, p. 416–420. DOI: 10.1109/LGRS.2020.2977168
  2. CEBA, F., MAKHOUL, E., BROQUETAS, A., et al. Modeling fast boat motion impact on satellite SAR MTI systems. IEEE Geoscience and Remote Sensing Letters, 2015, vol. 12, no. 10, p. 2145–2149. DOI: 10.1109/LGRS.2015.2453018
  3. LI, J. A., ZHU, X. M., STOICA, P., et al. High resolution angle-Doppler imaging for MTI radar. IEEE Transactions on Aerospace and Electronic Systems, 2010, vol. 46, no. 3, p. 1544–1556. DOI: 10.1109/TAES.2010.5545209
  4. LI, K., WEN, B. Y., XU, Y. M., et al. A novel UHF radar system design for river dynamics monitoring. IEICE Electronic Express, 2015, vol. 12, no. 4, p. 1–8. DOI: 10.1587/elex.12.20141074
  5. LAGERKVIST, L. Design considerations for a modern naval fire control radar. In IEEE Radar Conference. Arlington (USA), 2010, p. 615–619. DOI: 10.1109/RADAR.2010.5494547
  6. SACHUK, I. I., ORLENKO, V. M., SHIRMAN, Y. D. UWB signals, SA perspectives in radar guidance. In 3rd International Conference on Ultrawideband and Ultrashort Impulse Signals (UWBUS). Sevastopol (Ukraine), 2006, p. 133–135. DOI: 10.1109/UWBUS.2006.307179
  7. GUO, J. P., CHANG, S. Q., YANG, F. W., et al. Low-slow-small target detection using stepped-frequency signals in a strong folded clutter environment. IET Radar Sonar and Navigation, 2021, vol. 15, no. 9, p. 1030–1044. DOI: 10.1049/rsn2.12095
  8. WANG, K., ZENG, Z. F., SUN, J. G. Through-wall detection of the moving paths and vital signs of human beings. IEEE Geoscience and Remote Sensing Letters, 2019, vol. 16, no. 5, p. 717–721. DOI: 10.1109/LGRS.2018.2881311
  9. CHEN, H. Y., LIU, Y. X., JIANG, W. D., et al. A new approach for synthesizing the range profile of moving targets via stepped-frequency waveforms. IEEE Geoscience and Remote Sensing Letters, 2006, vol. 3, no. 3, p. 406–409. DOI: 10.1109/LGRS.2006.873874
  10. XIA, Y., NING, S., SHEN, H., Moving targets detection algorithm based on background subtraction and frames subtraction. In The 2nd International Conference on Industrial Mechatronics and Automation (ICINDMA). Wuhan (China), 2010, p. 122–125. DOI: 10.1109/ICINDMA.2010.5538075
  11. BAO, Y., REN, L., HE, P., et al. A novel approach for clutter cancellation in HPRF stepped-frequency radar. In 9th International Conference on Signal Processing (ICOSP). Beijing (China), 2008, p. 2384–2387. DOI: 10.1109/ICOSP.2008.4697629
  12. YBARRA, G., WU, S., BILBRO, G., et al. Optimal signal processing of frequency-stepped CW radar data. IEEE Transactions on Microwave Theory and Techniques, 1995, vol. 43, no. 1, p. 94–105. DOI: 10.1109/22.363002
  13. AUBRY, A., CAROTENUTO, V., DE MAIO, A., et al. High range resolution profile estimation via a cognitive stepped frequency technique. IEEE Transactions on Aerospace and Electronic Systems, 2019, vol. 55, no. 1, p. 444–458. DOI: 10.1109/TAES.2018.2880024
  14. REN, L., KONG, L., FOROUGHIAN, F., et al. Comparison study of noncontact vital signs detection using a Doppler stepped-frequency continuous-wave radar and camera-based imaging photoplethysmography. IEEE Transactions on Microwave Theory and Techniques, 2017, vol. 65, no. 9, p. 3519–3529. DOI: 10.1109/TMTT.2017.2658567
  15. PARK, J., NGUYEN, C. A new millimeter-wave step-frequency radar sensor for distance measurement. IEEE Microwave and Wireless Components Letters, 2002, vol. 12, no. 6, p. 221–222. DOI: 10.1109/LMWC.2002.1010001
  16. SU, W. C., TANG, M. C., EL ARIF, R., et al. Stepped-frequency continuous-wave radar with self-injection-locking technology for monitoring multiple human vital signs. IEEE Transactions on Microwave Theory and Techniques, 2019, vol. 67, no. 12, p. 5396 to 5405. DOI: 10.1109/TMTT.2019.2933199
  17. KAKOUCHE, I., ABADLIA, H., EL KORSO, M. N., et al. Joint vital signs and position estimation of multiple persons using SIMO radar. Electronics, 2021, vol. 10, no. 22, p. 1–15. DOI: 10.3390/electronics10222805
  18. XIONG, J. J., HONG, H., XIAO, L., et al. Chest and abdominal signals separation based on SIMO radar with difference beamforming. IEEE Microwave and Wireless Components Letters, 2022, vol. 32, no. 3, p. 218–221. DOI: 10.1109/LMWC.2022.3144502
  19. FRIENDLANDER, F. On the relationship between MIMO and SIMO radars. IEEE Transactions on Signal Processing, 2009, vol. 57, no. 1, p. 394–398. DOI: 10.1109/TSP.2008.2007106
  20. BOUTTE, D., LEE, H., RADZICKI, V., et al. A portable SIMO radar for through wall detection and imaging. In IEEE Military Communications Conference (MILCOM). Tampa (USA), 2015, p. 204–209. DOI: 10.1109/MILCOM.2015.7357443
  21. XIONG, J. J., HONG, H., ZHANG, H. Q., et al. Multitarget respiration detection with adaptive digital beamforming technique based on SIMO radar. IEEE Transactions on Microwave Theory and Techniques, 2020, vol. 68, no. 11, p. 4814–4824. DOI: 10.1109/TMTT.2020.3020082
  22. HEUERMANN, H., HARZHEIM, T., CRONENBROECK, T. First SIMO harmonic radar based on the SFCW concept and the HR transfer function. Remote Sensing, 2021, vol. 13, no. 24, p. 1 to 23. DOI: 10.3390/rs13245088
  23. LAI, X. P., LAI, C. L., ZHAO, R. J. An iterative approach to near-uniform group-delay error design of FIR filters. IEEE Signal Processing Letters, 2011, vol. 18, no. 2, p. 107–110. DOI: 10.1109/LSP.2010.2099217
  24. PAULI, M., GOTTEL, B., SCHERR, S., et al. Miniaturized millimeter-wave radar sensor for high-accuracy applications. IEEE Transactions on Microwave Theory and Techniques, 2017, vol. 65, no. 5, p. 1707–1715. DOI: 10.1109/TMTT.2017.2677910
  25. VASANELLI, C., BATRA, R., DI SERIO, A., et al. Assessment of a millimeter-wave antenna system for MIMO radar applications. IEEE Antennas and Wireless Propagation Letters, 2017, vol. 16, p. 1261–1264. DOI: 10.1109/LAWP.2016.2631889
  26. FENG, C., JIANG, X. N., JEONG, M. G., et al. Multitarget vital signs measurement with chest motion imaging based on MIMO radar. IEEE Transactions on Microwave Theory and Techniques, 2021, vol. 69, no. 11, p. 4735–4747. DOI: 10.1109/TMTT.2021.3076239

Keywords: Planar location radar, SIMO system, stepped frequency waveform, range-angle correspondence, moving target indicator, sparse array

D. Song, Q. Chen, K. Li [references] [full-text] [DOI: 10.13164/re.2022.0477] [Download Citations]
An Adaptive Sparse Constraint ISAR High Resolution Imaging Algorithm Based on Mixed Norm

Based on the sparsity of inverse synthetic aperture radar (ISAR) signal, in this paper, a novel high resolution imaging algorithm is proposed. In this method, an optimal ISAR signal model based on mixed norm is established by using compressed sensing theory. The high-resolution ISAR image with short coherent accumulation time is realized by solving the optimization model. The main advantages of the proposed approach are: The model makes use of the l2,0 mixed norm to realize faster convergence and improve the computational speed of the model solution obviously. Moreover, according to the result sparsity of each iteration under arbitrary noise, the regularization coefficient in the model can be adjusted adaptively, which avoids the complex process of repeated attempts, otherwise, the optimal coefficient needs to be estimated and attempted by the statistical characteristics of the noise and signal. The effectiveness of the proposed method is verified by simulated and measured data.

  1. KANG, B. S., LEE, K., KIM, K. T. Image registration for 3-D interferometric-ISAR imaging through joint-channel phasedifference functions. IEEE Transactions on Aerospace and Electronic Systems, 2021, vol. 57, no. 1, p. 22–38. DOI: 10.1109/TAES.2020.3021108
  2. SUWA, K., WAKAYAMA, T., IWAMOTO, M. Three-dimensional target geometry and target motion estimation method using multistatic ISAR movies and its performance. IEEE Transactions on Geoscience and Remote Sensing, 2011, vol. 49, no. 6, p. 2361–2373. DOI: 10.1109/TGRS.2010.2095423
  3. OZ, Y., ALP, Y. K., YAZGAN-ERER, I. ISAR imaging under group sparsity constraints using ADMM. In 2020 28th Signal Processing and Communications Applications Conference (SIU). Gaziantep (Turkey), 2020, p. 1–4. DOI: 10.1109/SIU49456.2020.9302303
  4. KANG, M., LEE, S., KIM, K., et al. Bistatic ISAR imaging and scaling of highly maneuvering target with complex motion via compressive sensing. IEEE Transactions on Aerospace and Electronic Systems, 2018, vol. 54, no. 6, p. 2809–2826. DOI: 10.1109/TAES.2018.2830598
  5. XU, G., ZHANG, B. J., CHEN, J. L., et al. Sparse inverse synthetic aperture radar imaging using structured low-rank method. IEEE Transactions on Geoscience and Remote Sensing, 2022, vol. 60, p. 1–12. DOI: 10.1109/TGRS.2021.3118083
  6. ZHANG, L., XING, M. D., QIU, C. W., et al. Resolution enhancement for inversed synthetic aperture radar imaging under low SNR via improved compressed sensing. IEEE Transactions on Geoscience and Remote Sensing, 2010, vol. 48, no. 10, p. 3824 to 3838. DOI: 10.1109/TGRS.2010.2048575
  7. CANDÈS, E., WAKIN, M., BOYD, S. Enhancing sparsity by reweighted l1 minimization. Journal of Fourier Analysis and Applications (Special Issue on Sparsity), 2008, vol. 14, no. 5,p.877–905. DOI: 10.1007/s00041-008-9045-x
  8. FENG, J. J, SUN, Y. N., JI, X. X. High-resolution ISAR imaging based on improved sparse signal recovery algorithm. Wireless Communications and Mobile Computing, 2021, p. 1–7. DOI: 10.1155/2021/5541116
  9. CHEN, Q. Q., XU, G., ZHANG, L., et al. Three-dimensional interferometric inverse synthetic aperture radar imaging with limited pulses by exploiting joint sparsity. IET Radar, Sonar & Navigation, 2015, vol. 9, no. 6, p. 692–701. DOI: 10.1049/iet-rsn.2014.0275
  10. BI, H., LI, Y., ZHU, D. Y., et al. An improved iterative thresholding algorithm for L_1-norm regularization based sparse SAR imaging. Science China (Information Sciences), 2020, vol. 63, no. 11, p. 330–339. DOI: 10.1007/s11432-020-2994-4
  11. LI, Y., JIANG, Z., OSMAN, O. M. O., et al. Mixed norm constrained sparse APA algorithm for satellite and network echo channel estimation. IEEE Access, 2018, vol. 6, p. 65901–65908. DOI: 10.1109/ACCESS.2018.2878310
  12. WEI, X., YANG, J., CHEN, W., et al. Translational motion compensation for ISAR imaging based on range joint fast orthogonal matching pursuit algorithm. IEEE Access, 2022, vol. 10, p. 37382–37395. DOI: 10.1109/ACCESS.2022.3165020
  13. HONG, T., ZHANG, S., LIU, Y. MTRC compensation for sparse aperture ISAR imaging. In 2020 International Conference on Wireless Communications and Smart Grid (ICWCSG). Qingdao (China), 2020, p. 52–56. DOI: 10.1109/ICWCSG50807.2020.00020
  14. BABACAN, S. D., MOLINA, R., KATSAGGELOS, A. K. Bayesian compressive sensing using Laplace priors. IEEE Transactions on Image Processing, 2010, vol. 19, no. 1, p. 53–63. DOI: 10.1109/TIP.2009.2032894
  15. QIN, D., LIU, D., GAO, X., et al. ISAR resolution enhancement using residual network. In 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP). Wuxi (China), 2019, p. 788–792. DOI: 10.1109/SIPROCESS.2019.8868757
  16. YANG, J., LU, X., DAI, Z., et al. Autofocus method for sparseaperture ISAR based on L0 norm and NLTV regularization. In2021 IEEE International Geoscience and Remote SensingSymposium IGARSS. Brussels (Belgium), 2021, p. 5103–5106. DOI: 10.1109/IGARSS47720.2021.9555148
  17. GU, Y., JIN, J., MEI, S. l_0 norm constraint LMS algorithm forsparse system identification. IEEE Signal Processing Letters,2009, vol. 16, no. 9, p. 774–777. DOI: 10.1109/LSP.2009.2024736
  18. LI, B., LIU, F., ZHOU, C., et al. Fast compressed sensing SARimaging using stepped frequency waveform. In 2016 IEEEInternational Conference on Microwave and Millimeter WaveTechnology (ICMMT). Beijing (China), 2016, p. 521–523. DOI:10.1109/ICMMT.2016.7761827
  19. XU, Z. B., CHANG, X. Y., XU, F. M., et al. L1/2 regularization: A thresholding representation theory and a fast solver. IEEETransactions on Neural Networks and Learning Systems, 2012, vol. 23, no. 7, p. 1013–1027. DOI: 10.1109/TNNLS.2012.2197412
  20. EISEN, M., MOKHTARI, A., RIBEIRO, A. Decentralized quasi-Newton methods. IEEE Transactions on Signal Processing, 2017, vol. 65, no. 10, p. 2613–2628. DOI: 10.1109/TSP.2017.2666776
  21. ZHANG, M., WANG, X., CHEN, X., et al. The kernel conjugategradient algorithms. IEEE Transactions on Signal Processing,2018, vol. 66, no. 16, p. 4377–4387. DOI:10.1109/TSP.2018.2853109
  22. YE, Q. L., AMINI, A. A., ZHOU, Q. Optimizing regularizedCholesky score for order-based learning of Bayesian networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, vol. 43, no. 10, p. 3555–3572. DOI:10.1109/TPAMI.2020.2990820

Keywords: Inverse Synthetic Aperture Radar (ISAR), mixed norm, regularization coefficient, sparse constraint

A. N. Yadav [references] [full-text] [DOI: 10.13164/re.2022.0486] [Download Citations]
Tunable Balanced-to-Unbalanced In-Phase Power Divider: Theoretical Analysis and Design

This paper presents a tunable power divider (PD) which is balanced at the input port and unbalanced at the output ports. This tunable balanced-to-unbalanced (TBU) PD divides the power either equally or in specific ratio by varying capacitance in the circuit. The complete theoretical study is presented for this type of PD. The analysis is based on the impedance matching of all the ports and isolation requirements of the two unbalanced output ports. By changing the capacitance, different power dividing ratio (PDR) can be achieved. The theoretical results are obtained from the design equations of the proposed PD. The reflection coefficient of the unbalanced ports are better than 10 dB with fractional bandwidth of 21.5%. The isolation between the two output unbalanced ports is achieved better than 15 dB with fractional bandwidth of 23.5%. The proposed PD shows the in-phase characteristic between the two output signals.

  1. SCHUHLER, M. On evaluation of beamforming networks. IEEE Antennas and Wireless Propagation Letters, 2014, vol. 13, p. 766–769. DOI: 10.1109/LAWP.2014.2316542
  2. LIALIOS, D., ZEKIOS, C. L., GEORGAKOPOULOS, S. V., et al. A mm-wave true-time-delay beamformer architecture based on a blass matrix topology. In IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting. Montreal (QC, Canada), 2020, p. 1609–1610. DOI: 10.1109/IEEECONF35879.2020.9329535
  3. WILKINSON, E. J. An N-way hybrid power divider. IRE Transactions on Microwave Theory and Techniques, 1960, vol. 8, no. 1, p. 116–118. DOI: 10.1109/TMTT.1960.1124668
  4. GYSEL, U. H. A new N-way power divider/combiner suitable for high-power applications. In IEEE-MTT-S International Microwave Symposium. Palo Alto (CA, USA), 1975, p. 116–118. DOI: 10.1109/MWSYM.1975.1123301
  5. WU, L., SUN, Z., YILMAZ, H., et al. A dual-frequency Wilkinson power divider. IEEE Transactions on Microwave Theory and Techniques, 2006, vol. 54, no. 1, p. 278–284. DOI: 10.1109/TMTT.2005.860300
  6. WU, L., YILMAZ, H., BITZER, T., et al. A dual-frequency Wilkinson power divider: For a frequency and its first harmonic. IEEE Microwave and Wireless Components Letters, 2005, vol. 15, no. 2, p. 107–109. DOI: 10.1109/LMWC.2004.842848
  7. LI, J., WANG, B. Novel design of Wilkinson power dividers with arbitrary power division ratios. IEEE Transactions on Industrial Electronics, 2011, vol. 58, no. 6, p. 2541–2546. DOI: 10.1109/TIE.2010.2066536
  8. NWAJANA, A. O., IJEMARU, G. K., ANG, K. L.-M., et al. Unbalanced two-way filtering power splitter for wireless communication systems. Electronics, 2021, vol. 10, no. 5, p. 1–9. DOI: 10.3390/electronics10050617
  9. XIA, B., WU, L. S., REN, S.W., et al. A balanced-to-balanced power divider with arbitrary power division. IEEE Transactions on Microwave Theory and Techniques, 2013, vol. 61, no. 8, p. 2831–2840. DOI: 10.1109/TMTT.2013.2268739
  10. XU, K., SHI, J., LIN, L., et al. A balanced-to-unbalanced microstrip power divider with filtering function. IEEE Transactions on Microwave Theory and Techniques, 2015, vol. 63, no. 8, p. 2561–2569. DOI: 10.1109/TMTT.2015.2445051
  11. ZHANG, W., WU, Y., LIU, Y., et al. A wideband balanced-to-unbalanced coupled-line power divider. IEEE Microwave and Wireless Components Letters, 2016, vol. 26, no. 6, p. 410–412. DOI: 10.1109/LMWC.2016.2561400
  12. YADAV, A. N., BHATTACHARJEE, R. Balanced to unbalanced power divider with arbitrary power ratio. IEEE Microwave and Wireless Components Letters, 2016, vol. 26, no. 11, p. 885–887. DOI: 10.1109/LMWC.2016.2615006
  13. ZHU, Y., SONG, K., FAN, M., et al. Wideband single-ended-tobalanced power divider with intrinsic common-mode suppression. IEEE Microwave and Wireless Components Letters, 2020, vol. 30, no. 4, p. 379–382. DOI: 10.1109/LMWC.2020.2973863
  14. SHI, J., YIN, Z., LU, J., et al. An approach to N-stage balanced-to-single- ended out-of-phase power divider with enhanced operating bandwidth. IEEE Access, 2020, vol. 8, p. 13584–13592. DOI: 10.1109/ACCESS.2020.2966490
  15. YADAV, A. N., BHATTACHARJEE, R. Balanced-to-unbalanced in-phase power divider. In IEEE MTT-S International Microwave and RF Conference (IMaRC). Ahmedabad (India), 2017, p. 1–4. DOI: 10.1109/IMaRC.2017.8449687
  16. XIAO, Y., LIN, F., MA, H., et al. A planar balanced power divider with tunable power-dividing ratio. IEEE Transactions on Microwave Theory and Techniques, 2017, vol. 65, no. 12, p. 4871–4882. DOI: 10.1109/TMTT.2017.2722403
  17. FAN, W., LU, A., WAI, L., et al. Mixed-mode S-parameter characterization of differential structures. In Proceedings of the 5th Electronics Packaging Technology Conference (EPTC). Singapore, 2003, p. 533–537. DOI: 10.1109/EPTC.2003.1271579
  18. POZAR, D. M. Microwave Engineering. 4th ed., Wiley, 2012. ISBN: 9780470631553

Keywords: Tunable power divider, balanced-to-unbalanced, differential mode, microwave circuit

C. Chen, F. F. Yang, C. L. Zhao, H. J. Xu [references] [full-text] [DOI: 10.13164/re.2022.0496] [Download Citations]
Distributed Reed-Solomon Coded Cooperative Space-Time Labeling Diversity Network

This paper proposes a distributed Reed-Solomon coded cooperative labeling diversity (DRSCC-LD) scheme over the Rayleigh frequency-flat fast fading channel to further improve the BER performance. The non-binary Reed-Solomon (RS) code with more consecutive roots is applied at the relay to provide additional redundancy. As a novel diversity technique, labeling diversity (LD) with three different mappers is employed in the proposed DRSCC-LD scheme utilizing 16-QAM and 64-QAM, respectively, which may achieve diversity gain and greatly decrease the error floor (EF). Besides, a reduced-complexity detection algorithm based on a variable signal subset (RC-VSS) is proposed to lower the complexity of detection at both relay and destination. The proposed critical SNR-assisted (CSA) joint decoding algorithm then collaborates with the joint detection based on the RC-VSS algorithm to improve the overall BER performance. Theoretical analysis and Monte Carlo simulated results reveal that the proposed DRSCC-LD scheme clearly outperforms its corresponding non-cooperative RS coded scheme by a gain of more than 7 dB and the existing schemes by a margin of more than 3.5 dB under the identical conditions, respectively.

  1. GOVINDASAMY, K., XU, H. J., PILLAY, N. Space-time block coded spatial modulation with labeling diversity. International Journal of Communication Systems, 2017, vol. 31, no. 1, p. 1–15. DOI: 10.1002/dac.3395
  2. LI, X. D., CHINDAPOL, A., RITCEY, J. A. Bit-interleaved coded modulation with iterative decoding and 8PSK signaling. IEEE Transactions on Communications, 2002, vol. 50, no. 8, p. 1250–1257. DOI: 10.1109/TCOMM.2002.801524
  3. CHINDAPOL, A., RITCEY, J. A. Design, analysis, and performance evaluation for BICM-ID with square QAM constellations in Rayleigh fading channels. IEEE Journal on Selected Areas in Communications, 2001, vol. 19, no. 5, p. 944–957. DOI: 10.1109/49.924878
  4. HUANG, Y. H., RITCEY, J. A. Optimal constellation labeling for iteratively decoded bit-interleaved space-time coded modulation. IEEE Transactions on Information Theory, 2005, vol. 51, no. 5, p. 1865–1871. DOI: 10.1109/TIT.2005.846409
  5. HUANG, Y. H., RITCEY, J. A. Improved 16-QAM constellation labeling for BI-STCM-ID with the Alamouti scheme. IEEE Communications Letters, 2005, vol. 9, no. 2, p. 157–159. DOI: 10.1109/LCOMM.2005.02002
  6. KRASICKI, M. Labelling diversity for MIMO systems. In European Wireless Conference–Sustainable Wireless Technologies (European Wireless). Vienna (Austria), 2011, p. 1–7. ISBN: 9783800733439
  7. KRASICKI, M. Essence of 16-QAM labelling diversity. Electronics Letters, 2013, vol. 49, no. 8, p. 567–569. DOI: 10.1049/el.2012.4275
  8. VAN DER MEULEN, E. C. Three-terminal communication channels. Advances in Applied Probability, 1971, vol. 3, no. 1, p. 120–154. DOI: 10.2307/1426331
  9. HUNTER, T. E., SANAYEI, S., NOSRATINIA, A. Outage analysis of coded cooperation. IEEE Transactions on Information Theory, 2006, vol. 52, no. 2, p. 375–391. DOI: 10.1109/TIT.2005.862084
  10. ZHAO, C. L., YANG, F. F., UMAR, R., et al. Two-source asymmetric turbo-coded cooperative spatial modulation scheme with code matched interleaver. Electronics, 2020, vol. 9, no. 1, p. 1–20. DOI: 10.3390/electronics9010169
  11. MUGHAL, S., YANG, F. F., UMAR, R. Reed-Muller network coded-cooperation with joint decoding. IEEE Communications Letters, 2019, vol. 23, no. 1, p. 24–27. DOI: 10.1109/LCOMM.2018.2879101
  12. WANG, H., CHEN, Q. C. LDPC based network coded cooperation design for multi-way relay networks. IEEE Access, 2019, vol. 7, p. 62300–62311. DOI: 10.1109/ACCESS.2019.2915293
  13. RIJAL, H., YANG, F. F., RODOR, G. Optimized QC-LDPC coded cooperation for single relay wireless cooperative communication system. In 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). Chengdu (China), 2021, p. 340–343. DOI: 10.1109/ICCWAMTIP53232.2021.9674081
  14. DIA, D., M., DIOUF, M. D., DIOP, I. Performance of polar codes in cooperative transmission systems. In Proceedings of 2nd International Conference on Electrical, Communication, and Computer Engineering (ICECCE). Istanbul (Turkey), 2020, p. 1–5. DOI: 10.1109/ICECCE49384.2020.9179453
  15. LIANG, H., LIU, A. J., LIU, X., et al. Construction and optimization for adaptive polar coded cooperation. IEEE Wireless Communications Letters, 2020, vol. 9, no. 8, p. 1187–1190. DOI: 10.1109/LWC.2020.2984738
  16. EJAZ, S., YANG, F. F., XU, H. J. Labeling diversity for 2 x 2 WLAN coded-cooperative networks. Radioengineering, 2015, vol. 24, no. 2, p. 470–480. DOI: 10.13164/re.2015.0470
  17. EJAZ, S., YANG, F. F., XU, H. J. Split labeling diversity for wireless half-duplex relay assisted cooperative communication systems. Telecommunication Systems, 2020, vol. 75, no. 4, p. 437–446. DOI: 10.1007/s11235-020-00694-6
  18. ALMAWGANI, A. H. M., SALLEH, M. F. M. RS coded cooperation with adaptive cooperation level scheme over multipath Rayleigh fading channel. In IEEE 9th Malaysia International Conference on Communications (MICC). Kuala Lumpur (Malaysia), 2009, p. 480–484. DOI: 10.1109/MICC.2009.5431555
  19. GUO, P. C., YANG, F. F, ZHAO, C. L., et al. Jointly optimized design of distributed Reed-Solomon codes by proper selection in relay. Telecommunication Systems, 2021, vol. 78, no. 3, p. 391–403. DOI: 10.1007/s11235-021-00822-w
  20. ZHAO, C. L., YANG, F. F., CHEN, C., et. al. Reed-Solomon coded cooperative space-time block coded spatial modulation. In International Conference on Wireless Communications and Smart Grid (ICWCSG). Hangzhou (China), 2021, p. 99–103. DOI: 10.1109/ICWCSG53609.2021.00027
  21. AYANDA, D. Performance analysis of M-ary amplitude and phase shift keying uncoded space-time labeling diversity with three transmit antennas in nonlinear Rician. Transactions on Emerging Telecommunications Technologies, 2021, vol. 32, no. 11. DOI: 10.1002/ett.4348
  22. SOLWA, S., ELMEZUGHI, M. K., BAMISAYE, A. J., et al. Genetic algorithm-based uncoded M-ary phase shift keying space-time labelling diversity with three transmit antennas for future wireless networks. In 9th International Conference on Electrical and Electronics Engineering (ICEEE). Alanya (Turkey), 2022, p. 423–428. DOI: 10.1109/ICEEE55327.2022.9772544
  23. XU, H. J., GOVINDASAMY, K., PILLAY, N. Uncoded space-time labeling diversity. IEEE Communications Letters, 2016, vol. 20, no. 8, p. 1511–1514. DOI: 10.1109/LCOMM.2016.2580503
  24. AYANDA, D., XU, H. J., PILLAY,N.Uncoded M-ary quadrature amplitude modulation space-time labeling diversity with three transmit antennas. International Journal of Communication Systems, 2018, vol. 31, no. 8, p. 1–13. DOI: 10.1002/dac.3818
  25. BAHNG, S., SHIN, S., PARK, Y. O. ML Approaching MIMO detection based on orthogonal projection. IEEE Communications Letters, 2007, vol. 11, no. 6, p. 474–476. DOI: 10.1109/LCOMM.2007.070146
  26. BARRY, J. R., LEE, E. A., MESSERSCHMITT, D. G. Digital Communication. 3rd ed. Springer US, 2004. ISBN: 9781461502272

Keywords: Reed-Solomon (RS) code, distributed coded cooperation, labeling diversity (LD), detection algorithm, joint decoding algorithm

L. Ge, Z. Wang, L. Qian, P. Wei, F. Gao, M. Li [references] [full-text] [DOI: 10.13164/re.2022.0510] [Download Citations]
Improved Phase Noise Compensation in OFDM Systems

Phase noise (PN) consists of common phase error (CPE) and inter carrier interference (ICI). In an OFDM symbol, CPE has the same impact on each subcarrier, which is easy to be suppressed. However, ICI destroys the orthogonality of subcarriers, which is difficult to be eliminated. Therefore, an additional method is needed to be performed in the OFDM receiver to compensate the ICI. The interpolation method is considered an effective way to eliminate the ICI caused by PN in the OFDM system. To enhance the accuracy of the PN estimation and compensation, we propose a linear method, LI-ICI-EE1 method based on LI-ICI-E1. Multiple interpolation slopes are first calculated by selecting multiple pairs of observation samples, then the slope with the maximal linear fitting degree based on the least square (LS) criterion is selected to improve the LI precision. Furthermore, to improve the estimation accuracy of PN in the LI-ICI-EE1, we propose a Shrinkage-based on LI-ICI-E1 method named SLI-EE1, which is implemented by adding an l2 norm penalty term to the error function. At last, to optimize the low accuracy of LI-ICI-EE1 and SLI-EE1 when the PN compensation problem is a high-order problem, we propose a non-linear method Shrinkage-based Third-order Lagrange method named STL. Simulation results show that the improved methods have better BER performance.

  1. GE, L., ZHANG, Y., CHEN, G., et al. Compression-based LMMSE channel estimation with adaptive sparsity for massive MIMO in 5G systems. IEEE System Journal, 2019, vol. 13, no. 4, p. 3847–3857. DOI: 10.1109/JSYST.2019.2897862
  2. MATHECKEN, P. T., RIIHONEN, T. S., WERNER, T. Performance analysis of OFDM with wiener phase noise and frequency selective fading channel. IEEE Transactions on Communications, 2011, vol. 59, no. 5, p. 1321–1331. DOI: 10.1109/TCOMM.2011.030411.100401
  3. NEGUSSE, S., ZETTERBERG, P., HANDEK, P. Phase-noise mitigation in OFDM by best match trajectories. IEEE Transactions on Communications, 2015, vol. 63, no. 5, p. 1712–1725. DOI: 10.1109/TCOMM.2015.2422829
  4. MATHECKEN, P., RIIHONEN, T., WERNER, S., et al. Constrained phase noise estimation in OFDM using scattered pilots without decision feedback. IEEE Transactions on Signal Processing, 2017, vol. 65, no. 9, p. 2348–2362. DOI: 10.1109/TSP.2017.2655481
  5. WANG, W., WANG, Z., ZHANG, C., et al. A BP-MF-EP based iterative receiver for joint phase noise estimation, equalization and decoding. IEEE Signal Processing Letters, 2016, vol. 23, no. 10, p. 1349–1353. DOI: 10.1109/LSP.2016.2593917
  6. SOLTANI, M., POURAHMADI, V., MIRZAEI, A., et al. Deep learning-based channel estimation. IEEE Communications Letters, 2019, vol. 23, no. 4, p. 652–655. DOI: 10.1109/LCOMM.2019.2898944
  7. RUI,W., HANI, M., MEI, X., et al. Channel estimation, carrier recovery, and data detection in the presence of phase noise in OFDM relay systems. IEEE Transactions on Wireless Communications, 2016, vol. 15, no. 2, p. 1186–1205. DOI: 10.1109/TWC.2015.2487268
  8. AMIRHOSSEIN, M., CHINTHA, T., GEOFFREY, L. Y. Deep learning-based phase noise compensation in multicarrier systems. IEEE Wireless Communications Letters, 2021, vol. 10, no. 10, p. 2110–2114. DOI: 10.1109/LWC.2021.3093574
  9. MATTU, S. R., CHOCKALINGAM, A. Learning based channel estimation and phase noise compensation in doubly-selective channels. IEEE Communications Letters, 2022, vol. 26, no. 5, p. 1052–1056. DOI: 10.1109/LCOMM.2022.3155186
  10. BITTERNER, S., ZIMMERMANN, E., FETTEIS, G. Exploiting phase noise properties in the design of MIMO-OFDM receivers. In IEEE Wireless Communications and Networking Conference (WCNC). Las Vegas (NV, USA), 2008, p. 940–945. DOI: 10.1109/ICTC52510.2021.9621195
  11. SYRJALA, V., VALKAMA, M., TCHAMOV, N. N., et al. Phase noise modelling and mitigation techniques in ofdm communications systems. In Wireless Telecommunications Symposium (WTS). Prague (Czechia), 2009, p. 1–7. DOI: 10.1109/WTS.2009.5068965
  12. TCHAMOV,N.N., RINNE, J., HAZMI, A., et al. Enhanced algorithm for digital mitigation of ICI due to phase noise in OFDM receivers. IEEE Wireless Communications Letters, 2013, vol. 2, no. 1, p. 6–9. DOI: 10.1109/WCL.2012.091912.120412
  13. YUAN, J., ZHANG, F., QIU, P., et al. A novel phase noise suppression algorithm in CO-OFDM systems. Semiconductor Optoelectronics, 2017, vol. 38, no. 4, p. 557–561. Available at: http://en.cnki.com.cn/Article_en/CJFDTotal-BDTG201704023.htm
  14. BAO, W., BI, M., XIAO, S., et al. Lagrange interpolation based extended Kalman filter for phase noise suppression in CO-OFDM system. Optics Communications, 2019, vol. 435, p. 221–226. DOI: 10.1016/j.optcom.2018.11.027
  15. LESHEM, A., YEMINI, M. Phase noise compensation for OFDM systems. IEEE Transactions on Signal Processing, 2017, vol. 65, no. 21, p. 5675–5686. DOI: 10.1109/TSP.2017.2740165
  16. TONG, J., HU, R., XI, J., et al. Linear shrinkage estimation of covariance matrices using low-complexity cross-validation. Signal Processing, 2018, vol. 148, p. 223–233. DOI: 10.1016/j.sigpro.2018.02.026
  17. DONG, L., ZHAO, H., CHEN, Y., et al. Introduction on IMT-2020 5G trials in China. IEEE Journal on Selected Areas in Communications, 2017, vol. 35, no. 8, p. 1849–1866. DOI: 10.1109/JSAC.2017.2710678
  18. GAO, Z., DAI, L.,WANG, Z., et al. Spatially common sparsity based adaptive channel estimation and feedback for FDD massive MIMO. IEEE Transactions on Signal Processing, 2015, vol. 63, no. 23, p. 6169–6183. DOI: 10.1109/TSP.2015.2463260

Keywords: Channel estimation, phase noise, orthogonal frequency division multiplexing, shrinkage technique, third-order Lagrange method

A. Kovalova, L. Hudcova, R. Roka [references] [full-text] [DOI: 10.13164/re.2022.0520] [Download Citations]
Optical Ray Transfer Matrix Model of the Turbulent Cells Cascade

The paper offers a new approach to modeling atmospheric turbulence consisting of turbulent cells whose size is larger than the optical beam width. Particular turbulent cells are approximated by an optical element matrix. The ray transfer matrix method is presented, through which the optical elements can be described in the matrix form. A deflection simulation was performed that indicated the behavior of the optical beam by passing through the optical element. Furthermore, the calculation of the deflection vector is described together with a cascade model of turbulent cells. The matrix calculation for the cascade of optical elements is also expressed.

  1. KHALIGHI, M. A., UYSAL, M. Survey on free space optical communication: A communication theory perspective. IEEE Communications Surveys and Tutorials, 2014, vol. 16, no. 4, p. 2231–2258. DOI: 10.1109/COMST.2014.2329501
  2. BARCIK, P., WILFERT, O., DOBESCH, A., et al. Experimental measurement of the atmospheric turbulence effects and their influence on performance of fully photonic wireless communication receiver. Physical Communication, 2018, vol. 31, p. 212–217. DOI: 10.1016/j.phycom.2018.05.003
  3. SIEGEL, T., CHEN, S.-P. Investigations of free space optical communications under real-world atmospheric conditions. Wireless Personal Communications, 2021, vol. 116, p. 475–490. DOI: 10.1007/s11277-020-07724-1
  4. SAHA, D., ROY, J., FIABOE, K. F., et al. Design and analysis of FSO (Free Space Optics) link at high bit rate. In Third International Conference on Inventive Systems and Control (ICISC). Coimbatore (India), 2019, p. 62–66. DOI: 10.1109/ICISC44355.2019.9036358
  5. BAG, B., DAS, A., CHANDRA, A., et al. Performance analysis of FSO links in turbulent atmosphere. Chapter in Design, Implementation and Analysis of Next Generation Optical Networks. 2019. DOI: 10.4018/978-1-5225-9767-4.ch004
  6. ZHANG, J., LI, R., GAO, Z., et al. Ergodicity of phase fluctuations for free-space optical link in atmospheric turbulence. IEEE photonics technology letters, 2019, vol. 31, no. 5, p. 377–380. DOI: 10.1109/LPT.2019.2895886
  7. ROKA, R., STEFANOVIC, C., MORALES-CESPEDES, M., et al. Performance analysis of the FBMC modulation format in optical fiber and wireless communications. In International Symposium on Wireless Communication Systems (ISWCS). Berlin (Germany), 2021, p. 1–6. DOI: 10.1109/ISWCS49558.2021.9562137
  8. POLIAK, J., KOMRSKA, J., WILFERT, O. Restricted beam analysis for FSO links. In European Conference on Antennas and Propagation (EUCAP). Prague (Czech Republic), 2012, p. 335–339. DOI: 10.1109/EuCAP.2012.6206678
  9. PRABU, K., SRIRAM KUMAR, D., SRINIVAS, T. Performance analysis of FSO links under strong atmospheric turbulence conditions using various modulation schemes. Optik, 2014, vol. 125, no. 19, p. 5573–5581. DOI: 10.1016/j.ijleo.2014.07.028
  10. AHMED, A., SINGH, A., SINGH, A., et al. Performance analysis of WDM-MIMO free space optical system under atmospheric turbulence. In International Conference on Signal Processing and Integrated Networks (SPIN). Noida (India), 2019, p. 820–825. DOI: 10.1109/SPIN.2019.8711685
  11. YANG, G., LI, Z., BI, M., et al. Channel modeling and performance analysis of modulating retroreflector FSO systems under weak turbulence conditions. IEEE Photonics Journal, 2017, vol. 9, no. 2, p. 1–10. DOI: 10.1109/JPHOT.2017.2677501
  12. ANDREWS, L. C., PHILIPS, R. L. Laser Beam Propagation through Random Media. Bellingham: SPIE Optical Engineering Press, 1998. ISBN: 081942787X
  13. ANDREWS, L. C., PHILIPS, R. L., HOPEN, C. Y. Laser Beam Scintillation with Applications. Bellingham: SPIE, 2001. ISBN: 9780819478511
  14. MAJUMDAR, A. K., RICKLIN, J. C. Free-Space Laser Communications: Principles and Advances. New York: Springer, 2008. ISBN: 9780387286525
  15. HUDCOVA, L., WILFERT, O. Determination of the atmospheric turbulence by the analysis of the optical beam deflection. In International Conference Radioelektronika (RADIOELEKTRONIKA). Bratislava (Slovakia), 2020, p. 1–5. DOI: 10.1109/RADIOELEKTRONIKA49387.2020.9092387
  16. GERRARD, A., BURCH, J. M. Introduction to Matrix Methods in Optics. New York: Dover, 1994. ISBN: 0486680444
  17. KOGELNIK, H., LI, T. Laser beams and resonators. Proceedings of the IEEE, 1966, vol. 54, no. 10, p. 1312–1329. DOI: 10.1109/PROC.1966.5119
  18. KOVALOVA, A. Quantification of Turbulence by the Equivalent Temperature Gradient (in Slovak). Master’s Thesis, Brno University of Technology, Brno, 2021. Available at: https://www.vutbr.cz/studenti/zav-prace/detail/133605

Keywords: Atmospheric turbulence, matrix optics, cascade of turbulent cells, ABCD matrix, reciprocity

Z. L. Zhu, J. L. Li [references] [full-text] [DOI: 10.13164/re.2022.0527] [Download Citations]
Design of Dual-Mode Loop Resonator-Based Microwave Diplexers with Enhanced Performance

In this paper, a dual-mode loop resonator based circuit topology is studied for microwave diplexer applications. Several diplexers, with dense and sparse channel separations, are further discussed based on the introduced topology, featuring capable of controlling transmission zeros flexibly. Hence microwave diplexers with high selectivity and good channel isolation can be realized by placing transmission zeros of the channel filters at the desired channels. With the use of the proposed topology, the achieved center frequency ratio between two channels can be from 1.03 to 1.35 with good isolations, high selectivity and compact size. The demonstration diplexers are realized on PCB processes, but can be implemented with other media including MMIC. Experimental validations on the developed demonstrator are presented in the paper, and measured responses match well the full-wave electromagnetic simulated results. The developed UMTS diplexer demonstrator achieves the measured minimum passband insertion losses of 2.55 and 2.7 dB with return losses better than 15 dB and channel isolations over 40 dB at the two channels.

  1. MATTHAEI, G. L., CRISTAL, E. G. Multiplexer channelseparating units using interdigital and parallel-coupled filters. IEEE Transactions on Microwave Theory and Techniques, 1965, vol. 13, no. 3, p. 328–334. DOI: 10.1109/TMTT.1965.1125997
  2. WENZEL, R. J. Printed-circuit complementary filters for narrow bandwidth multiplexers. IEEE Transactions on Microwave Theory and Techniques, 1968, vol. 16, no. 3, p. 147–157. DOI: 10.1109/TMTT.1968.1126635
  3. CHUANG, M. L., WU, M. T. Microstrip diplexer design using common T-shaped resonator. IEEE Microwave and Wireless Components Letters, 2011, vol. 21, no. 11, p. 583–585. DOI: 10.1109/LMWC.2011.2168949
  4. CHEN, C. F., HUANG, T. Y., CHOU, C. P., et al. Microstrip diplexers design with common resonator sections for compact size, but high isolation. IEEE Transactions on Microwave Theory and Techniques, 2006, vol. 54, no. 5, p. 1945–1952. DOI: 10.1109/TMTT.2006.873613
  5. TANTIVIWAT, S., INTARAWISET, N., JEENAWONG, R. Wide-stopband, compact microstrip diplexer with common resonator using stepped-impedance resonators. In 1st IEEE Tencon Spring Conference for Region 10. Sydney (Australia), 2013, p. 174–177. DOI: 10.1109/TENCONSpring.2013.6584435
  6. CHEN, D., ZHU, L., BU, H., et al. A novel planar diplexer using slotline-loaded microstrip ring resonator. IEEE Microwave and Wireless Components Letters, 2015, vol. 25, no. 11, p. 706–708. DOI: 10.1109/LMWC.2015.2479836
  7. GUAN, X., YANG, F., LIU, H., et al. Compact and high-isolation diplexer using dual-mode stub-loaded resonators. IEEE Microwave and Wireless Components Letters, 2014, vol. 24, no. 6, p. 385 to 387. DOI: 10.1109/LMWC.2014.2313591
  8. PENG, H. S., CHIANG, Y. C. Microstrip diplexer constructed with new types of dual-mode ring filters. IEEE Microwave and Wireless Components Letters, 2015, vol. 25, no. 1, p. 7–9. DOI: 10.1109/LMWC.2014.2365740
  9. SONG, K., YAN, Y., ZHONG, C., et al. Compact multimoderesonator diplexer with wide upper-stopband and high isolation. Electromagnetics, 2019, vol. 39, no. 4, p. 262–270. DOI: 10.1080/02726343.2019.1595387
  10. SONG, K., ZHOU, Y., CHEN, Y., et al. Compact high-isolation multiplexer with wide stopband using spiral defected ground resonator. IEEE Access, 2019, vol. 7, p. 31702–31710. DOI: 10.1109/ACCESS.2019.2901794
  11. DONG, Y., ITOH, T. Substrate integrated waveguide loaded by complementary split-ring resonators for miniaturized diplexer design. IEEE Microwave and Wireless Components Letters, 2011, vol. 21, no. 1, p. 10–12. DOI: 10.1109/LMWC.2010.2091263
  12. YANG, T., CHI, P. L., ITOH, T. High isolation and compact diplexer using the hybrid resonators. IEEE Microwave and Wireless Components Letters, 2010, vol. 20, no. 10, p. 551–553. DOI: 10.1109/LMWC.2010.2052793
  13. GORUR, A. K., TURKELI, A., DOGAN, E., et al. A novel compact microstrip diplexer with closely spaced channels. In 50th European Microwave Conference. Utrecht (The Netherlands), 2020, p. 116–119. DOI: 10.23919/EuMC48046.2021.9338170
  14. LUO, S., ZHU, L., SUN, S. A dual-band ring-resonator bandpass filter based on two pairs of degenerate modes. IEEE Transactions on Microwave Theory and Techniques, 2010, vol. 58, no. 12, p. 3427–3432. DOI: 10.1109/TMTT.2010.2053590
  15. NWAJANA, A. O., YEO, K. S. K. Microwave diplexer purely based on direct synchronous and asynchronous coupling. Radioengineering, 2016, vol. 25, no. 2, p. 247–252. DOI: 10.13164/re.2016.0247

Keywords: Microwave diplexer, dual-mode resonator, loop resonator, microstrip resonator

Y.-Y. Won, S. M. Yoon [references] [full-text] [DOI: 10.13164/re.2022.0533] [Download Citations]
Simultaneous Wireless Transmission Based on Visible LED of On-Off-Keying and Discrete Multitone Signal Using Sparse Compressive Sampling and Derivative-Subtractive Sampling

We propose a technique for simultaneously transmitting two signals with different waveforms (non-return-to-zero on-off keying (NRZ-OOK) signal and discrete multi-tone (DMT) signal) in an optical wireless link based on visible light emitting diode (LED). A sparse compressive sampling technique is proposed to reduce the length of the DMT signal encoded by quadrature phase shift keying (QPSK) symbols and a derivative-subtractive sampling is proposed to separate the NRZ-OOK signal and the DMT signal from the mixed signal (NRZ-OOK + DMT). It is possible to reduce the length of the DMT signal up to 38% using the sparse compressive sampling technique. A 37.6-Mb/s transmission capacity (NRZ-OOK: 10 Mb/s, QPSK symbols: 20 Mb/s + 7.6 Mb/s) is achieved over 10 ­MHz bandwidth.

  1. WU, X., SOLTANI, M. D., ZHOU, L., et al. Hybrid LiFi and WiFi networks: A survey. IEEE Communications Surveys & Tutorials, 2021, vol. 23, no. 2, p. 1398–1420. DOI: 10.1109/COMST.2021.3058296
  2. CHOWDHURY, M. Z., HASAN, M. K., SHAHJALAL, M., et al. Optical wireless hybrid networks: Trends, opportunities, challenges, and research directions. IEEE Communications Surveys & Tutorials, 2020, vol. 22, no. 2, p. 930–966. DOI: 10.1109/COMST.2020.2966855
  3. CISCO. Cisco Visual Networking Index: Forecast and Trends, 2017–2022. Cisco, San Jose, CA, USA, Rep., Nov. 2018.
  4. ZHANG, D., ZHOU, Z., MUMTAZ, S., et al. One integrated energy efficiency proposal for 5G IoT communications. IEEE Internet of Things Journal, 2016, vol. 3, no. 6, p. 1346–1354. DOI: 10.1109/JIOT.2016.2599852
  5. DE VRIES, J. P., SIMIĆ, L., ACHTZEHN, A., et al. The Wi-Fi “congestion crisis”: Regulatory criteria for assessing spectrum congestion claims. Telecommunications Policy, 2014, vol. 38, no. 8–9, p. 838–850. DOI: 10.1016/j.telpol.2014.06.005
  6. POHLMANN, C. Visible light communication. In Proceedings of Seminar Kommunikationsstandards der Medizintechnik, 2010, p. 1–14.
  7. MATHEUS, L. E. M., VIEIRA, A. B., VIEIRA, L. F. M., et al. Visible light communication: Concepts, applications and challenges. IEEE Communications Surveys & Tutorials, 2019, vol. 21, no. 4, p. 3204–3237. DOI: 10.1109/COMST.2019.2913348
  8. HAAS, H., YIN, L., WANG, Y., et al. What is LiFi? Journal of Lightwave Technology, 2016, vol. 34, no. 6, p. 1533–1544. DOI: 10.1109/JLT.2015.2510021
  9. ISLIM, M. S., FERREIRA, R. X., HE, X., et al. Towards 10 Gb/s orthogonal frequency division multiplexing-based visible light communication using a GaN violet micro-LED. Photonics Research, 2017, vol. 5, no. 2, p. A35–A43. DOI: 10.1364/PRJ.5.000A35
  10. BINH, P. H., HUNG, N. T. High-speed visible light communications using ZnSe-based white light emitting diode. IEEE Photonics Technology Letters, 2017, vol. 28, no. 18, p. 1948–1951. DOI: 10.1109/LPT.2016.2578964
  11. COSSU, G., KHALID, A. M., CHOUDHURY, P., et al. 3.4 Gbit/s visible optical wireless transmission based on RGB LED. Optics Express, 2012, vol. 20, no. 26, p. B501–B506. DOI: 10.1364/OE.20.00B501
  12. WANG, Y., HUANG, X., TAO, L., et al. 4.5-Gb/s RGB-LED based WDM visible light communication system employing CAP modulation and RLS based adaptive equalization. Optics Express, 2015, vol. 23, no. 10, p. 13626–13633. DOI: 10.1364/OE.23.013626
  13. GOLDSTEIN, T., OSHER, S. The split Bregman method for L1-regularized problems. SIAM Journal on Imaging Sciences, 2009, vol. 2, no. 2, p. 323–343. DOI: 10.1137/080725891
  14. DONOHO, D. L. Compressed sensing. IEEE Transactions on Information Theory, 2006, vol. 52, no. 4, p. 1289–1306. DOI: 10.1109/TIT.2006.871582

Keywords: Derivative-subtractive sampling, discrete multi-tone, optical wireless transmission, sparse compressive sampling, white light emitting diode

Z. Tengah, N. H. Abd Rahman, Y. Yamada, N. E. Abd Rashid, I. Pasya, M. A. Aris, N. Q. Dinh [references] [full-text] [DOI: 10.13164/re.2022.0541] [Download Citations]
Design of Bifurcated Beam using Convex Bent Array Feed for Satellite Mobile Earth Station Application

For multibeam operation at the satellite mobile earth station and telecommunication base stations, a cylindrical lens antenna with multi-feed is a promising candidate due to the simple antenna configuration and good scanning performance to produce multi beams. However, efficient illumination at the lens surface is critical. Previously, the present antennas were used; however, a significant ta-pered distribution is observed, resulting in under-illumination at the lens edges. The feed positions are re-quested to be placed near the lens to achieve a slender lens form. Therefore, the feed radiation pattern should have high radiations at the wide-angle region. This paper proposes a bifurcated beam array antenna to alter the amplitude distribution. This method is expected to improve the radiation pattern coverage area. In designing a bifur-cated beam antenna, the important parameter is to ensure that the separated beams have the same current phase excitations at each radiating element and a precise patch arrangement to achieve the targeted radiation pattern. The differences in surface current will affect the radiation patterns due to the significant interference and cancella-tion effects which will contribute to high losses. This pa-per forms the array by a convex bent array with the same phase excitation for all patch elements. The feed perfor-mances are also verified by the good agreement between simulated and measured results. An improved aperture distribution is demonstrated for array feed having 0.7λo spacing compared to the tapered distribution by a single patch design with the hyperbolic lens through detailed analysis and comparative study. By changing the spacing distance of the convex bent array, many radiation patterns are observed, such as strong radiation in the wide-angle region, the uniform radiation level in a wide-angle region, and the tapered radiation pattern. Thus, many aperture distributions of center-dip, uniform and tapered, are achieved.

  1. WANG, W., LIU, A., ZHANG, Q., et al. Robust multigroup mul-ticast transmission for frame-based multibeam satellite systems. IEEE Access, 2018, vol. 6, p. 46074–46083. DOI: 10.1109/ACCESS.2018.2865998
  2. HASSAN, W. A., JO, H. S., THAREK, A. R. The feasibility of coexistence between 5G and existing services in the IMT-2020 candidate bands in Malaysia. IEEE Access, 2017, vol. 5, p. 14867 to 14888. DOI: 10.1109/ACCESS.2017.2690309
  3. SAADA, M. H. A. Design of efficient millimeter wave planar an-tenna for 5G communication systems. M. S. Thesis, The Islamic University of Gaza, 2017. DOI: 10.13140/RG.2.2.13540.37760
  4. RAHIMA, S. K. A., HAKIMI, S., YAMADA, Y., et al. Investiga-tion of pencil and bifurcated beam fed cylindrical dielectric lens antenna for 5G mobile base stations. Journal of Telecommunica-tion, Electronic and Computer Engineering, 2017, vol. 9, no. 1–5, p. 27–32. ISSN 2180-1843
  5. AHMADI, S. Toward 5G Xilinx solutions and enablers for next-generation wireless systems. White Paper: Xilinx MPSoCs and FPGAs, 2016, vol. 1, p. 1–32. Available at: https://docs.xilinx.com/v/u/en-US/wp476-toward-5g
  6. TENGAH, Z., ALI, M. T., ABD RAHMAN, N. H., et al. Achievement of a bifurcated beam by a bend-array configuration. In Proceedings of the 2016 6th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications. Cairns (Australia), 2016, p. 1–4. DOI: 10.1109/APWC.2016.7738137
  7. TANAKA, M., NAKAMURA, M., KAWAI, M., et al. Experi-mental fixed and mobile multibeam satellite communications system. In IEEE International Conference on Communications. Bos-ton (USA), 1989, p. 1–8. DOI: 10.1109/ICC.1989.49945
  8. PARCHIN, N. O., SHEN, M., PEDERSEN, G. F. Small-size ta-pered slot antenna (TSA) design for use in 5G phased array appli-cations. ACES Journal, 2017, vol. 32, no. 3, p. 193–202. ISSN: 1943-5711
  9. OJAROUDIPARCHIN, N., SHEN, M., PEDERSEN, G. F. A 28 GHz FR-4 compatible phased array antenna for 5G mobile phone applications. In 2015 International Symposium on Antennas and Propagation (ISAP). Hobart (TAS, Australia), 2015, p. 1–4. ISBN: 978-4-8855-2302-1
  10. HUANG, F., CHEN, W., RAO, M. Switched-beam antenna array based on Butler matrix for 5G wireless communication. In 2016 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM). Nanjing (China), 2016, p. 1–3. DOI: 10.1109/iWEM.2016.7505030
  11. MOODY, H. The systematic design of the Butler matrix. IEEE Transactions on Antennas and Propagation, 1964, vol. 12, no. 6, p. 786–788. DOI: 10.1109/TAP.1964.1138319
  12. ROTMAN, W., TURNER, R. Wide-angle microwave lens for line source applications. IEEE Transactions on Antennas and Propaga-tion, 1963, vol. 11, no. 6, p. 623–632. DOI: 10.1109/TAP.1963.1138114
  13. ANSARUDIN, F., ABD RAHMAN, N. H., YAMADA, Y., et al. Multi beam dielectric lens for 5G base station. Sensors, 2020, vol. 20, no. 20, p. 1–17. DOI: 10.3390/s20205849
  14. GIDDENS, H., HAO, Y. Multi-beam graded dielectric lens anten-na from multi-material 3D printing. IEEE Transaction on Antennas and Propagation, 2020, vol. 68, no. 9, p. 6832–6837. DOI: 10.1109/TAP.2020.2978949
  15. YAMADA, Y., QUZWAIN, K. M. C., IDRUS I. I., et al. Base sta-tion antennas for the 5G mobile system. In Proceeding of 2018 IEEE International RF and Microwave Conference (RFM). Penang (Malaysia), 2018, p. 1–4. DOI: 10.1109/RFM.2018.8846489
  16. LO, Y. T., LEE, S. W. Antenna Handbook, Volume Ⅲ, Antenna Applications. Chapman & Hall, 1993. ISBN: 978-0442015947
  17. ANSARUDIN, F., ABD RAHMAN, T., YAMADA, Y. Design of dielectric lens antenna for 5G mobile base station. In 2018 Interna-tional Symposium on Antennas and Propagation (ISAP 2018). Busan (South Korea), 2018, p. 1–2. ISBN: 978-89-5708-304-8
  18. HUNG, P. V., DINH, N. Q., YAMADA, Y., et al. Parametric anal-ysis of negative and positive refractive index lens antenna by AN-SYS HFSS. International Journal of Antennas and Propagation (Hindawi), 2020, vol. 2020, p. 1–11. DOI: 10.1155/2020/9128921
  19. BALLESTEROS, C., MAESTRE, M., SANTOS, M. C., et al. A 3D printed lens antenna for 5G applications. In Proceedings of the 2019 IEEE International Symposium on Antennas and Propa-gation and USNC-URSI Radio Science Meeting, Atlanta (GA, USA), 2019, p. 1985–1986. DOI: 10.1109/APUSNCURSINRSM.2019.8889092
  20. LI, Y., GE, L., CHEN, M., et al. Multibeam 3-D-printed Luneburg lens fed by magnetoelectric dipole antennas for millimeter-wave MIMO applications. IEEE Transactions on Antennas and Propa-gation. 2019, vol. 67, no. 5, p. 2923–2933. DOI: 10.1109/TAP.2019.2899013
  21. COMISSO, M., PALESE, G., BABICH, F., et al. 3D multibeam and null synthesis by phase-only control for 5G antenna arrays. Electronics, 2019, vol. 8, no. 6, p. 656–669. DOI: 10.3390/electronics8060656
  22. WANG, Z. X., DOU, W. B. Design and analysis of several kinds of dielectric lens antennas. Journal of Electromagnetic Waves and Application, 2006, vol. 20, no. 12, p. 1643–1653. DOI: 10.1163/156939306779292327
  23. KOMLJENOVIC, T. Lens Antenna - Analysis and Synthesis at mm-Waves. Faculty of Electrical Engineering and Computing, University of Zareb, 2008. Available at: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.525.8224&rep=rep1&type=pdf
  24. ZHANG, Z., YANG, S., ZENG, Y., et al. A cylindrical lens anten-na with extremely flat beams. IEEE Access, 2019, vol. 7, p. 156675–156685. DOI: 10.1109/ACCESS.2019.2948961
  25. BALANIS, C. A. Antenna Theory: Analysis and Design. 3rd ed. Hoboken (New Jersey, Canada): John Wiley & Sons, Inc., 2005, p. 14–20. ISBN: 978-0-471-66782-7
  26. STUTZMAN, W. L., THIELE, G. A. Antenna Theory and Design. 2nd ed. United States: John Wiley & Sons, Inc., 1998, p. 130–137. ISBN: 0-471-02590-9
  27. ABD RAHMAN, N. H., YAMADA, Y., NORDIN, M. S. A. Anal-ysis on the effects of the human body on the performance of elec-tro-textile antennas for wearable monitoring and tracking applica-tion. Materials, 2019, vol. 12, no. 10, p. 1–17. DOI: 10.3390/ma12101636
  28. WOO, H., KHAN, A. R., MASUI, H., et al. Discharge observation on antenna surface radiating high power microwave in plasma en-vironment. Transactions of the Japan Society for Aeronautical and Space Sciences, Aerospace Technology Japan, 2014, vol. 12, p. 11–19. DOI: 10.2322/tastj.12.11
  29. TENGAH, Z., ALI, M. T., ABD RAHMAN, N. H., et al. Design of serial feeds for a bifurcated beam of bend-array configuration. In 2016 IEEE Asia-Pacific Conference on Applied Electromagnetics (APACE). Langkawi (Malaysia), 2016, p. 43–46. DOI: 10.1109/APACE.2016.7916471
  30. YASIN, S., KHUDA, I. E., NAZIR, I., et al. Numerical modeling of the order of convergence of surface charge density useful in es-timating bandwidth for microstrip patch antenna. Asian Journal of Engineering, Sciences & Technology, 2015, vol. 5, no. 2, p. 1–3. Available at: https://www.researchgate.net/publication/325010282
  31. SMOLDERS, B., VAATE, J. G., KANT, D., et al. Dual-Beam Wideband Beamformer with Integrated Antenna Array. University of Massachusetts, Amherst, USA, 2000. Available at: https://www.researchgate.net/publication/228358713
  32. https://www.mathworks.com/products/matlab.html
  33. https://rfstation.com/cst/
  34. PIKSA, P., ZVANOVEC, S., CERNY, P. Elliptic and hyperbolic dielectric lens antennas in mm-waves. Radioengineering, 2011, vol. 20, no. 1, p. 270–275. ISSN: 1210-2512
  35. LO, Y. T., LEE, S. W. Antenna Handbook. Volume II. Van Nos-trand Reinhold, New York, 1994. ISBN: 978-0442015930

Keywords: Multi-beam, satellite mobile earth station, cylindrical lens antenna, bifurcated beam, convex bent array

L. Cao, J. Zhang, Y. Liu, Y. Zhu, J. Deng, G. Chen [references] [full-text] [DOI: 10.13164/re.2022.0553] [Download Citations]
Uncooperative Emitter Localization Based on Joint Sensor Selection and Semidefinite Programming

Radio emitter localization based on Received Signal Strength (RSS) is promising in large-scale Internet of Things (IoT) and wireless sensor networks (WSNs) for its low hardware and computation costs. To improve its local-ization accuracy and reduce the system energy consump-tion, we propose an improved RSS localization algorithm based on the joint sensor selection and semidefinite pro-gramming (SDP). An initial position estimate is first ob-tained using RSSs available at a random set of sensors. A refined sensor set is then selected to complete the sec-ond estimation by analyzing the geometric structure of sensing network. Performance of the method is evaluated in terms of localization accuracy and execution time, and compared with existing methods. Extensive simulations demonstrate that the proposed approach achieves a locali-zation accuracy of approximately 1.5 m with 8 to 10 sen-sors. The method outperforms the second-order cone pro-gramming (SOCP) and the least squared relative error (LSRE)-based SDP algorithms in terms of both the loca-tion and the transmit power estimation accuracy.

  1. ZAFARI, F., GKELIAS, A., LEUNG, K. A survey of indoor local-ization systems and technologies. IEEE Communications Surveys & Tutorials, 2019, vol. 21, no. 3, p. 2568–2599. DOI: 10.1109/COMST.2019.2911558
  2. VERA-AMARO, R., RIVERO-ANGELES, M. E., LUVIANO-JUAREZ, A. Design and analysis of wireless sensor networks for animal tracking in large monitoring polar regions using phase-type distributions and single sensor model. IEEE Access, 2019, vol. 7, p. 45911–45929. DOI: 10.1109/ACCESS.2019.2908308
  3. YAN, Y., YANG, G., WANG, H., et al. Semidefinite relaxation for source localization with quantized ToA measurements and transmission uncertainty in sensor networks. IEEE Transactions on Communications, 2021, vol. 69, no. 2, p. 1201–1213. DOI: 10.1109/TCOMM.2020.3037551
  4. KATWE, M., GHARE, P., SHARMA, P. K., et al. NLOS error mitigation in hybrid RSS-TOA-based localization through semi-definite relaxation. IEEE Communications Letters, 2020, vol. 24, no. 12, p. 2761–2765. DOI: 10.1109/LCOMM.2020.3020948
  5. VELASCO, J., PIZARRO, D., MACIAS-GUARASA, J., et al. TDOA matrices: Algebraic properties and their application to ro-bust denoising with missing data. IEEE Transactions on Signal Processing, 2016, vol. 64, no. 20, p. 5242–5254. DOI: 10.1109/TSP.2016.2593690
  6. MINGYI, Y., ANNAN, L. A robust TDOA based solution for source location using mixed Huber loss. Journal of Systems Engi-neering and Electronics, 2021, vol. 32, no. 6, p. 1375–1380. DOI: 10.23919/JSEE.2021.000117
  7. WANG, Y., HO, K. C. Unified near-field and far-field localization for AOA and hybrid AOA-TDOA positionings. IEEE Transactions on Wireless Communications, 2018, vol. 17, no. 2, p. 1242–1254. DOI: 10.1109/TWC.2017.2777457
  8. ZHENG, Y., SHENG, M., LIU, J., et al. Exploiting AoA estima-tion accuracy for indoor localization: A weighted AoA-based ap-proach. IEEE Wireless Communications Letters, 2019. vol. 8, no. 1, p. 65–68. DOI: 10.1109/LWC.2018.2853745
  9. POLAK, L., ROZUM, S., SLANINA, M., et al. Received signal strength fingerprinting-based indoor location estimation employing machine learning. Sensors (Basel), 2021, vol. 21, no. 13, p. 4605–4629. DOI: 10.3390/s21134605
  10. ALTAF KHATTAK, S. B., FAWAD, NASRALLA, M. M., et al. WLAN RSS-based fingerprinting for indoor localization: A ma-chine learning inspired bag-of-features approach. Sensors (Basel), 2022, vol. 22, no. 14, p. 5236–5251. DOI: 10.3390/s22145236
  11. ZOU, Y., LIU, H. RSS-based target localization with unknown model parameters and sensor position errors. IEEE Transactions on Vehicular Technology, 2021, vol. 70, no. 7, p. 6969–6982. DOI: 10.1109/TVT.2021.3089161
  12. WANG, Z. F., ZHANG, H., LU, T., et al. Cooperative RSS-based localization in wireless sensor networks using relative error esti-mation and semidefinite programming. IEEE Transactions on Ve-hicular Technology, 2019, vol. 68, no. 1, p. 483–497. DOI: 10.1109/TVT.2018.2880991
  13. SHI, J., WANG, G., JIN, L. Least squared relative error estimator for RSS based localization with unknown transmit power. IEEE Signal Processing Letters, 2020, vol. 27, p. 1165–1169. DOI: 10.1109/LSP.2020.3005298
  14. DOGANDZIC, A., JIN, J. H. Maximum likelihood estimation of statistical properties of composite gamma-lognormal fading chan-nels. IEEE Transactions on Signal Processing, 2004, vol. 52, no. 10, p. 2940–2945. DOI: 10.1109/TSP.2004.834265
  15. ZISKIND, I., WAX, M. Maximum likelihood localization of mul-tiple sources by alternating projection. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988, vol. 36, no. 10, p. 1553–1560. DOI: 10.1109/29.7543
  16. WANG, G., CHEN, H., LI, Y., et al. On received-signal-strength based localization with unknown transmit power and path loss ex-ponent. IEEE Wireless Communications Letters, 2012, vol. 1, no. 5, p. 536–539. DOI: 10.1109/WCL.2012.072012.120428
  17. VAGHEFI, R. M., GHOLAMI, M. R., BUEHRER, R. M., et al. Cooperative received signal strength-based sensor localization with unknown transmit powers. IEEE Transactions on Signal Pro-cessing, 2013, vol. 61, no. 6, p. 1389–1403. DOI: 10.1109/TSP.2012.2232664
  18. TOMIC, S., BEKO, M., DINIS, R. RSS-based localization in wire-less sensor networks using convex relaxation: Noncooperative and cooperative schemes. IEEE Transactions on Vehicular Technolo-gy, 2015, vol. 64, no. 5, p. 2037–2050. DOI: 10.1109/TVT.2014.2334397
  19. ABABNEH, A. A. Density-based sensor selection for RSS target localization. IEEE Sensors Journal, 2018, vol. 18, no. 20, p. 8532–8540. DOI: 10.1109/JSEN.2018.2866062
  20. ABABNAH, A., NATARAJAN, B. Optimal control-based strategy for sensor deployment. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2011, vol. 41, no. 1, p. 97–104. DOI: 10.1109/TSMCA.2010.2049992
  21. BOPARDIKAR, S. D., ENNASR, O., TAN, X. Randomized sen-sor selection for nonlinear systems with application to target local-ization. IEEE Robotics and Automation Letters, 2019, vol. 4, no. 4, p. 3553–3560. DOI: 10.1109/LRA.2019.2928208
  22. BEL, A., VICARIO, J. L., SECO-GRANADOS, G. Node selection for cooperative localization: Efficient energy vs. accuracy trade-off. In IEEE 5th International Symposium on Wireless Pervasive Computing 2010. Modena (Italy), 2010, p. 307–312. DOI: 10.1109/ISWPC.2010.5483734
  23. DAI, Z., WANG, G., JIN, X., et al. Nearly optimal sensor selection for TDOA-based source localization in wireless sensor networks. IEEE Transactions on Vehicular Technology, 2020, vol. 69, no. 10, p. 12031–12042. DOI: 10.1109/TVT.2020.3011118
  24. YILMAZ, H. B., TUGCU, T. Location estimation-based radio en-vironment map construction in fading channels. Wireless Commu-nications & Mobile Computing, 2015, vol. 15, no. 3, p. 561–570. DOI: 10.1002/wcm.2367
  25. MUKHOPADHYAY, B., SRIRANGARAJAN, S., KAR, S. Signal strength-based cooperative sensor network localization using con-vex relaxation. IEEE Wireless Communications Letters, 2020, vol. 9, no. 12, p. 2207–2211. DOI: 10.1109/LWC.2020.3018679
  26. ABABNEH, A. A. Knapsack-based sensor selection for target lo-calization under energy and error constraints. IEEE Sensors Jour-nal, 2021, vol. 21, no. 23, p. 27208–27217. DOI: 10.1109/JSEN.2021.3123734
  27. BISHOP, A. N., JENSFELT, P. An optimality analysis of sensor-target geometries for signal strength based localization. In 2009 In-ternational Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP). Melbourne (VIC, Austral-ia), 2009, p. 127–132. DOI: 10.1109/ISSNIP.2009.5416784
  28. HAVYARIMANA, V., XIAO, Z., SIBOMANA, A., et al. A fusion framework based on sparse Gaussian–Wigner prediction for vehi-cle localization using GDOP of GPS satellites. IEEE Transactions on Intelligent Transportation Systems, 2020, vol. 21, no. 2, p. 680–689. DOI: 10.1109/TITS.2019.2891585
  29. GRANT, M., BOYD, S. CVX: MATLAB Software for Disciplined Convex Programming. [Online] Cited 2021-02-23. Available at: http://cvxr.com/cvx

Keywords: Received signal strength, sensor selection, semidefinite programming, least squared relative error

D. Chen, A. Xiang, S. Xiong, L. Wang, L. Guo [references] [full-text] [DOI: 10.13164/re.2022.0564] [Download Citations]
Direct Coupled Wave Removal for GPR Data Based on SVD in the Wavelet Domain

This paper presents a new algorithm of the singular value decomposition (SVD) in the wavelet domain for ground penetrating radar (GPR) to remove direct coupled waves. In fact, direct coupled waves commonly disturb the reflecting waves from underground targets. Besides, the amplitude and energy of direct coupled waves are large, which reduces the resolution of the images to the targets and adversely affects the subsequent image interpretation work. The GPR signal is decomposed into several levels by Wavelet to obtain approximation components and detailed components of each level. The information of targets is contained in big eigenvalues of detail components, while the direct coupled waves are contained in small ones. Therefore, the SVD in the wavelet domain can reduce the misjudgment of effective signals and improve the signal to noise ratio (SNR) of GPR signals. The simulated and field GPR data show that the SVD in the wavelet domain denoising method has better results for direct coupled wave removal than the traditional methods, which validates the effectiveness of the proposed denoising method.

  1. YAN, J., BO,W., ZHAO, X., et al. Application of ground penetrating radar in reservoir leakage detection in complex geological areas. IOP Conference Series: Earth and Environmental Science, 2021, vol. 706, no. 1, p. 1–9. DOI: 10.1088/1755-1315/706/1/012009
  2. WANG, S., LIU, G., JING, G., et al. State-of-the-art review of ground penetrating radar (GPR) applications for railway ballast inspection. Sensors, 2022, vol. 22, no. 7, p. 2450–2478. DOI: 10.3390/s22072450
  3. GHOZZI, R., LAHOUAR, S., SOUANI, C. FDTD-based sensitivity analysis of GPR acquisition parameters for accurate detection of buried cylindrical objects. Electronics Letters, 2022, vol. 58, no. 3, p. 118–120. DOI: 10.1049/ell2.12371
  4. VAUGHAN, C. J. Ground-penetrating radar surveys used in archaeological investigations. Geophysics, 1986, vol. 51, no. 3, p. 595–604. DOI: 10.1190/1.1442114
  5. BASILE, V., CARROZZO, M. T., NEGRI, S., et al. A groundpenetrating radar survey for archaeological investigations in an urban area (Lecce, Italy). Journal of Applied Geophysics, 2000, vol. 44, no. 1, p. 15–32. DOI: 10.1016/S0926-9851(99)00070-1
  6. WEI, X., ZHANG, Y. Interference removal for autofocusing of GPR data from RC bridge decks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, vol. 8, no. 3, p. 1145–1151. DOI: 10.1109/JSTARS.2015.2402211
  7. SALAZAR, A., SAFONT, G., VERGARA, L. Application of independent component analysis for evaluation of Ashlar masonry walls. In International Work-Conference on Artificial Neural Networks (IWANN). Torremolinos-Malaga (Spain), 2011, p. 469–476. DOI: 10.1007/978-3-642-21498-1_59
  8. LI, J., LIU, C., ZENG, Z., et al. GPR signal denoising and target extraction with the CEEMD method. IEEE Geoscience and Remote Sensing Letters, 2015, vol. 12, no. 8, p. 1–5. DOI: 10.1109/LGRS.2015.2415736
  9. FENG, D.,WANG, X.,WANG, X. Deep convolutional denoising autoencoders with network structure optimization for the high-fidelity attenuation of random GPR noise. Remote Sensing, 2021, vol. 13, no. 9, p. 1–22. DOI: 10.3390/rs13091761
  10. MUZY, J. F., BACRY, E., ARNEODO, A. Multifractal formalism for fractal signals: The structure-function approach versus the wavelet-transform modulus-maxima method. Physical Review E, 1993, vol. 47, no. 2, p. 875–884. DOI: 10.1103/PhysRevE.47.875
  11. BAILI, J., LAHOUAR, S., HERGLI, M., et al. GPR signal de-noising by discrete wavelet transform. NDT & E International, 2009, vol. 42, no. 8, p. 696–703. DOI: 10.1016/j.ndteint.2009.06.003
  12. HUO, Z., WANG, M. The application of KL transform to remove direct wave in ground penetrating radar records. In International Conference on Image and Graphics (ICIG). Chengdu (China), 2007, p. 133–138. DOI: 10.1109/ICIG.2007.173
  13. SONG, C., LU, Q., LIU, C., et al. Random noise de-noising and direct wave eliminating in ground penetrating radar signal using SVD method. In International Conference on Ground Penetrating Radar (GPR). Hong Kong (China), 2016, p. 1–5. DOI: 10.1109/ICGPR.2016.7572636
  14. JIANG, Z., ZHOU, W., STANLEY, H. E. Multifractal cross wavelet analysis. Fractals, 2017, vol. 25, no. 6, p. 1–10. DOI: 10.1142/S0218348X17500542
  15. BACRY, E., MUZY, J. F., ARNEODO, A. Singularity spectrum of fractal signals from wavelet analysis: Exact results. Journal of Statistical Physics, 1993, vol. 70, no. 3, p. 635–674. DOI: 10.1007/BF01053588
  16. WU, Z., LIU, T., HUA, C. Wavelet threshold de-noising based on higher-order statistics in attenuating random noise. SEG Technical Program Expanded Abstracts, 2006, vol. 25, no. 1, p. 58–61. DOI: 10.1190/1.2370119
  17. SHI, X., YANG, Q. Suppressing the direct wave noise in GPR data via the 2-D physical wavelet frame. In Proceedings of the International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE). Changchun (China), 2011, p. 1161–1164. DOI: 10.1109/TMEE.2011.6199411
  18. JIN, L., CHEN, X. The combination of wavelet transform and nonlinear filtering for time-lapse seismic difference analysis. SEG Technical Program Expanded Abstracts, 2008, vol. 27, no. 1, p. 3214–3218. DOI: 10.1190/1.3064013
  19. DOWNS, C., JAZAYERI, S. Resolution enhancement of deconvolved ground penetrating radar images using singular value decomposition. Journal of Applied Geophysics, 2021, vol. 193, p. 1–18. DOI: 10.1016/j.jappgeo.2021.104401
  20. LIU, C., SONG, C., LU, Q. Random noise de-noising and direct wave eliminating based on SVD method for ground penetrating radar signals. Journal of Applied Geophysics, 2017, vol. 144, no. 3, p. 125–133. DOI: 10.1016/j.jappgeo.2017.07.007
  21. XUE,W., LUO, Y., YANG, Y., et al. Noise suppression for GPR data based on SVD of window-length-optimized Hankel matrix. Sensors, 2019, vol. 19, no. 17, p. 1–25. DOI: 10.3390/s19173807
  22. GAO, Y. T., XU, J. Geological radar signal processing techniques based on wavelet domain KL transform. Science Technology and Engineering, 2018, vol. 18, no. 10, p. 161–166, (in Chinese).
  23. WU, X., YAN, F., ZENG, R., et al. Research on ground-penetrating radar clutter suppression based on wavelet transform and K-SVD. Journal of Hebei University of Science and Technology, 2021, vol. 42, no. 2, p. 111–118, (in Chinese).
  24. FENG, D., DAI, Q., HE, J., et al. Finite-difference time-domain implementation of ground-penetrating radar GPR orthorectified simulation. Advances in Geophysics, 2006, vol. 2, p. 630–636, (in Chinese).

Keywords: Singular value decomposition, wavelet domain, ground penetrating radar, direct coupled waves, SNR

M. Khalaj-Amirhosseini [references] [full-text] [DOI: 10.13164/re.2022.0572] [Download Citations]
Design of Nonuniformly Spaced Antenna Arrays Using Orthogonal Coefficients Equating Method

Orthogonal Coefficients Equating (OCE) method as an analytic method is proposed to synthesize nonuniformly spaced antenna arrays to have array factors nearly equal to that of a previously designed uniformly spaced antenna arrays. In this method, the orthogonal coefficients of array factors of nonuniformly space array are equated to those of uniformly space array. To this end, three orthogonal functions including Chebyshev polynomials, Legendre polynomials and exponential functions are discussed. Some examples are brought to verify the performance of the OCE method for all three orthogonal functions.

  1. SCHJAER-JACOBSEN, H., MADSEN, K. Synthesis of nonuni-formly spaced arrays using a general nonlinear minimax optimiza-tion method. IEEE Transactions on Antennas and Propagation, 1976, vol. 24, p. 501–506. DOI: 10.1109/TAP.1976.1141369
  2. BAE, J.-H., KIM, K.-T., LEE, J.-H., et al. Design of steerable non-uniform linear array geometry for side-lobe reduction. Microwave and Optical Technology Letters, 2003, vol. 36, no. 5, p. 363–367. DOI: 10.1002/mop.10765
  3. KURUP, D. G., HIMDI, M., RYDBERG, A. Synthesis of uniform amplitude unequally spaced arrays using the differential evolution algorithm. IEEE Transactions on Antennas and Propagation, 2003, vol. 51, no. 9, p. 2210–2217. DOI: 10.1109/TAP.2003.816361
  4. ORAIZI, H., FALLAHPOUR, M. Nonuniformly spaced linear ar-ray design for the specified beamwidth/sidelobe level or specified irectivity/sidelobe level with coupling considerations. Progress In Electromagnetic Research M, 2008, vol. 4, p. 185–209. DOI: 10.2528/PIERM08072302
  5. ZAMAN, M. A., ABDUL-MATIN, MD. Nonuniformly spaced linear antenna array design using firefly algorithm. International Journal of Microwave Science and Technology, 2012, p. 1–8. DOI: 10.1155/2012/256759
  6. MAHMOUD, K. R. Synthesis of unequally-spaced linear array us-ing modified central force optimization algorithm. IET Micro-waves, Antennas & Propagation, 2016, vol. 10, no. 10, p. 1011–1021. DOI: 10.1049/iet-map.2015.0801
  7. HARRINGTON, R. F. Sidelobe reduction by nonuniform element spacing. IRE Transactions on Antennas and Propagation, 1961, vol. 9, no. 2, p. 187–192. DOI: 10.1109/TAP.1961.1144961
  8. ISHIMARU, A. Theory of unequally spaced arrays. IRE Transac-tions on Antennas and Propagation, 1962, vol. 10, no. 6, p. 691–702. DOI: 10.1109/TAP.1962.1137952
  9. REDLICH, R. W. Iterative least squares synthesis of nonuniformly spaced linear array. IEEE Transactions on Antennas and Propaga-tion, 1973, vol. 21, no. 1, p. 106–108. DOI: 10.1109/TAP.1973.1140405
  10. HODJAT, F., HOVANESSIAN, S. A. Nonuniformly spaced linear and planar array antennas for sidelobe reduction. IEEE Transac-tions on Antennas and Propagation, 1978, vol. 26, no. 2, p. 198–204. DOI: 10.1109/TAP.1978.1141812
  11. YU, C.-C. Sidelobe reduction of asymmetric linear array by spac-ing perturbation. Electronics Letters, 1997, vol. 33, no. 9, p. 730–732. DOI: 10.1049/el:19970499
  12. REN, X. F., AZEVEDO, J. A., CASIMIRO, A. M. Synthesis of non-uniformly spaced arrays using the Fourier transform and win-dow techniques. IET Microwaves, Antennas and Propagation, 2009, vol. 3, no. 8, p. 1245–1253. DOI: 10.1049/iet-map.2008.0217
  13. LIN, C., QING, A., FENG, Q. Synthesis of unequally spaced an-tenna arrays by using differential evolution. IEEE Transactions on Antennas and Propagation, 2010, vol. 58, no. 8, p. 2553–2558. DOI: 10.1109/TAP.2010.2048864
  14. YANG, K., ZHAO, Z. Q., LIU, Q. H. Fast pencil beam pattern synthesis of large unequally spaced antenna arrays. IEEE Transac-tions on Antennas and Propagation, 2013, vol. 61, no. 2, p. 627–634. DOI: 10.1109/TAP.2012.2220319
  15. ISHIMARU, A. Unequally spaced arrays based on the Poisson sum formula. IEEE Transactions on Antennas and Propagation, 2014, vol. 62, p. 1549–1554. DOI: 10.1109/TAP.2013.2283255
  16. YOU, B. Q., CAI, L. R., ZHOU, J. H., et al. Hybrid approach for the synthesis of unequally spaced array antennas with sidelobes reduction. IEEE Antennas and Wireless Propagation Letters, 2015, vol. 14, p. 1569–1572. DOI: 10.1109/LAWP.2015.2412778
  17. KHALAJ-AMIRHOSSEINI, M., VECCHI, G., PIRINOLI, P. Near-Chebyshev pattern for nonuniformly spaced arrays using ze-ros matching method. IEEE Transactions on Antennas and Propa-gation, 2017, vol. 65, no. 10, p. 5155–5161. DOI: 10.1109/TAP.2017.2737041
  18. KHALAJ-AMIRHOSSEINI, M. Design of nonuniformly spaced arrays using yeros matching method. International Journal of RF and Microwave Computer-Aided Engineering, 2018, vol. 28, no. 9, DOI: 10.1002/mmce.21490
  19. KHALAJ-AMIRHOSSEINI, M. Design of nonuniformly spaced antenna arrays using Fourier's coefficients equating method. IEEE Transactions on Antennas and Propagation, 2018, vol. 66, no. 10, p. 5326–5332. DOI: 10.1109/TAP.2018.2861981
  20. BOOZARI, M., KHALAJ-AMIRHOSSEINI, M. Development of an allocation method to synthesis of unequally spaced arrays with minimum number of elements and mutual coupling considerations. International Journal of RF and Microwave Computer-Aided En-gineering, 2022, vol. 32, no. 4. DOI: 10.1002/mmce.23064
  21. KHALAJ-AMIRHOSSEINI, M. To reduce the number of elements of linear antenna arrays using Fourier's coefficients equating meth-od. Scientia Iranica, 2022, p. 1–12. DOI: 10.24200/SCI.2021.57801.5423
  22. KHALAJ-AMIRHOSSEINI, M. Synthesis of linear and planar ar-rays with sidelobes of individually arbitrary levels. International Journal of RF and Microwave Computer-Aided Engineering, 2018, vol. 29, no. 3. DOI: 10.1002/mmce.21637
  23. KHALAJ-AMIRHOSSEINI, M. Synthesis of low sidelobe level antenna arrays through only main lobe assumption. Scientific Re-ports, 2021, vol. 11, p. 1–8. DOI: 10.1038/s41598-021-01934-8

Keywords: Nonuniformly spaced arrays, uniformly spaced arrays, orthogonal coefficients equating, Chebyshev polynomials, Legendre polynomials, exponential functions.