Increasing the Angular Resolution and Range of Measuring Systems Using Ultra-Wideband Signals

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The problem of obtaining three-dimensional radio images of objects with increased resolution based on the use of ultra-wide-band pulse signals and new methods of their digital processing is considered. The inverse problem of reconstructing the image of a signal source with a resolution exceeding the Rayleigh criterion has been solved numerically. Mathematically, the problem is reduced to solving the Fredholm integral equation of the first kind by numerical methods based on the representation of the solution in the form of decomposition into systems of orthogonal functions. The method of selecting the systems of functions used, which increases the stability of solutions, is substantiated. Variational problems of optimizing the shape and duration of ultra-wide-band pulses have been solved, ensuring the maximum possible signal-to-noise ratio during location studies of objects with fully or partially known signal reflection characteristics. The proposed procedures make it possible to increase the range of measuring systems, and also make it possible to increase the stability of solutions to inverse problems. It is shown that the use of the developed methods for achieving super-resolution to process ultra-wideband signals dramatically improves the quality of 3D images of objects in the radio range.

作者简介

B. Lagovskiy

Russian Technological University (MIREA)

Email: robertlag@yandex.ru
Moscow, Russia

E. Rubinovich

Trapeznikov Institute of Control Sciences, Russian Academy of Sciences

编辑信件的主要联系方式.
Email: rubinvch@gmail.com
Moscow, Russia

参考

  1. Odendaal W., Barnard E., Pistorius C.W.I. Two Dimensional Superresolution Radar Imaging Using the MUSIC Algorithm // IEEE Trans. 1994. Vol. AP-42. No. 10. P. 1386-1391. https://doi.org/10.1109/8.320744
  2. Waweru N.P., Konditi D.B.O., Langat P.K. Performance Analysis of MUSIC Root- MUSIC and ESPRIT DOA Estimation Algorithm // Int. J. Electrical Computer Energetic Electronic and Communication Engineering. 2014. Vol. 08. No. 01. P. 209-216.
  3. Yuebo Zha, Yulin Huang, Jianyu Yang. An Iterative Shrinkage Deconvolution for Angular Super-Resolution Imaging in Forward-Looking Scanning Radar // Progress 88 In Electromagnetics Research B., 2016. V. 65. P. 35-48. https://doi.org/10.2528/PIERB15100501
  4. Almeida M.S., Figueiredo M.A. Deconvolving images with unknown boundaries using the alternating direction method of multipliers // IEEE Trans. Image Process. 2013. Vol. 22. No. 8. P. 3074-3086.
  5. Dudik M., Phillips S.J., Schapire R.E. Maximum entropy density estimation with generalized regularization and an application to species distribution modeling // J. Machine Learning Research. 2007. Vol. 8. P. 1217-1260.
  6. Stoica P., Sharman K.C. Maximum likelihood methods for direction-of-arrival estimation // IEEE Trans. on Acoustics, Speech and Signal Processing. 1990. No. 38(7). P. 1132-1143.
  7. Geiss A., Hardin J.C. Radar super resolution using a deep convolutional neural network // Journal of Atmospheric and Oceanic Technology. 2020. Vol. 37. No. 12. P. 2197-2207.
  8. Ramani S., Liu Z., Rosen J., Nielsen J., Fessler J.A. Regularization parameter for nonlinear iterative image restoration and MRI selection reconstruction using GCV and SURE- based methods // IEEE Trans. on Image Processing. 2012. V. 21. No. 8. P. 3659-3672.
  9. Morse P., Feshbach H. Methods of Theoretical Physics. McGraw-Hill Science/Engineering/ Math. 1953.
  10. Lagovsky B.A., Rubinovich E.Y. Algebraic methods for achieving super-resolution by digital antenna arrays // Mathematics. 2023. V. 11. No. 4. P. 1-9. https://doi.org/10.3390/math11041056
  11. Lagovsky B.A., Samokhin A.B., Shestopalov Y.V. Angular Superresolution Based on A Priori Information. Radio Science. 2021. V. 56. No. 1. 2021. P. 1-11. https://doi.org/10.1029/2020RS007100
  12. Лаговский Б.А. Угловое сверхразрешение в двумерных задачах радиолокации // Радиотехника и электроника. 2021. Т. 66. № 9. C. 853-858. https://doi.org/10.31857/S0033849421090102
  13. Лаговский Б.А., Рубинович Е.Я. Алгоритмы цифровой обработки данных измерений, обеспечивающие угловое сверхразрешение // Мехатроника, автоматизация, управление. 2021. Т. 22. № 7. С. 349-356. https://doi.org/10.17587/mau.22.349-356
  14. Калинин В.И., Чапурский В.В., Черепенин В.А. Сверхразрешение в системах радиолокации и радиоголографии на основе MIMO антенных решеток с рециркуляцией сигналов // Радиотехника и электроника. 2021. T. 66. № 6. С. 614-624. https://doi.org/10.31857/s0033849421060139
  15. Щукин А.А., Павлов А.Е. Параметризация пользовательских функций в цифровой обработке сигналов для получения углового сверхразрешения // Russian Technological Journal. 2022. № 10(4). С. 38-43. https://doi.org/10.32362/2500-316X-2022-10-4-38-43
  16. Lagovsky B.A., Samokhin A.B. Superresolution in signal processing using a priori information // IEEE Conf. Publications International Conference Electromagnetics in Advanced Applications (ICEAA). Italy. 2017. P. 779-783. https://doi.org/10.1109/ICEAA.2017. 8065365
  17. Dong J., Li Y., Guo Q., Liang X. Through-wall moving target tracking algorithm in multipath using UWB radar // IEEE Geosci. Remote Sens. Lett. 2021. P. 1-5. https://doi.org/10.1109/ lgrs.2021.3050501
  18. Khan H.A., Edwards D.J., Malik W.Q. Ultra wideband MIMO radar // Proc. IEEE Intl. Radar Conf. Arlington, VA, USA, 2005. 9 May 2005.
  19. Zhou Yuan, Law Choi Look, Xia Jingjing. Ultra low-power UWB-RFID system for precise location-aware applications // 2012 IEEE Wireless Communications and Networking Conference. Workshops (WCNCW). 2012. P. 154-158.
  20. Taylor J.D. Ultra-wideband Radar Technology. CRC Press Boca Raton, London, New Work, Washington. 2000.
  21. Holami G., Mehrpourbernety H., Zakeri B. UWB Phased Array Antennas for High Resolution Radars // Proc. of the 2013 International Symp. on Electromagnetic Theory, 2013. P. 532-535.
  22. Lagovsky B.A., Samokhin A.B., Shestopalov Y.V. Pulse Characteristics of Antenna Array Radiating UWB Signals // Proceedings of the 10th European Conference on Antennas and Propagation (EuCAP 2016). Davos, Switzerland. 2016. P. 2479-2482. https://doi.org/10.1109/EuCAP.2016.7481624
  23. Lagovsky B.A., Samokhin A.B., Shestopalov Y.V. Increasing accuracy of angular measurements using UWB signals. 2017 11th European Conference on Antennas and Propagation (EUCAP) // IEEE Conf. Publications. Paris. 2017. P. 1083-1086. https://doi.org/10.23919/EuCAP.2017.7928204
  24. Anis R., Tielert M. Design of UWB pulse radio transceiver using statistical correlation technique in frequency domain // Advances in Radio Science. 2007. V. 5. P. 297-304. https://doi.org/10.5194/ars-5-297-2007
  25. Niemela V., Haapola J., Hamalainen M., Iinatti J. An ultra wideband survey: Global regulations and impulse radio research based on standards // IEEE Communications Surveys and Tutorials. 2016. V. 19. No. 2. P. 874-890. https://doi.org/10.1109/COMST.2016.2634593
  26. Barrett T. History of UWB Radar and Communications: Pioneers and Innovators // Progress in Electromagnetics Symposium (PIERS) 2000. Microwave Journ, January 2001.
  27. Дмитриев А.С., Ефремова Е.В., Кузьмин Л.В. Генерация последовательности хаотических импульсов при воздействии периодического сигнала на динамическую систему // Письма в ЖТФ. 2005. Т. 31. № 22. С. 29. https://doi.org/10.1134/S1064226906050093
  28. Yang D., Zhu Z., Liang B. Vital sign signal extraction method based on permutation entropy and EEMD algorithm for ultra-wideband radar // IEEE Access. 2019. V. 7. https://doi.org/10.1109/ACCESS.2019.2958600
  29. Вендик О.Г. Антенны с немеханическим движением луча. М.: Советское Радио, 1965.
  30. Ватсон Г.Н. Теория бесселевых функций / пер. со 2-го англ. изд. /М.: ИЛ, 1947.

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