超宽带合成孔径地表穿透雷达干扰抑制技术研究
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摘要
近年来,地表穿透合成孔径雷达(GPSAR)得到了广泛使用和飞速发展。作为一种近场探测SAR,其不仅容易受到各种射频干扰(RFI)的影响,还不可避免的要受到耦合杂波的干扰。国防科技大学超宽带雷达技术研究室在“十五”期间研制了轨道地表穿透合成孔径雷达(Rail-GPSAR),各种射频干扰和耦合干扰严重影响了Rail-GPSAR的探测性能。能否有效抑制这些干扰,是提高GPSAR成像质量和系统性能的关键。
针对这个实际情况,本文就Rail-GPSAR的干扰抑制问题展开了深入的研究。在对Rail-GPSAR干扰的深入分析和对常用的干扰抑制方法研究的基础上,重点讨论了三类适用于Rail-GPSAR的干扰抑制方法:自适应滤波法、特征子空间滤波法和二维频域法。本文详细介绍了这三类算法的原理及特点,详细讨论了滤波过程中各种参数的选取问题,并对干扰抑制结果进行分析评估,对比各种方法的优点及局限性。
自适应滤波是一种重要的统计信号处理手段,Rail-GPSAR杂波成份复杂,非常适合采用自适应滤波的办法。无论是利用自适应抵消滤波法去除耦合干扰,还是利用自适应预测误差法抑制RFI,都可以取得良好的效果。
特征子空间滤波法则是通过特征向量分解的方式,分别建立信号子空间与干扰子空间。通过将回波数据向信号子空间投影的方式滤除杂波。其特点是能够极大的抑制掉强干扰的频率成份。二维频域法的思想是利用有效目标回波与干扰杂波在二维频域内的支撑域不同的特
点,比较准确的进行谱估计。本文采取一套行之有效的信号处理流程,有效的抑制了干扰杂波。
通过对Rail-GPSAR实测数据的处理结果进行评估分析,发现上述三类算法非常适合Rail-GPSAR的干扰抑制,均能产生令人满意的效果。
Recent years, Ground Penetrating Synthetic Aperture Radar(GPSAR) has been well developed and been applied to many fields. As a short-range detection radar, it is influenced not only by the Radio Frequency Interference (RFI), but also by the coupling clutter. To improve the SAR images quality, we have to suppress the clutter effectively.
The paper is based on the subject of clutter suppression of the Rail-GPSAR system which was build by National University of Defense Technology. Here it introduces many of traditional approaches to suppress the clutter. The paper pays much attention to these approaches: Adaptive Filtering, Eigen-subspace Decomposition Filtering and 2D Fourier Transform Filtering.
Adaptive filtering can not only cancel the coupling clutter but also predict the RFI. The approach proved to be effective to restrain the complex clutter of Rail-GPSAR.
Eigen-subspace decomposition filtering suppresses the clutter by projecting the received signal to the‘signal-subspace’.‘Signal-subspace’is obtained by eigenvector-subspace decomposition.
2D Fourier transform filtering is a novel way to suppress the interference. It projects the received signals to the 2D Fourier Domain. The target echoes and the interference clutter are distributed to different areas. Then we can estimate the spectrum of RFI and restrain the clutter by a wiener filter.
By analyzing the result, we found these three approaches can suppress the clutter effectively. The performance of each filter is satisfied.
针对这个实际情况,本文就Rail-GPSAR的干扰抑制问题展开了深入的研究。在对Rail-GPSAR干扰的深入分析和对常用的干扰抑制方法研究的基础上,重点讨论了三类适用于Rail-GPSAR的干扰抑制方法:自适应滤波法、特征子空间滤波法和二维频域法。本文详细介绍了这三类算法的原理及特点,详细讨论了滤波过程中各种参数的选取问题,并对干扰抑制结果进行分析评估,对比各种方法的优点及局限性。
自适应滤波是一种重要的统计信号处理手段,Rail-GPSAR杂波成份复杂,非常适合采用自适应滤波的办法。无论是利用自适应抵消滤波法去除耦合干扰,还是利用自适应预测误差法抑制RFI,都可以取得良好的效果。
特征子空间滤波法则是通过特征向量分解的方式,分别建立信号子空间与干扰子空间。通过将回波数据向信号子空间投影的方式滤除杂波。其特点是能够极大的抑制掉强干扰的频率成份。二维频域法的思想是利用有效目标回波与干扰杂波在二维频域内的支撑域不同的特
点,比较准确的进行谱估计。本文采取一套行之有效的信号处理流程,有效的抑制了干扰杂波。
通过对Rail-GPSAR实测数据的处理结果进行评估分析,发现上述三类算法非常适合Rail-GPSAR的干扰抑制,均能产生令人满意的效果。
Recent years, Ground Penetrating Synthetic Aperture Radar(GPSAR) has been well developed and been applied to many fields. As a short-range detection radar, it is influenced not only by the Radio Frequency Interference (RFI), but also by the coupling clutter. To improve the SAR images quality, we have to suppress the clutter effectively.
The paper is based on the subject of clutter suppression of the Rail-GPSAR system which was build by National University of Defense Technology. Here it introduces many of traditional approaches to suppress the clutter. The paper pays much attention to these approaches: Adaptive Filtering, Eigen-subspace Decomposition Filtering and 2D Fourier Transform Filtering.
Adaptive filtering can not only cancel the coupling clutter but also predict the RFI. The approach proved to be effective to restrain the complex clutter of Rail-GPSAR.
Eigen-subspace decomposition filtering suppresses the clutter by projecting the received signal to the‘signal-subspace’.‘Signal-subspace’is obtained by eigenvector-subspace decomposition.
2D Fourier transform filtering is a novel way to suppress the interference. It projects the received signals to the 2D Fourier Domain. The target echoes and the interference clutter are distributed to different areas. Then we can estimate the spectrum of RFI and restrain the clutter by a wiener filter.
By analyzing the result, we found these three approaches can suppress the clutter effectively. The performance of each filter is satisfied.
引文
[1] Hu Jin-feng,Zhou Zheng-ou,“A novel method for clutter reduction in the FLGPR measurements”,IEEE International Conference on Communications, Circuits and Systems, 2004。
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[3] F. Shubitidze, K. O’Neill, I. Shamatava, K. Sun and K.D. Paulsen,“Analysis of GPR scattering by multiple subsurface metallic objects to improve UXO discrimination”,IEEE International Geoscience and Remote Sensing Symposium, 2003.
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[2] R. Wu, A.Clement, J.Li, E. G. Larsson, M. Bradley, J.Habersat and G. Maksymonko,“Adaptive ground bounce removal”,Electronics Letters Vol.37, No.20, Sep.2001
[3] F. Shubitidze, K. O’Neill, I. Shamatava, K. Sun and K.D. Paulsen,“Analysis of GPR scattering by multiple subsurface metallic objects to improve UXO discrimination”,IEEE International Geoscience and Remote Sensing Symposium, 2003.
[4] Brian KarZsen, Jan Larsen, Helge B.D. Srensen and Kaj B. Jakobsen,“Comparison of PCA and ICA based clutter reduction in GPR systems for anti-personal landmine detection”,11th IEEE Signal Processing, 2001
[5] Keigo Iizuka, Alois P. Freundorfer,“Detection of nonmetallic buried objects by a step frequency radar”,IEEE Vol.71, No.2, Feb.1983
[6] A. S. Shmalenyuk, Yu. G, Tishchenko, N.A. Armand, V. M. Polyakov,“Detection of shallowly buried dielectric objects with microwave radiometers”,IEEE Geoscience and Remote Sensing Symposium, 1994.
[7] H. Brunzell,“Detection of shallowly buried objects using impulse radar”,IEEE transaction on GEOSCIENCE and REMOTE SENSING, Vol.37, No.2, Mar.1999
[8] Madrid, J.J.M.; Corredera, J.R.C.; Vela, G.DeM.; Rodriguez, F.J.J.,“Detection of shallowly buried objects with subsurface radars”,IEEE Geoscience and Remote Sensing Symposium, 1993
[9] Abrahamsson, R.; Larsson, E.G.; Li, J.; Habersat, J.; Maksymonko, G.; Bradley, M,“Elimination of leakage and ground-bounce effects in ground-penetrating radar data”,the 11th IEEE Signal Processing Workshop on Statistical Signal Processing, 2001.
[10] H. Brunzell,“Pre-processing of ground penetrating impulse radar data for improved detection capability”,IEEE,1998
[11] Margaret Cheneya, David Isaacsona, Victoria I. Lytleb, Stephen F. Ackley,“Recovery of surface parameters from stepped-frequency radar returns”,Mathematics and Computers in Simulation 50 (1999) p527~539
[12] G. F. Stickley, I.D. Longstaff, M.J. Radcliffe,“Synthetic aperture radar for the detection of shallow buried objects”,IEE Conference Publicaton No.431, 1996
[13] Zaikov E.A, Mikhnev V.A, Maksimovitch Ye.S,“The eigenvector-based identification ofshallow buried targets in ground penetrating radar”,the 14th Int.Crimean Conference “Microwave & Telecommunication Technology”,2004
[14] Peter Cooper, Giles Verwey, Christopher Purry,“Ultra wideband endfire synthetic aperture radar for landmine detection”,IEEE InternationalGeoscience and Remote Sensing Symposium, Vol.2 p752~754,2003
[15] Michael A. Morgen, Fellow,“Ultra-wideband impulse scattering measurements”,IEEE Transactions on Antennas and Propagation, Vol.42, No.6, Jun.1994
[16] Dragana Carevic,“Wavelet-based method for detection of shallowly buried objects from GPR data”,IEEE Information, Decision and Control, 1999
[17] Wan Xianrong, Wen Biyang, Ke Hengyu,“Adaptive radio frequency interference mitigation for HF surface wave radar”,IEEE the 4th International Conference on Microwave and Millmeter Wave Technoloty Proceedings, 2004
[18] Amir Leshem, Alle-Jan van der Veen,“Adaptive suppression of RFI and its effect on radio-astronomical image formation”,IEEE Image Processing, Vol.3, p616_619 ,2001
[19] X. Luo, L.M.H. Ulander, J. Askne, G. Smith, P.O. Frolind,“RFI suppression in ultra-wideband SAR systems using LMS filters in frequency domain”,Electronics Letters, Vol.37, No.4, Feb.2001
[20] Timothy Miller, Lee Potter, John McCorkle,“RFI suppression for ultra wideband radar”,IEEE Transactions on Aerospace and Electronic Systems, Vol.33, No.4, Oct.1997
[21] Charles TC Le, Scott Hensley, Elaine Chapin,“Removal of RFI in wideband radars”,IEEE Geoscience and Remote Sensing Symposium Proceedings, 1998
[22] Egil S.Eide,“Radar imaging of small objects closely below the earth surface”,Ph.D thesis,Department of Telecommunications Norwegian University,2000
[23] Jin Tian, Zhou Zhimin, Song Qian, Chang Wenge,“UWB SAR RFI Suppression based on region of support in 2-D wavenumber domain”,Journal of Electronics (China),to be appear
[24] 周智敏,黄晓涛,常文革,梁甸农,“UWB-SAR 抑制 RFI 算法性能评估与测试”,国防科技大学学报 Vol.24 No2 2002
[25] 常文革,梁甸农,周智敏,“轨道超宽带 SAR 实验技术研究”,电子学报 Vol.29, No.9, Sep.2001
[26] 徐玉清,张国进,高攀,“冲击脉冲雷达探雷”,电波科学学报 Vol.16, No.4, Dec.2001
[27] 黄伟,李大心,唐庆兵,“二维滤波在探地雷达图像处理中的应用研究”,工程勘察2002 年第 4 期
[28] 张立国,周正欧,“浅地层探地雷达回波倒相的自适应处理”,电子科技大学学报 Vol.33, No.5, Oct.2004
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