非均匀环境下STAP方法研究
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摘要
空时自适应信号处理(STAP)的理论研究已渐趋成熟,研究的热点已转向STAP的工程实现。现阶段的研究表明,雷达所面临的实际环境中存在着大量的非均匀因素,常规STAP的性能在非均匀环境中会受到严重影响。
本文首先研究了几种常见的非均匀现象:杂波功率非均匀、干扰目标和孤立干扰,分别分析了这几种非均匀现象对STAP性能的影响,并对其进行了仿真研究。
针对杂波功率非均匀,本文对典型的功率选择法(PST)进行了介绍和研究,并针对功率选择法在强备选样本数不足时,杂波功率估计过低的问题提出了改进措施,仿真及实测数据的处理结果验证了改进措施的有效性。针对干扰目标,介绍了几种常见的非均匀检测器;对抑制孤立干扰的频域替代法进行了研究,针对其存在干扰目标信号残余的问题,对其进行了改进,仿真及实测数据的处理结果都验证了改进方法的有效性。
在研究各种非均匀现象及其抑制方法的基础上,本文对可以抑制各种非均匀现象的综合型STAP方法进行了深入研究。分析了直接数据域方法的原理及其优缺点。对先验知识STAP进行了探索性研究,提出了基于先验SAR图像的非均匀STAP方法,该方法通过对SAR图像上的相似区域进行区域平均抑制杂波功率非均匀和干扰目标的影响,打破了常规STAP以距离单元回波做统计平均的做法,仿真结果显示了方法的有效性。本文还提出一种结合距离-多普勒域沿迹干涉(RD-ATI)技术的非均匀STAP方法,该方法将RD-ATI技术与改进的PST法和频域替代法进行结合,RD-ATI技术作为干扰运动目标检测器,用来发现干扰目标和孤立干扰,为后续的动目标检测提供先验信息,提高动目标检测的针对性,改进的PST法用来抑制杂波功率非均匀的影响,改进的频域替代法用来抑制孤立干扰。实测数据的处理结果表明该方法能有效抑制各种非均匀现象,大大减少了STAP搜索动目标的运算负担,是一种适合实际应用的非均匀STAP方法。
Space time adaptive processing (STAP) is a leading technology candidate for improving detection performance of next generation airborne radar. The performance of STAP is greatly affected in non-homogeneous clutter environments. New STAP algorithms for this problem are studied widely.
Three common non-homogeneous factors are researched firstly in this paper, they are: power non-homogeneity、interference target and discrete interference. Then, the influence to STAP caused by nonhomogeneous clutter environment is analyzed and simulated.
For power non-homogeneity, the typical method called power selected training (PST) is researched. It is shown that when there are not enough strong secondary data for selected, the PST method can’t work well, so the improvement of the PST method is proposed, and the result of simulation and real data shows its effectiveness. For interference target, Non-homogeneous Detector (NHD) is introduced. For discrete interference, substitution method is used and improved. Besides, the range-Doppler domain ATI (RD-ATI) technique is used to detect interference moving target and provide important information to STAP.
Based on the research of methods for non-homogeneous clutter environments, at the end of the paper, integrative STAP approach is researched. The direct-data domain (DDD) method is introduced. To research the knowledge-based STAP, a non-homogeneous STAP method based on priori SAR image is proposed and simulated. Furthermore, a Non-homogeneous STAP Approach Combined with RD-ATI Technique is proposed, in which RD-ATI technique is used as a NHD to provide prior knowledge of moving targets, PST method is employed to restrain clutter power non-homogeneous, and Frequency Domain Substitution (FDS) method used to eliminate the discrete interference. The approach improves conventional STAP performance significantly and greatly reduces computational burden, which has a great practical value. The result of real data from a three-channel SAR/GMTI system shows efficiency of the approach.
本文首先研究了几种常见的非均匀现象:杂波功率非均匀、干扰目标和孤立干扰,分别分析了这几种非均匀现象对STAP性能的影响,并对其进行了仿真研究。
针对杂波功率非均匀,本文对典型的功率选择法(PST)进行了介绍和研究,并针对功率选择法在强备选样本数不足时,杂波功率估计过低的问题提出了改进措施,仿真及实测数据的处理结果验证了改进措施的有效性。针对干扰目标,介绍了几种常见的非均匀检测器;对抑制孤立干扰的频域替代法进行了研究,针对其存在干扰目标信号残余的问题,对其进行了改进,仿真及实测数据的处理结果都验证了改进方法的有效性。
在研究各种非均匀现象及其抑制方法的基础上,本文对可以抑制各种非均匀现象的综合型STAP方法进行了深入研究。分析了直接数据域方法的原理及其优缺点。对先验知识STAP进行了探索性研究,提出了基于先验SAR图像的非均匀STAP方法,该方法通过对SAR图像上的相似区域进行区域平均抑制杂波功率非均匀和干扰目标的影响,打破了常规STAP以距离单元回波做统计平均的做法,仿真结果显示了方法的有效性。本文还提出一种结合距离-多普勒域沿迹干涉(RD-ATI)技术的非均匀STAP方法,该方法将RD-ATI技术与改进的PST法和频域替代法进行结合,RD-ATI技术作为干扰运动目标检测器,用来发现干扰目标和孤立干扰,为后续的动目标检测提供先验信息,提高动目标检测的针对性,改进的PST法用来抑制杂波功率非均匀的影响,改进的频域替代法用来抑制孤立干扰。实测数据的处理结果表明该方法能有效抑制各种非均匀现象,大大减少了STAP搜索动目标的运算负担,是一种适合实际应用的非均匀STAP方法。
Space time adaptive processing (STAP) is a leading technology candidate for improving detection performance of next generation airborne radar. The performance of STAP is greatly affected in non-homogeneous clutter environments. New STAP algorithms for this problem are studied widely.
Three common non-homogeneous factors are researched firstly in this paper, they are: power non-homogeneity、interference target and discrete interference. Then, the influence to STAP caused by nonhomogeneous clutter environment is analyzed and simulated.
For power non-homogeneity, the typical method called power selected training (PST) is researched. It is shown that when there are not enough strong secondary data for selected, the PST method can’t work well, so the improvement of the PST method is proposed, and the result of simulation and real data shows its effectiveness. For interference target, Non-homogeneous Detector (NHD) is introduced. For discrete interference, substitution method is used and improved. Besides, the range-Doppler domain ATI (RD-ATI) technique is used to detect interference moving target and provide important information to STAP.
Based on the research of methods for non-homogeneous clutter environments, at the end of the paper, integrative STAP approach is researched. The direct-data domain (DDD) method is introduced. To research the knowledge-based STAP, a non-homogeneous STAP method based on priori SAR image is proposed and simulated. Furthermore, a Non-homogeneous STAP Approach Combined with RD-ATI Technique is proposed, in which RD-ATI technique is used as a NHD to provide prior knowledge of moving targets, PST method is employed to restrain clutter power non-homogeneous, and Frequency Domain Substitution (FDS) method used to eliminate the discrete interference. The approach improves conventional STAP performance significantly and greatly reduces computational burden, which has a great practical value. The result of real data from a three-channel SAR/GMTI system shows efficiency of the approach.
引文
[1]王永良,彭应宁.空时自适应信号处理.北京:清华大学出版社, 2000.
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[6] R.Klemm. Adaptive airborne MTI: An auxiliary channel approach. IEE proc. Vol.134, 1987, No3, 269-276
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[8] E. C. Barile, R. L. Fante, J. A. Torres. Some limitations on the effectiveness of airborne radar. IEEE Trans. On AES. 1992, 28(4):1015-1023
[9] P. Richardson. Relationships between DPCA and adaptive space-time processing techniques for clutter suppression. Int. Cof. On Radar, Paris. 1994:295-300
[10] Dipietro R. Extended factored space-time processing for airborne radar systems. Proceedings of the 26th Asilomar Conference on Signals, Systems and Computing. Pacific Grove, CA, 1992. 425-430
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[14]王永良,保铮,彭应宁.空时二维自适应处理的统一理论模型与局域处理方法.电子学报, 1996,24(9): 64-69
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[2] M.O.Little and W.P.Berry. Real-time multichannel airborne radar measurements. IEEE Proc. Int. Conf. Radar Syracuse, New York, 1997
[3] Ward J. Space-time adaptive processing for airborne radar. Technical Report 1015, MIT Lincoln Laboratory, 1994.
[4] L.E.Brennan, J.D.Mallett, and L.S.Reed. Theory of adaptive radar. IEEE Tran. AES-9(2), 1973:237-251.
[5] Brennan L E, Mallete J D, Reed I S. Adaptive arrays in airborne MTI radar. IEEE Trans on AP, 1976, 24(5): 566-571
[6] R.Klemm. Adaptive airborne MTI: An auxiliary channel approach. IEE proc. Vol.134, 1987, No3, 269-276
[7] Wang H. An adaptive spatial-temporal processing for airborne surveillance radar systems. IEEE Trans. On AES. 1994, 30(3):660-670
[8] E. C. Barile, R. L. Fante, J. A. Torres. Some limitations on the effectiveness of airborne radar. IEEE Trans. On AES. 1992, 28(4):1015-1023
[9] P. Richardson. Relationships between DPCA and adaptive space-time processing techniques for clutter suppression. Int. Cof. On Radar, Paris. 1994:295-300
[10] Dipietro R. Extended factored space-time processing for airborne radar systems. Proceedings of the 26th Asilomar Conference on Signals, Systems and Computing. Pacific Grove, CA, 1992. 425-430
[11] Farina A, Saverione A. The MVDR vectorial lattice applied to space-time processing for AEW radar with large instanoueous bandwidth. IEEE Proc. Radar Sonar and Navigation, 1996, 143(1): 41-46
[12] Farina A, Graziano R, Lee F. Adaptive space-time processing with algorithm: experimental results using recorded live data. Proc. Of 1995 IEEE Int. Conf, Alexandria, VA, 1995, 595-602
[13] Liu Q G, Peng Y L. Analysis of array errors and a short-time processor in airborne phased array radars. IEEE Trans on AES, 1996, 32(2): 587-597
[14]王永良,保铮,彭应宁.空时二维自适应处理的统一理论模型与局域处理方法.电子学报, 1996,24(9): 64-69
[15]王永良.新一代机载雷达的空时二维自适应信号处理. [博士学位论文];西安:西安电子科技大学; 1994
[16] L E Brennan, D J Piwinski, M F Standaher. Comparison of space-time adaptive processing approaches using experimental airborne radar data. The Record of 1993 IEEE National Radar Conf. Massachusetts, USA, 1993:176-181
[17] R Brown, M Wicks, Y Zhang, etc. A space-time adaptive processing approach for improved performance and afford ability. 1996 IEEE National Radar Conf., MI, USA, 1996:321-326
[18] H Wang, Y Zhang, Q Zhang. An improved and Affordable Space-Time Adaptive Processing Approach. 1996 CIE Int. Conf on Radar, Beijing, 1996:72-77
[19] A Heimovich. The eigencanceler: Adaptive radar by eigenanalysis methods. IEEE Trans. On AES, 1996, 32(2):532-542
[20] A. Heimovich, M. Berin. Eigenanalysis based space-time adaptive radar performance analysis. IEEE Trans. On AES, 1997, 33(4):1170-1179
[21] J S Goldstein, I S Reed. Subspace selection for partially adaptive sensor array processing. IEEE Trans, on AES, 1997, 33(2):988-996
[22] Guerci, J.R. Knowledge-aided sensor signal processing and expert reasoning. In Proceedings of 2002 Knowledge-Aided Sensor signal Processing and Expert Reasoning (KASSPER) Workshop, Washington, Dc, 2002
[23] Melvin W L. Eigenbased modeling of nonhomogeneous airborne radar environments. Proc of the IEEE National Radar Conf, Dallas, TX, USA, 1998, 171-176
[24] Melvin W L. Space-time adaptive radar performance in heterogeneous clutter. IEEE Trans on AES, 2000, 36(2): 621:633
[25] Melvin W L, Guerci J R, Callahan M J. Design of adaptive detection algorithms for surveillance radar. Proc of the IEEE int. Radar conf, Alexandria, VA, USA, 2000, 608-613
[26]王永良,李天泉.机载雷达空时自适应信号处理技术回顾与展望.中国电子科学研究院学报, 2008年06月,第三期:271-275
[27] D. J. Rabideau, A.O. Steinhardt. Power Select Training for False Alarm Mitigation in Airborne Radar. Adaptive sensor array processing workshop, MIT Lincoln Laboratory, 1996
[28] Rabideau D J, Steinhardt A O. Improving the performance of adaptive arrays in nonstationary environments through data-adaptive training. Proc of the 30th Asilomar Conf on Signals, Systems and Computers, Pacific Grove, CA, USA, 1996: 75-79
[29] Rabideau D J, Steinhardt A O. Improved adaptive clutter cancellation through data-adaptive training. IEEE Trans on AES, 1999, 35(3):879-891
[30] Guerci J R. Space-time adaptive processing for radar. Boston, London: Artech House, 2003.
[31] Guerci J R, Bergin J S. Principal components covariance matrix tapers and the subspace leakage problem. IEEE Trans on AES, 2000, 38(1): 152-162
[32] Guerci J R. Theory and application of covariance matrix tapers for robustadaptive beamforming. IEEE Trans on SP, 1999, 47(4): 977-985
[33] Guerci J R, Bergin J S. Principal components, covariance matrix tapers and the interference modulation problem. Proc of the Adaptive Sensor Array Processing Workshop, MIT Lincoln Laboratory, Lexington, MA, USA, 1999
[34] Chang H H. Improving space-time adaptive processing radar performance in non-homogeneous clutter. Doctor Dissertation, Syracuse University, 1997
[35] Melvin W L, Wicks M C, Chen P. Non-homogeneity detection method and apparatus for improved adaptive signal processing. USA Patent Pending, Application Number 694, 577, filed 9 August 1996.
[36] Braham Himed, Yassir Salama, James H. Improved detection of close proximity targets using two-step NHD. IEEE international radar Conf, 2000: 781-786
[37] Wang Y L, et al. Robust space-time adaptive processing for airborne radar in non-homogeneous clutter environments. IEEE Trans on AES, 2003, 39(1):70-81
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