稀疏恢复空时自适应处理技术研究综述

doi:10.3969/j.issn.0372-2112.2019.03.033

电子学报 ›› 2019, Vol. 47 ›› Issue (3): 748-756.DOI: 10.3969/j.issn.0372-2112.2019.03.033

稀疏恢复空时自适应处理技术研究综述

段克清^1,3, 袁华东¹, 许红², 谢文冲¹, 王永良¹

1. 空军预警学院, 湖北武汉 430019;
2. 海军工程大学电子工程学院, 湖北武汉 430033;
3. 中山大学电子与通信工程学院, 广东广州 510006

收稿日期:2018-05-08 修回日期:2018-07-03 出版日期:2019-03-25 发布日期:2019-03-25
作者简介:段克清 男,1981年生于河北石家庄,2010年获国防科技大学信息与通信工程专业工学博士学位,现为空军预警学院雷达兵器运用工程军队重点实验室讲师.主要研究方向为空时自适应处理、阵列信号处理和稀疏恢复等.E-mail:duankeqing@aliyun.com;袁华东 男,1985年生于湖北宜昌,现为空军预警学院信息与通信工程专业博士研究生.主要研究方向为空时自适应处理和稀疏恢复等.E-mail:yhdtiandadida@126.com;许红男,1991年生于四川成都,现为海军工程大学通信与信息系统专业博士研究生.主要研究方向为目标跟踪、信息融合和认知雷达等.E-mail:xuhongzhxu@163.com;谢文冲 男,1979年生于山西运城,2006年获国防科技大学信息与通信工程专业工学博士学位,现为空军预警学院雷达兵器运用工程军队重点实验室副教授.主要研究方向为机载雷达信号处理、空时自适应处理和阵列信号处理等.E-mail:xwch1978@aliyun.com;王永良 男,1965年生于浙江嘉兴,1994年获西安电子科技大学信号与信息处理专业工学博士学位,现为空军预警学院雷达兵器运用工程军队重点实验室教授、博士生导师.主要研究方向为雷达信号处理、空时自适应处理和阵列信号处理等.E-mail:ylwangkjld@163.com
基金资助:
国家自然科学基金（No.61871397，No.61501506）

An Overview on Sparse Recovery Space-Time Adaptive Processing Technique

DUAN Ke-qing^1,3, YUAN Hua-dong¹, XU Hong², XIE Wen-chong¹, WANG Yong-liang¹

1. Air Force Early Warning Academy, Wuhan, Hubei 430019, China;
2. Electronic Engineering Department, Navy University of Engineering, Wuhan, Hubei 430033, China;
3. School of Electronic and Communication Engineering, Sun Yat-sen University, Guangzhou, Guangdong 510006, China

Received:2018-05-08 Revised:2018-07-03 Online:2019-03-25 Published:2019-03-25

摘要/Abstract

摘要： 相较于传统空时自适应处理（STAP）技术，稀疏恢复（SR）STAP技术在小样本条件下杂波抑制性能显著提升，因此适用于现实非均匀杂波环境.本文首先阐述了SR STAP基本原理，分析了机载雷达杂波空时稀疏特性；然后总结了SR STAP发展历史与现状，并在此基础上针对其相关科学问题进行了探讨，包括：空时谱估计还是杂波抑制、单观测样本还是多观测样本、白化还是置零、重构算法参数依赖还是不依赖、非平稳杂波下是否适用及干扰条件下是否可行；最后给出了当前SR STAP技术走向实用化过程中所面临的关键问题，即网格失配和空域误差影响，并分别讨论了无网格压缩感知和字典自校正的解决途径.

关键词: 空时自适应处理, 机载雷达, 杂波抑制, 稀疏恢复, 非均匀杂波环境, 无网格压缩感知

Abstract: Compared with conventional space-time adaptive processing (STAP) technique,sparse recovery (SR) STAP technique can significantly improve the clutter suppression performance in the case of limited training samples,and hence is well suited for practical non-homogeneous clutter environment.Firstly,the paper describes the principle of SR STAP,and analyzes the clutter sparsity in space-time plane for airborne radar.Then the development and current status of SR STAP is summarized.On this basis,some key issues about the technique are discussed which include space-time spectrum estimation or clutter suppression,single or multiple measurements,clutter whitening or nulling,parameter dependence or independence for recovery algorithms,whether applicable for non-stationary clutter environment,and whether feasible under the condition of jamming.Finally,key problems confronted in the real-world applications for sparse recovery STAP technique are presented,which include off-grid effect,influence of spatial errors,and huge computational cost.Meanwhile,effective ways including gridless compressive sensing and self-calibration of overcomplete dictionary are respectively discussed to solve above problems.

Key words: space-time adaptive processing, airborne radar, clutter suppression, sparse recovery, non-homogeneous clutter environment, gridless compressive sensing

中图分类号:

TN957

段克清, 袁华东, 许红, 谢文冲, 王永良. 稀疏恢复空时自适应处理技术研究综述[J]. 电子学报, 2019, 47(3): 748-756.

DUAN Ke-qing, YUAN Hua-dong, XU Hong, XIE Wen-chong, WANG Yong-liang. An Overview on Sparse Recovery Space-Time Adaptive Processing Technique[J]. Acta Electronica Sinica, 2019, 47(3): 748-756.

参考文献

[1] Brennan L E,Mallett J D,Reed I S.Theory of adaptive radar[J].IEEE Transactions on Aerospace and Electronic Systems,1973,9(2):237-251.
[2] Reed I S,Mallett J D,Brennan L E.Rapid convergence rate in adaptive arrays[J].IEEE Transactions on Aerospace and Electronic Systems,1974,10(6):853-863.
[3] Melvin W L,Shownman,G A.An approach to knowledge-aided covariance estimation[J].IEEE Transactions on Aerospace and Electronic Systems,2006,42(3):1021-1042.
[4] Melvin W L,Guerci J R.Adaptive detection in dense target environments[A].IEEE National Radar Conference[C].Atlanta,GA:IEEE Press,2001.187-192.
[5] Himed B,Salama Y,Michel J H.Improved detection of close proximity targets using two-step NHD[A].IEEE National Radar Conference[C].Alexandria,NA:IEEE Press,2000.781-786.
[6] Wang Y,Chen J,Bao Z,et al.Robust space-time adaptive processing for airborne radar in nonhomogeneous clutter environments[J].IEEE Transactions on Aerospace and Electronic Systems,2003,39(1):70-81.
[7] Guerci J,Baranoski E.Knowledge-aided adaptive radar at DARPA:An overview[J].IEEE Signal Processing Magazine,2006,23(1):41-50.
[8] Klemm R.Adaptive airborne MTI:an auxiliary channel approach[J].IET Radar Sonar &Navigation,1987,134(3):269-276.
[9] Wang H,Cai L.On adaptive spatial-temporal processing for airborne surveillance radar systems[J].IEEE Transactions on Aerospace and Electronic Systems,1994,30(3):660-670.
[10] Brown R,Wicks M.A space-time adaptive processing approach for improved performance and affordability[A].IEEE National Radar Conference[C].Ann,Arbor,MI:IEEE Press,1996.321-326.
[11] Haimovich A,Bar N Y.An eigenanalysis interference canceler[J].IEEE Transactions on Signal Processing,1991,39(1):76-84.
[12] Goldstein J S,Reed I S.Reduced rank adaptive filtering[J].IEEE Transactions on Signal Processing,1997,45(2):492-496.
[13] Zatman M,Marshall D.Forwards-backwards averaging for adaptive beamforming and STAP[A].Proceedings of IEEE International Conference on Acoustics,Speech,and Signal Processing[C].Atlanta,GA:IEEE Press,1996.2630-2633.
[14] Pillai S U,Lim Y L,Guerci J R.Generalized forward/backward subaperture smoothing techniques for sample starved STAP[J].IEEE Transactions on Signal Processing,2000,48(12):3569-3574.
[15] Sarkar T K,Wang H,Park S,et al.A deterministic least squares approach to space time adaptive processing (STAP)[J].IEEE Transactions on Signal Processing,2001,49(1):91-103.
[16] Parker P,Swindlehurst A.Space-time autoregressive filtering for matched subspace STAP[J].IEEE Transactions on Aerospace and Electronic Systems,2003,39(2):510-520.
[17] Roman J R,Rangaswamy M,Davis D W,et al.Parametric adaptive matched filter for airborne radar applications[J].IEEE Transactions on Aerospace and Electronic Systems,2000,36(2):677-692.
[18] Melvin,W,Wicks M,Antonik P,et al.Knowledge-based space-time adaptive processing for airborne early warning radar[J].IEEE AES Systems Magazine,1998,13(4):37-42
[19] Bergin J S,Teixeira C M,Techau P M,et al.Improved clutter mitigation performance using knowledge-aided space-time adaptive processing[J].IEEE Transactions on Aerospace and Electronic Systems,2006,42(3):997-1009.
[20] Wu Y,Tang J,Peng Y.On the essence of knowledge-aided clutter covariance estimate and its convergence[J].IEEE Transactions on Aerospace and Electronic Systems,2011,47(1):569-585.
[21] 范西昆,曲毅.知识辅助机载雷达杂波抑制方法研究进展[J].电子学报,2012,40(6):1199-1206.Fan Xi-kun,Qu Yi.An overview of knowledge-aided clutter mitigation methods for airborne radar[J].Acta Electronica Sinica,2012,40(6):1199-1206.(in Chinese)
[22] Donoho D L,Elad M,Temlyakov V N.Stable recovery of sparse overcomplete representations in the presence of noise[J].IEEE Transactions on Information Theory,2016,52(1):6-18.
[23] Sun K,Zhang H,Li G,et al.A novel STAP algorithm in heterogeneous[A].IEEE International Conference on Geoscience & Remote Sensing Symposium[C].Cape Town:IEEE,2009.336-339.
[24] Sun K,Meng H,Wang Y,et al.Direct data domain STAP using sparse representation of clutter spectrum[J].Signal Processing,2011,91(9):2222-2236.
[25] Yang Z,Li X,Wang H,et al.On clutter sparsity analysis in space-time adaptive processing airborne radar[J].IEEE Geoscience and Remote Sensing Letters,2013,10(5):1214-1218.
[26] Maria S,Fuchs J J.Application of the global matched filter to STAP data an efficient algorithmic approach[A].Proceedings of IEEE International Conference on Acoustics,Speech,and Signal Processing[C].Toulouse,France:IEEE Press,2006.14-19.
[27] Selesnich I W,Pillai S U,Li K Y,et al.Angle-Doppler processing using sparse regularization[A].Proceedings of IEEE International Conference on Acoustics,Speech,and Signal Processing[C].Dallas TX:IEEE Press,2010.2750-2753.
[28] Parker H T,Potter L C.A Bayesian perspective on sparse regularization for STAP post-processing[A].IEEE Radar Coference[C].Washington,DC:IEEE Press,2010.1471-1475.
[29] Li J,Zhu X,Stoica P,et al.High resolution angle-Doppler imaging for MTI radar[J].IEEE Transactions on Aerospace and Electronic Systems,2010,46(3):1544-1556.
[30] Sen S.OFDM radar-space-time adaptive processing by exploiting spatio-temporal sparsity[J].IEEE Transactions on Signal Processing,2013,61(1):118-130.
[31] 孙珂,张颢,李刚,等.基于杂波谱稀疏恢复的空时自适应处理[J].电子学报,2011,39(6):1389-1393.Sun Ke,Zhang Hao,Li Gang,et al.STAP via sparse recovery of clutter spectrum[J].Acta Electronica Sinica,2011,39(6):1389-1393.(in Chinese)
[32] Ma Z,Liu Y,Meng H,et al.Jointly Sparse recovery of multiple snapshots in STAP[A].IEEE Radar Conference[C].Ottawa,ON:IEEE Press,2013.1-4.
[33] Ma Z,Liu Y,Meng H,et al.Sparse recovery-based space-time adaptive processing with array errorself-calibration[J].Electronics Letters,2014,50(13):152-154.
[34] Yang Z,de Lamare R C,Li X.L1-regularized STAP algorithms with a generalized sidelobe canceler architecture for airborne radar[J].IEEE Transactions on Signal Processing,2012,60(2):674-686.
[35] Yang Z,Li X,Wang H,et al.Knowledge-aided STAP with sparse-recovery by exploiting spatio-temporal sparsity[J].IET Signal Processing,2016,10(2):150-161.
[36] Yang Z,Li X,Wang H,et al.Adaptive clutter suppression based on iterative adaptive approach for airborne radar[J].Signal Processing,2013,93(12):3567-3577.
[37] Yang Z,de Lamare R C,Liu W.Sparsity-based STAP using alternating direction method with gain/phase errors[J].IEEE Transactions on Aerospace and Electronic Systems,2017,53(6):756-768.
[38] 阳召成,黎湘,王宏强.基于空时功率谱稀疏性的空时自适应处理技术研究进展[J].电子学报,2014,42(6),1194-1204.Yang Zhao-cheng,Li Xiang,Wang Hong-qiang.An overview of space-time adaptive processing technology based on sparsity of space-time power spectrum[J].Acta Electronica Sinica,2014,42(6):1194-1204.(in Chinese)
[39] Yang X,Sun Y,Zeng T,et al.Fast STAP method based on PAST with sparse constraint for airborne phased array radar[J].IEEE Transactions on Signal Processing,2016,64(17):4550-4561.
[40] Sun Y,Yang X,Long T,et al.Robust sparse Bayesian learning STAP method for discrete interference suppression in nonhomogeneous clutter[A].IEEE Radar Conference[C].Seattle,WA:IEEE Press,2017.1003-1008.
[41] Guo Y,Liao G,Feng W.Sparse representation based algorithm for airborne radar in beam-space post-Doppler reduced-dimension space-time adaptive processing[J].IEEE Access,2017,5:5896-5903.
[42] Feng W,Zhang Y,He X,et,al.Cascaded clutter and jamming suppression method using sparse representation[J].Electronics Letters,2015,51(19):1524-1526.
[43] Feng W,Guo Y,Zhang Y,et,al.Airborne radar space time adaptive processing based on atomic norm minimization[J].Signal Processing,2018,148:31-40.
[44] Wang Z,Wang Y,Duan K,et al.Subspace-augmented clutter suppression technique for STAP radar[J].IEEE Geoscience and Remote Sensing Letters,2016,13(3):462-466.
[45] Wang Z,Wang Y,Gao F,et al.Clutter nulling STAP algorithm based on sparse representation for airborne radar[J].IET Radar Sonar & Navigation,2017,11(1):177-184.
[46] Duan K,Xie W,Chen H,et al.Sparsity-based STAP algorithm with multiple measurement vectors via sparse Bayesian learning strategy for airborne radar[J].IET Signal Processing,2017,11(5):544-553.
[47] Wang Z,Xie W,Duan K,et al.Clutter suppression algorithm based on fast converging sparse Bayesian learning for airborne radar[J].Signal Processing,2017,130:159-168.
[48] Duan K,Liu W,Duan G,Wang Y.Off-grid effects mitigation exploiting knowledge of the clutter ridge for sparse recovery STAP[J].IET Radar Sonar & Navigation,2018,12(5):557-564.
[49] Sun H,Lu Y,Lesturgie M.Experimental investigation of iterative adaptive approach for ground moving target indication[A].IEEE Radar Conference[C].Chengdu,China:IEEE Press,2011.715-718.
[50] Cotter S F,Rao B D,Engan K,et al.Sparse solutions to linear inverse problems with multiple measurement vectors[J].IEEE Transactions on Signal Processing,2005,53(7):2477-2488.
[51] Tropp J A,Gilbert A C,Strauss M J.Algorithms for simultaneous sparse approximation,Part I:Greedy pursuit[J].Signal Processing,2006,86:572-588.
[52] Tropp J A.Algorithms for simultaneous sparse approximation,Part II:Covex relaxation[J].Signal Processing,2006,86:589-602.
[53] Chen J,Huo X.Theoretical results on sparse representations of multiple-measurement vectors[J].IEEE Transactions on Signal Processing,2006,54(12):4634-4643.
[54] Wipf D,Rao B.An empirical Bayesian strategy for solving the simultaneous sparse approximation problem[J].IEEE Transactions on Signal Processing,2007,55(7):3704-3716.
[55] Tsao T,Himed B,Michels J.Effects of interference rank estimation on the detection performance of rank reduced STAP algorithms[A].IEEE Radar Conference[C].Dallas,TX:IEEE Press,1998.147-152.
[56] Goodman A,Stiles J.On clutter rank observed by arbitrary arrays[J].IEEE Transactions on Signal Processing,2007,55(1):178-186.
[57] Tipping M E.Sparse Bayesian learning and the relevance vector machine[J].Journal of Machine Learning Research,2001,1:211-244.
[58] Wipf D P,Rao B D.Sparse Bayesian learning for basis selection[J].IEEE Transactions on Signal Processing,2004,52(8):2153-2164.
[59] Wang Y,Peng Y,Bao Z.Space-time adaptive processing for airborne radar with various array orientations[J].IET Radar Sonar & Navigation,1997,144(6):330-340.
[60] Duan K,Xie W,Wang Y.Nonstationary clutter suppression for airborne conformal array radar[J].Science China Information Sciences,2011,54(10):2170-2177.
[61] Meng X,Wang T,Wu J,et al.Short-range clutter suppression for airborne radar by utilizing prefiltering in elevation[J].IEEE Geoscience and Remote Sensing Letters,2009,6(2):268-272.
[62] 段克清,谢文冲,陈辉,等.基于俯仰维信息的机载雷达非均匀杂波抑制方法[J].电子学报,2011,39(3):585-590.Duan Ke-qing,Xie Wen-chong,Chen Hui,et al.Elevation-based methods for nonhomogeneous clutter suppression in airborne radar[J].Acta Electronica Sinica,2011,39(3):585-590.(in Chinese)
[63] Wu J,Wang T,Meng X,et al.Clutter suppression for airborne nonsidelooking radar using ERCB-STAP algorithm[J].IET Radar,Sonar & Navigation,2012,6(9):497-506.
[64] Shen M,Meng X,Zhang L.Efficient adaptive approach for airborne radar short-range clutter suppression[J].IET Radar,Sonar & Navigation,2012,6(9):900-904.
[65] Yang Z,Xie L H.On grid sparse methods for line spectral estimation from complete and incomplete data. IEEE Transactions on Signal Processing,2015,63(12):3139-3153.
[66] Candés E J,Fernandez-Granda C.Towards a mathematical theory of super-resolution[J].Communications on Pure &Applied Mathematics,2014,67(6):906-956.
[67] Tang G G,Bhaskar B N,Shah P,Recht B.Compressed sensing on the grid[J].IEEE Transactions on Information Theory,2013,59(11):7465-7490.
[68] Bhaskar B N,Tang G G,Recht B.Atomic norm denoising with applications to line spectral estimation[J].IEEE Transactions on Signal Processing,2013,61(23):5987-5999.
[69] Xenaki A,Gerstoft P.Grid-free compressive beamforming[J].Acoustical Society of America,2015,137(4):1923-1935.
[70] Li Y,Chi Y.Off-the-grid line spectrum denoising and estimation with multiple measurement vectors[J].IEEE Transactions on Signal Processing,2016,64(5):1257-1269.
[71] Fannjiang A,Tseng H C.Compressive radar with off-grid targets:a perturbation approach[J].Inverse Problems 2012,29(5):1-23.
[72] Prünte L.Off-grid compressed sensing for GMTI using SAR images[A].Proceedings of 2013 International Conference on Signal Processing with Adaptive Sparse Structured Representations[C].Lausanne,Switzerland:CADMOS,2013.248-251.
[73] Sun K,Liu Y M,Meng H D,et al.Adaptive sparse representation for source localization with gain/phase errors[J].Sensors,2011,11(5):4780-4793.
[74] Zhao L F,Bi G A,Wang L,et al.An improved auto-calibration algorithm based on sparse Bayesian learning framework[J].IEEE Signal Processing Letters,2013,20(9):889-892.
[75] Liu A F,Baker C J,Gao C C.Robust space-time adaptive processing for nonhomogeneous clutter in the presence of model errors[J].IEEE Transactions on Aerospace and Electronic Systems,2016,52(1):155-168.

稀疏恢复空时自适应处理技术研究综述

An Overview on Sparse Recovery Space-Time Adaptive Processing Technique

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	李淑慧, 邓志红, 冯肖雪, 潘峰. 强杂波背景下基于变分贝叶斯推理的机载雷达目标跟踪算法[J]. 电子学报, 2022, 50(5): 1089-1097.
[2]	韩超垒, 杨志伟, 张庆君, 廖桂生, 何鹏远. 距离-多普勒-频带域3D-AWP-MRF分类辅助的SAR-GMTI杂波抑制方法[J]. 电子学报, 2021, 49(12): 2339-2348.
[3]	赵岐诚. 论电磁兼容性设计理念[J]. 电子学报, 2020, 48(2): 238-242.
[4]	位寅生, 周希波, 刘佳俊. 稳健的基于参数化协方差矩阵估计的空时自适应处理方法[J]. 电子学报, 2019, 47(9): 1943-1950.
[5]	周必雷, 王永良, 段克清, 戴凌燕, 李荣锋, 陈风波. 一种主瓣干扰环境下的雷达目标参数“同维”稀疏估计方法[J]. 电子学报, 2019, 47(6): 1201-1208.
[6]	郑晨, 席晓莉, 宋忠国, 王梦蕾. 基于子空间技术中奇异向量分析的穿墙雷达杂波抑制方法[J]. 电子学报, 2019, 47(4): 848-854.
[7]	郑晨, 席晓莉, 宋忠国. 基于延迟锁定环跟踪对消技术的穿墙雷达杂波抑制[J]. 电子学报, 2018, 46(9): 2181-2187.
[8]	谌诗娃, 周青松, 张剑云, 毛云祥. 对空时自适应处理雷达的投散射式伪杂波干扰方法信号特性分析[J]. 电子学报, 2018, 46(2): 401-409.
[9]	谌诗娃, 张剑云, 周青松, 朱家兵. 对空时二维自适应处理雷达的投散射宽时限扫频式干扰技术研究[J]. 电子学报, 2017, 45(6): 1349-1355.
[10]	周延, 姜博, 聂卫科, 张万绪. 空域分解的机载MIMO雷达空时处理方法[J]. 电子学报, 2017, 45(10): 2348-2354.
[11]	高志奇, 陶海红, 赵继超. 基于联合稀疏功率谱恢复的机载雷达稳健STAP算法研究[J]. 电子学报, 2016, 44(11): 2796-2801.
[12]	晏艺翡, 廖桂生, 杨志伟. 一种利用目标微动特性提高SAR-MMTI检测性能的方法[J]. 电子学报, 2015, 43(6): 1050-1057.
[13]	王泽涛, 段克清, 谢文冲, 王永良. 基于SA-MUSIC理论的联合稀疏恢复STAP算法[J]. 电子学报, 2015, 43(5): 846-853.
[14]	陈功, 谢文冲, 王永良. 基于空时联合约束的机载雷达STAP单脉冲角度估计方法[J]. 电子学报, 2015, 43(3): 489-495.
[15]	方明, 戴奉周, 刘宏伟, 王小谟. 基于多帧观测联合感知的空时自适应处理[J]. 电子学报, 2015, 43(12): 2368-2373.