基于修正自适应匹配滤波器的机动目标检测方法

李海; 刘新龙; 周盟; 刘维建

doi:10.12000/JR15105

基于修正自适应匹配滤波器的机动目标检测方法

DOI: 10.12000/JR15105

1.
(中国民航大学天津市智能信号与图像处理重点实验室天津 300300)
2.
(空军预警学院黄陂士官学校武汉 430019)

基金项目:

国家自然科学基金(61471365, 61231017, 61571442), 中央高校基本科研业务费项目(3122015B002), 中国民航大学蓝天青年学者培养经费

详细信息

作者简介:
李海(1976-),男,天津人,现为中国民航大学副教授,研究方向为空时自适应信号处理、机载气象雷达信号处理等。E-mail:haili@cauc.edu.cn刘新龙(1984-),男,甘肃张掖人,现为中国民航大学硕士研究生,研究方向为空时自适应信号处理、动目标检测。E-mail:xinl_liu@qq.com周盟(1988-),男,四川广汉人,现为中国民航大学硕士研究生,研究方向为空时自适应信号处理、动目标检测、机载气象雷达信号处理。E-mail:bard_belief@hotmail.com刘维建(1982-),男,山东莱芜人,现为空军预警学院黄陂士官学校助教,主要研究方向为雷达信号处理、多通道信号检测、阵列信号处理和统计信号处理。E-mail:liuvjian@163.com

通讯作者:
李海haili@cauc.edu.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2015-09-18
- 修回日期: 2015-10-25
- 网络出版日期: 2015-10-28

Detection of Maneuvering Target Based on Modified AMF

1.
(Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China)
2.
(Huangpi NCO School of Air Force Early Warning Academy, Wuhan 430019, China)

Funds:

The National Natural Science Foundation of China (61471365, 61231017, 61571442), National Universitys Basic Research Foundation of China (3122015B002), Foundation for Sky Young Scholars of Civil Aviation University of China

摘要

摘要: 机动目标回波的多普勒走动和训练样本不足导致常规自适应匹配滤波器(Adaptive Matched Filter, AMF)检测机动目标时运算量大且性能不佳。针对此问题, 该文提出一种基于修正AMF的机动目标检测方法。该方法首先通过对角加载减少样本空间自由度, 从而降低对训练样本数的需求；然后以3次相位变换(Cubic Phase Transform, CPT)分离估计加速度, 并以估计值补偿多普勒走动, 降低联合匹配搜索维度, 进而减少运算量；最后进行积累检测。仿真结果表明, 该方法运算量低, 可实现小样本下机动目标的有效检测, 具有恒虚警(Constant False Alarm Rate, CFAR)特性。
- 机动目标检测 /
- 自适应匹配滤波器 /
- 3次相位变换 /
- 对角加载 /
- 多普勒走动
Abstract: Owing to the Doppler frequency migration of the return signal of maneuvering targets and finite training samples, it is difficult to detect maneuvering targets by conventional Adaptive Matched Filter (AMF) detectors. To solve this problem, a new method is proposed. First, to minimize sample size impairments, the diagonal loading technique was adopted to decrease the degrees of freedom of the sample space. Second, the Doppler frequency migration was compensated by the estimated acceleration which was estimated by the cubic phase transform, so as to reduce the dimension of matched searching and degrade the heavy calculation load. Finally, accumulation detection was conducted. The simulation results suggest that the proposed method can efficiently detect maneuvering target in finite sample situations with simple computation and constant false alarm rate detection.
- Maneuvering target detection /
- Adaptive matched filter /
- Cubic phase transform /
- Diagonal loading /
- Doppler frequency migration

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参考文献(31)

[1]	Klemm R. Principles of Space-time Adaptive Processing[M]. London: The Institution of Electrical Engineers, 2002: 87-100.
[2]	Melvin W L. A STAP overview[J]. IEEE Aerospace and Electronic Systems Magazine, 2004, 19(1): 19-35.
[3]	Ward J. Space-time adaptive processing for airborne radar[R]. Technical Report 1015, MIT Lincoln Laboratory, 1994: 1-79.
[4]	王永良, 刘维建, 谢文冲, 等. 机载雷达空时自适应检测方法研究进展[J]. 雷达学报, 2014, 3(2): 201-207.-Wang Y L, Liu W J, Xie W C, et al.. Research progress of space-time adaptive detection for airborne radar[J]. Journal of Radars, 2014, 3(2): 201-207.
[5]	Kelly E J. An adaptive detection algorithm[J]. IEEE Transactions on Aerospace and Electronic Systems, 1986, 22(1): 115-127.
[6]	Chen W S and Reed I S. A new CFAR detection test for radar[J]. Digital Signal Processing, 1991, 1(4): 198-214.
[7]	Robey F C, Fuhrmann D R, Kelly E J, et al.. A CFAR adaptive matched filter detector[J]. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(1): 208-216.
[8]	Kraut S and Scharf L L. The CFAR adaptive subspace detector is a scale-invariant GLRT[J]. IEEE Transactions on Signal Processing, 1999, 47(9): 2538-2541.
[9]	Li X L, Cui G L, Yi W, et al.. Coherent integration for maneuvering target detection based on Radon-Lv's distribution[J]. IEEE Signal Processing Letters, 2015, 22(9): 1467-1471.
[10]	Ru J F, Jilkov V P, Li X R, et al.. Detection of target maneuver onset[J]. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(2): 536-554.
[11]	Zhu S Q, Liao G S, Yang D, et al.. A new method for radar high-speed maneuvering weak target detection and imaging[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(7): 1175-1179.
[12]	Chen X L, Huang Y, Liu N B, et al.. Radon-fractional ambiguity function-based detection method of low-observable maneuvering target[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(2): 815-833.
[13]	Winters D W. Target motion and high range resolution profile generation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(3): 2140-2153.
[14]	Reed I S, Mallett J D, and Brennan L E. Rapid convergence rate in adaptive arrays[J]. IEEE Transactions on Aerospace and Electronic Systems, 1974, 10(6): 853-863.
[15]	Gvensen G M, Candan C, Orguner U, et al.. On generalized eigenvector space for target detection in reduced dimensions[C]. Proceedings of the IEEE International Radar Conference, Arlington VA, USA, 2015: 1316-1321.
[16]	Melvin W L. Space-time adaptive radar performance in heterogeneous clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2000, 36(2): 621-633.
[17]	同亚龙, 王彤, 文才, 等. 一种稳健的机载非正侧视阵雷达杂波抑制方法[J]. 电子与信息学报, 2015, 37(5): 1044-1050.-Tong Y L, Wang T, Wen C, et al.. A robust clutter suppression method for airborne non-sidelooking radar[J]. Journal of Electronics Information Technology, 2015, 37(5): 1044-1050.
[18]	Carlson B D. Covariance matrix estimation errors and diagonal loading in adaptive arrays[J]. IEEE Transactions on Aerospace and Electronic Systems, 1988, 24(4): 397-401.
[19]	Guerci J R and Bergin J S. Principal components, covariance matrix tapers, and the subspace leakage problem[J]. IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(1): 152-162.
[20]	Wu Y, Tang J, and Peng Y N. 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]	O'shea P. A fast algorithm for estimating the parameters of a quadratic FM signal[J]. IEEE Transactions on Signal Processing, 2004, 52(2): 385-393.
[22]	Reed I S, Gau Y L, and Truong T K. CFAR detection and estimation for STAP radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(3): 722-735.
[23]	Mestre X. Improved estimation of eigenvalues and eigenvectors of covariance matrices using their sample estimations[J]. IEEE Transactions on Information Theory, 2008, 54(11): 5113-5129.
[24]	Wang Y L, Liu W J, Xie W C, et al.. Reduced-rank space-time adaptive detection for airborne radar[J]. Science China Information Sciences, 2014, 57: 082310.
[25]	Guerci J R. Space-time Adaptive Processing for Radar[M]. London: Artech House, 2003: 51-72.
[26]	Benaych Georges F and Nadakuditi R R. The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices[J]. Advances in Mathematics, 2011, 227(1): 494-521.
[27]	Hiemstra J D. Robust implementations of the multistage wiener filter[D]. [Ph.D. dissertation], Virginia Polytechnic Institute and State University, 2003.
[28]	Skolnik M I. Radar Handbook[M]. New York: McGraw-Hill, 1990.
[29]	Gerlach K and Picciolo M L. Airborne/spacebased radar STAP using a structured covariance matrix[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(1): 269-281.
[30]	刘维建, 谢文冲, 王永良. 基于对角加载的自适应匹配滤波器和自适应相干估计器[J]. 系统工程与电子技术, 2013, 35(3): 463-468.Liu W J, Xie W C, and Wang Y L. AMF and ACE detectors based on diagonal loading[J]. Systems Engineering and Electronics, 2013, 35(3): 463-468.
[31]	Gau Y L. CFAR detection algorithm for STAP airborne radar[D]. [Ph.D. dissertation], University of Southern California, 1996.