基于线性约束最小方差原则的稳健快速自适应脉冲压缩方法

doi:10.12305/j.issn.1001-506X.2022.12.05

系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (12): 3621-3630.doi: 10.12305/j.issn.1001-506X.2022.12.05

基于线性约束最小方差原则的稳健快速自适应脉冲压缩方法

裴家正¹, 黄勇^1,*, 陈宝欣², 关键¹, 陈小龙¹

1. 海军航空大学航空作战勤务学院, 山东烟台 264000
2. 中国人民解放军92337部队, 辽宁大连 116000

收稿日期:2021-06-23 出版日期:2022-11-14 发布日期:2022-11-24
通讯作者: 黄勇
作者简介:裴家正 (1994—), 男, 博士研究生, 主要研究方向为雷达多维信号处理|黄勇 (1979—), 男, 副教授, 博士, 主要研究方向为MIMO雷达目标检测算法|陈宝欣 (1990—), 男, 工程师, 博士, 主要研究方向为阵列信号处理、雷达多维信号处理|关键 (1968—), 男, 教授, 博士, 主要研究方向为雷达目标检测与跟踪、侦察图像处理和信息融合|陈小龙 (1979—), 男, 副教授, 博士, 主要研究方向为雷达动目标检测、海杂波抑制、雷达信号精细化处理
基金资助:
国家自然科学基金(61871391);国家自然科学基金(U1933135);国家自然科学基金(61871392);国家自然科学基金(62101583);国防科技基金(2019-JCJQ-JJ-058);山东省高等学校青创科技支持计划(2019KJN026);山东省自然科学基金(ZR202102190211)

Robust fast adaptive pulse compression method based on linearly constrained minimum variance principle

Jiazheng PEI¹, Yong HUANG^1,*, Baoxin CHEN², Jian GUAN¹, Xiaolong CHEN¹

1. Aviation Operations and Service Institute, Naval Aviation University, Yantai 264000, China
2. Unit 92337 of the PLA, Dalian 116000, China

Received:2021-06-23 Online:2022-11-14 Published:2022-11-24
Contact: Yong HUANG

摘要/Abstract

摘要：

针对线性调频信号在距离单元内的回波采样点与目标点失配, 即采样失配的情况下, 自适应脉冲压缩性能下降的问题, 对快速自适应脉冲压缩(fast adaptive pulse compression, FAPC)方法进行改进, 提出一种基于线性约束最小方差(linearly constrained minimum variance, LCMV)原则的连续分块FAPC (contiguous block FAPC, CFAPC)方法。该方法将自适应波束形成方法类比到自适应脉冲压缩滤波方法中, 首先在最小方差无畸变响应(minimum variance distortionless response, MVDR)原则保持增益的前提下增加零点约束条件, 加宽零点凹口的宽度; 而后对分块的协方差矩阵设置置零条件, 抑制旁瓣能量, 实现在采样失配情况下保持稳健的目的。实验结果表明, 在脉内多普勒频移和采样失配同时存在的情况下, 所提方法可以更好地抑制目标的距离旁瓣, 具有较好的稳健性。

关键词: 线性调频信号, 采样失配, 自适应脉冲压缩, 距离旁瓣抑制, 线性约束最小方差

Abstract:

The performance of adaptive pulse compression degrades when echo sampling point of the linear frequency modulation (LFM) signals mismatched with the target point in a range cell (namely sampling mismatch). In order to solve the problem, this paper improves the fast adaptive pulse compression (FAPC) method and proposes a new continuous block FAPC (CFAPC) method which is based on linearly constrained minimum variance (LCMV) principle.The method analogizes the adaptive beamforming method to the adaptive pulse compression filtering method, firstly utilizes minimum variance distortion response (MVDR) principle to keep the target's gain and sets the zeroing constraints to widen the width of the energy's notch; then applies another zeroing constraint to block covariance matrix to further suppress the energy of sidelobes and maintain the robustness when sampling mismatch happens. The experiments show that the proposed method can better suppress the range sidelobes of the target and it is more robust when theintra-pulse Doppler shift and sampling mismatch exist simultaneously.

Key words: linear frequency modulation signal, sampling mismatch, adaptive pulse compression, range sidelobes suppression, linearly constrained minimum variance (LCMV)

中图分类号:

TN958.2

裴家正, 黄勇, 陈宝欣, 关键, 陈小龙. 基于线性约束最小方差原则的稳健快速自适应脉冲压缩方法[J]. 系统工程与电子技术, 2022, 44(12): 3621-3630.

Jiazheng PEI, Yong HUANG, Baoxin CHEN, Jian GUAN, Xiaolong CHEN. Robust fast adaptive pulse compression method based on linearly constrained minimum variance principle[J]. Systems Engineering and Electronics, 2022, 44(12): 3621-3630.

图/表 18

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参考文献 35

1	RICHARDS M A . Fundamentals of radar signal processing[M]. New York: The McGraw-Hill Companies, 2005: 230- 231.
2	ZHANG W , SUN , MINN H . Algorithm and performance analysis for frame detection based on matched filtering[J]. IEEE Access, 2020, 8, 40559- 40572. doi: 10.1109/ACCESS.2020.2975266
3	NARAYANAN R M , LIU A Z , RANGASWAMY M . An information elasticity framework for the adaptive matched filter[J]. IEEE Trans.on Aerospace and Electronic Systems, 2020, 56 (6): 4916- 4929. doi: 10.1109/TAES.2020.3009508
4	ACKROYD M H , GHANI F . Optimum mismatched filters for sidelobe suppression[J]. IEEE Trans.on Aerospace and Electronic Systems, 1973, 9 (2): 214- 218.
5	TSAO J , STEINBERG B D . Reduction of sidelobe and speckle artifacts in microwave imaging the CLEAN technique[J]. IEEE Trans.on Antennas and Propagation, 1988, 36 (4): 543- 556. doi: 10.1109/8.1144
6	RABASTE O , BOSSE J . Robust mismatched filter for off-grid target[J]. IEEE Signal Processing Letters, 2019, 26 (8): 1147- 1151. doi: 10.1109/LSP.2019.2923054
7	ZHOU K , LI D X , SU Y , et al. Joint design of transmit waveform and mismatch filter in the presence of interrupted sampling repeater jamming[J]. IEEE Signal Processing Letters, 2020, 27, 1610- 1614. doi: 10.1109/LSP.2020.3021667
8	潘孟冠, 胡金龙, 陈伯孝, 等. 基于CLEAN思想的互补码信号脉冲压缩算法[J]. 雷达科学与技术, 2020, 18 (3): 254- 261.
	PAN M G , HU J L , CHEN B X , et al. CLEAN concept based pulse compression algorithm for complementary code signal[J]. Radar Science and Technology, 2020, 18 (3): 254- 261.
9	BLUNT S D , GERLACH K . Adaptive pulse compression via MMSE estimation[J]. IEEE Trans.on Aerospace and Electronic Systems, 2006, 42 (2): 572- 584. doi: 10.1109/TAES.2006.1642573
10	BLUNT S D , GERLACH K . Multistatic adaptive pulse compression[J]. IEEE Trans.on Aerospace and Electronic Systems, 2006, 42 (3): 891- 903. doi: 10.1109/TAES.2006.248196
11	GERLACH K , BLUNT S D . Radar pulse compression repair[J]. IEEE Trans.on Aerospace and Electronic Systems, 2007, 43 (3): 1188- 1195. doi: 10.1109/TAES.2007.4383610
12	BLUNT S D, SMITH K J, GERLACH K. Doppler-compensated adaptive pulse compression[C]//Proc. of the IEEE Conference on Radar, 2006.
13	BLUNT S D , SHACKELFORD A K , GERLACH K . Doppler compensation & single pulse imaging using adaptive pulse compression[J]. IEEE Trans.on Aerospace and Electronic Systems, 2009, 45 (2): 647- 658. doi: 10.1109/TAES.2009.5089547
14	BLUNT S D, HIGGINS T. Achieving real-time efficiency for adaptive radar pulse compression[C]//Proc. of the IEEE Radar Conference, 2007: 116-121.
15	BLUNT S D , HIGGINS T . Dimensionality reduction techniques for efficient adaptive pulse compression[J]. IEEE Trans.on Aerospace & Electronic Systems, 2010, 46 (1): 349- 362.
16	HIGGINS T, BLUNT S D, GERLACH K. Gain-constrained adaptive pulse compression via an MVDR framework[C]//Proc. of the IEEE Radar Conference, 2009.
17	GUAN J , HUANG Y , HE Y . A CFAR detector for MIMO array radar based on adaptive pulse compression-Capon filter[J]. Science China Information Sciences, 2011, 54, 2411- 2424. doi: 10.1007/s11432-011-4329-1
18	LI L, YI W, KONG L J, et al. Range limited adaptive pulse compression via linear Bayes estimation[C]//Proc. of the IEEE Radar Conference, 2014: 1010-1014.
19	BAI J L, QIN P, LI H, et al. An improved adaptive pulse compression algorithm based on linear frequency modulation signal[C]//Proc. of the IEEE International Conference on Signal, Information and Data Processing, 2019.
20	刘韵佛, 刘峥, 谢荣. 互相关干扰下的MIMO雷达自适应脉冲压缩方法[J]. 西安电子科技大学学报, 2011, 38 (4): 89- 94. doi: 10.3969/j.issn.1001-2400.2011.04.016
	LIU Y F , LIU Z , XIE R . Adaptive pulse compression for MIMO radar in cross correlation interference[J]. Journal of Xidian University, 2011, 38 (4): 89- 94. doi: 10.3969/j.issn.1001-2400.2011.04.016
21	王伟, 马跃华, 郝燕玲. 基于MAPC-RISR的MIMO雷达距离——角度二维超分辨率成像算法[J]. 中国科学: 信息科学, 2015, 45 (3): 372- 384.
	WANG W , MA Y H , HAO Y L . High-resolution MIMO radar range-angle 2D imaging algorithm based on MAPC-RISR[J]. Scientia Sinica Informationis, 2015, 45 (3): 372- 384.
22	HENKE D, MCCORMICK P, BLUNT S D, et al. Practical aspects of optimal mismatch filtering and adaptive pulse compression for FM waveforms[C]//Proc. of the IEEE Radar Conference, 2015: 1149-1155.
23	李秀友, 董云龙, 黄勇, 等. 基于迭代线性约束最小方差的稳健自适应脉冲压缩方法[J]. 电子与信息学报, 2015, 37 (10): 2300- 2306.
	LI X Y , DONG Y L , HUANG Y , et al. Robust adaptive pulse compression algorithm based on reiterative linearly constrained minimum variance[J]. Journal of Electronics and Information Technology, 2015, 37 (10): 2300- 2306.
24	NING C , TIAN J , LI K , et al. Modified adaptive pulse compression algorithm for targets with range-straddling[J]. IEEE Trans.on Aerospace and Electronic Systems, 2021, 57 (5): 3057- 3070. doi: 10.1109/TAES.2021.3068438
25	CHEN B X, HUANG Y, CHEN X L, et al. Space-time-range adaptive processing for MIMO radar imaging[C]//Proc. of the International Conference on Radar, 2018.
26	MONZING R A , HAUPT R L , MILLER T W . Introduction to adaptive arrays[M]. New York: Wiley, 1980.
27	NI G , SONG Y , CHEN J F , et al. Single-channel LCMV-based adaptive beamforming with time-modulated array[J]. IEEE Antennas and Wireless Propagation Letters, 2020, 19 (11): 1881- 1885. doi: 10.1109/LAWP.2020.2997382
28	LIN J Q , CHAN S C . Recursive extended instrumental variable based LCMV beamformers for planar radial coprime arrays under spatially colored noise[J]. IEEE Trans.on Aerospace and Electronic Systems, 2021, 57 (1): 175- 189. doi: 10.1109/TAES.2020.3011870
29	ZHANG J , KOUTROUVELIS A I , HEUSDENS R , et al. Distributed rate-constrained LCMV beamforming[J]. IEEE Signal Processing Letters, 2019, 26 (5): 675- 679. doi: 10.1109/LSP.2019.2905161
30	郭翔宇, 鄢社锋, 王文侠. 基于迭代梯度方法的线性约束稳健Capon波束形成快速算法[J]. 信号处理, 2021, 37 (5): 712- 723.
	GUO X Y , YAN S F , WANG W X . A fast algorithm for linear constrained robust Capon beamforming based on iterative gradient method[J]. Journal of Signal Processing, 2021, 37 (5): 712- 723.
31	杨航. 快速稳健的自适应天线波束形成算法研究[D]. 哈尔滨: 哈尔滨工程大学, 2019.
	YANG H. Studyon fast robust beamforming algorithms[D]. Harbin: Harbin Engineering University, 2019.
32	TIAN Z , BELL K L , VAN T H L . A recursive least squares implementation for LCMP beamforming under quadratic constraint[J]. IEEE Trans.on Signal Processing, 2001, 49 (6): 1138- 1145. doi: 10.1109/78.923296
33	BLUNT S D . Polyphase-coded FM (PCFM) radar waveforms, part Ⅰ: implementation[J]. IEEE Trans.on Aerospace and Electronic Systems, 2014, 50 (3): 2218- 2229. doi: 10.1109/TAES.2014.130361
34	DAKOTA H. Robust optimal and adaptive pulse compression for FM waveforms[D]. Appleton: Lawrence University of Kansas, 2015.
35	BLUNT S D. Embedding information into radar emissions via waveform implementation[C]//Proc. of the International Waveform Diversity and Design Conference, 2010: 195-199.

实验组别	方法
实验组别	MF	MVDR-APC	MVDR-CFAPC	LCMV-CFAPC
(1)	35.4	76.7	74.5	74.3
(2)	35.4	73.4	74.2	74
(3)	31.2	46.5	61.2	64.6
(4)	34.2	57.1	71.1	72.5
(5)	35.1	47	65.7	68.3

实验组别	方法
实验组别	MF	MVDR-APC	MVDR-CFAPC	LCMV-CFAPC
(1)	0.09	0.77	0.53	0.67
(2)	0.08	0.76	0.61	0.69
(3)	0.08	0.77	0.62	0.68
(4)	0.08	0.79	0.58	0.67
(5)	0.09	0.77	0.58	0.68

MF	MVDR-APC	MVDR-CFAPC	LCMV-CFAPC
0.09	0.81	0.58	0.67

MF	MVDR-APC	LCMV-CFAPC
0.20	1.67	1.37

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[5]	崔开博, 陈曦, 黄敬健, 袁乃昌. 基于均匀圆阵时频干涉仪的LFM信号二维测向算法[J]. 系统工程与电子技术, 2017, 39(8): 1669-1676.
[6]	金艳, 高舵, 姬红兵. α稳定分布噪声下基于稳健S变换的LFM信号参数估计[J]. 系统工程与电子技术, 2017, 39(4): 693-699.
[7]	张武才, 潘明海, 陈诗弘. 基于LFM子脉冲的宽带雷达目标回波模拟方法[J]. 系统工程与电子技术, 2017, 39(4): 768-774.
[8]	刘博宇, 李陟, 杨于杰, 李宏宇, 史建华. 基于LFM信号的分布式空间动平台定位技术[J]. 系统工程与电子技术, 2017, 39(3): 482-487.
[9]	夏阳, 宋志勇, 卢再奇, 付强. 多载频相位编码雷达信号自适应脉冲压缩方法[J]. 系统工程与电子技术, 2016, 38(9): 2028-2032.
[10]	李军1,2, 林秋华1, 杨秀庭2, 康春玉2. #br# 近场宽带LFM信号被动测向和测距方法[J]. 系统工程与电子技术, 2016, 38(8): 1737-1743.
[11]	金艳, 胡碧昕, 姬红兵. α稳定分布噪声下基于最优L-柯西加权的LFM信号参数估计[J]. 系统工程与电子技术, 2016, 38(7): 1488-1495.
[12]	张民, 刘海鹏, 蔡兆晖. 基于组合窗的OFDM-NLFM信号设计[J]. 系统工程与电子技术, 2016, 38(2): 287-292.
[13]	刘凯, 韩嘉宾, 王韵白, 黄青华. 基于切割聚类的快速多分量LFM信号分离[J]. 系统工程与电子技术, 2015, 37(5): 1004-1008.
[14]	黄庆东，卢光跃，庞胜利，包志强. 改进的树型WSN分布式LCMV波束形成方法[J]. 系统工程与电子技术, 2014, 36(9): 1844-1848.
[15]	马秀荣，张媛，白媛，曹多. 基于功率谱形态学运算的LFM信号参数估计[J]. 系统工程与电子技术, 2014, 36(1): 16-22.

基于线性约束最小方差原则的稳健快速自适应脉冲压缩方法

Robust fast adaptive pulse compression method based on linearly constrained minimum variance principle

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