子空间约束秩1干扰下的雷达信号检测

doi:10.12305/j.issn.1001-506X.2022.01.13

系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (1): 94-99.doi: 10.12305/j.issn.1001-506X.2022.01.13

子空间约束秩1干扰下的雷达信号检测

邹鲲, 来磊*, 骆艳卜, 李伟

空军工程大学信息与导航学院, 陕西西安 710077

收稿日期:2020-08-07 出版日期:2022-01-01 发布日期:2022-01-19
通讯作者: 来磊
作者简介:邹鲲(1976—), 男, 副教授, 博士, 主要研究方向为统计信号处理、雷达信号检测与估计等|来磊(1983—), 男, 讲师, 博士, 主要研究方向为导航信息处理、智能信息处理|骆艳卜(1980—), 男, 讲师, 硕士, 主要研究方向为军用无线电导航与雷达信息处理|李伟(1978—), 男, 副教授, 博士, 主要研究方向为雷达干扰与抗干扰
基金资助:
国家自然科学基金(61871396);博士后基金(2017M623352);博士后基金(2018T111148);陕西省自然科学基金(2020JM-343);陕西省自然科学基金(2020JM352)

Radar signal detection with subspace constrained rank one interference

Kun ZOU, Lei LAI*, Yanbo LUO, Wei LI

School of Information and Navigation, Air Force Engineering University, Xi'an 710077, China

Received:2020-08-07 Online:2022-01-01 Published:2022-01-19
Contact: Lei LAI

摘要/Abstract

摘要：

考虑雷达待检测单元在受到子空间约束的秩1干扰情况下的自适应检测问题, 即待检测单元背景噪声协方差矩阵中叠加有一个秩为1的干扰协方差矩阵, 并假定干扰分量约束在一个已知的子空间内。采用双步广义似然比检验准则, 得到子空间约束的秩为1的干扰检测器(subspace constrained rank one interference detector, SC-ROID)。还推导了一种降维自适应相干估计器(rank-reduced adaptive coherent estimator, rr-ACE), 可以利用子空间的先验信息降低检测器计算量。计算机仿真分析表明, SC-ROID在无干扰或无干扰先验信息条件下, 与自适应相干估计器性能相当, 而在其他情况下具有较好的检测性能。而rr-ACE在小样本条件下的检测性能较好。

关键词: 自适应检测, 秩1干扰, 子空间约束干扰, 广义似然比检验, 降维

Abstract:

To sdve adaptive detection problem that the cell under test is contaminated by the subspace constrained rank one interference, namely the noise covariance matrix of the test data is superposed by a rank one interference covariance matrix, the interference is assumed to be located in a known subspace, and using the 2-step generalized likelihood ratio test criterion, we derive a subspace constrained rank one interference detector (SC-ROID). We also derive a rank-reduced adaptive coherent estimator (rr-ACE), which exploits the prior information of the interference to reduce the computational load. The computer simulation results show that, under the condition of no interference or no prior information of the interference, the SC-ROID performance amounts to the adaptive coherent estimator detector. In other cases, the SC-ROID outperforms other conventional detectors. The rr-ACE outperforms other competitors when the size of the reference data is low.

Key words: adaptive detection, rank one interference, subspace constrained interference, generalized likelihood ratio test, rank-reduced

中图分类号:

TP391

邹鲲, 来磊, 骆艳卜, 李伟. 子空间约束秩1干扰下的雷达信号检测[J]. 系统工程与电子技术, 2022, 44(1): 94-99.

Kun ZOU, Lei LAI, Yanbo LUO, Wei LI. Radar signal detection with subspace constrained rank one interference[J]. Systems Engineering and Electronics, 2022, 44(1): 94-99.

图/表 4

参考文献 20

1	DE MAIO A , GRECO M S . Modern radar detection theory[M]. Massachusets: Massachusets SciTech Publishing, 2016.
2	KELLY E J . An adaptive detection algorithm[J]. IEEE Trans.on Aerospace and Electronic System, 1986, 22 (1): 115- 127.
3	ROBEY F C , FUHRMANN D R , KELLY E J. , et al. A CFAR adaptive matched filter detector[J]. IEEE Trans.on Aerospace and Electronic System, 1992, 28 (1): 207- 216.
4	DE MAIO A , IOMMELLI S . Coincidence of the Rao test, Wald test, and GLRT in partially homogeneous environment[J]. IEEE Signal Process Letters, 2008, 15, 385- 388. doi: 10.1109/LSP.2008.920016
5	DE MAIO A . Rao test for adaptive detection in Gaussian interference with unknown covariance matrix[J]. IEEE Trans.on Signal Processing, 2007, (55): 3577- 3584.
6	DE MAIO A . A new derivation of the adaptive matched filter[J]. IEEE Signal Processing Letters, 2004, 11, 792- 793. doi: 10.1109/LSP.2004.835464
7	BESSON O , BIDON S . Adaptive processing with signal contaminated training samples[J]. IEEE Trans.on Signal Processing, 2013, 61 (7): 4318- 4329.
8	KRAUT S , SCHARF L L . The CFAR adaptive subspace detector is a scale-invariant GLRTs[J]. IEEE Trans.on Signal Processing, 1999, 47 (9): 2538- 2541. doi: 10.1109/78.782198
9	BIDON S , BESSON O , TOURNERET J Y . The adaptive coherence estimator is the generalized likelihood ratio test for a class of heterogeneous environments[J]. IEEE Signal Processing, 2008, 15, 281- 284. doi: 10.1109/LSP.2007.916044
10	BESSON O , ORLANDO D . Adaptive detection in nonhomogeneous environments using the generalized eigenrelation[J]. IEEE Signal Processing Letters, 2007, 14 (10): 731- 734. doi: 10.1109/LSP.2007.898355
11	BESSON O , TOURNERET J Y , BIDON S . Knowledge-aided Bayesian detection in heterogeneous environments[J]. IEEE Signal Processing Letters, 2007, 14 (5): 355- 358. doi: 10.1109/LSP.2006.888088
12	FENG D , XU L , PAN X , et al. Jamming wideband radar using interrupted-sampling repeater[J]. IEEE Trans.on Aerospace and Electronic System, 2017, 53 (3): 1341- 1354. doi: 10.1109/TAES.2017.2670958
13	LIU W J , HAN H , LIU J , et al. Multichannel radar adaptive signal detection in interference and structure nonhomogeneity[J]. Science China Information Sciences, 2017, 60 (11): 112- 302.
14	BESSON O. Detection in the presence of surprise or undernulled interference[J]. IEEE Signal Processing Letters, 14(5): 352-354.
15	ADDABBO P , BESSON O , ORLANDO D , et al. Adaptive detection of coherent radar targets in the presence of noise jamming[J]. IEEE Trans.on Signal Processing, 2019, 67 (24): 6498- 6510. doi: 10.1109/TSP.2019.2954499
16	WANG Z . Adaptive detection of a subspace signal in Gaussian noise and rank-one interference[J]. Digital Signal Processing, 2020, 96, 111- 222.
17	BESSON O, CHAUMETTE E, VINCENT F. Adaptive detection of a Gaussian signal in Gaussian noise[C]//Proc. of the 6th IEEE International Workshop on Computer Advances Multi-Sensor Adaptive Processings, 2015: 117-120.
18	COLUCCIA A , RICCI G , BESSON O . Design of robust radar detectors through random perturbation of the target signature[J]. IEEE Trans.on Signal Processing, 2019, 67 (19): 5118- 5129. doi: 10.1109/TSP.2019.2935915
19	ORLANDO D . A novel noise jamming detection algorithm for radar applications[J]. IEEE Trans.on Signal Processing, 2017, 24 (2): 206- 210. doi: 10.1109/LSP.2016.2645793
20	邹鲲, 廖桂生, 李军, 等. 非高斯杂波下知识辅助检测的认知方法[J]. 电子学报, 2014, 42 (6): 1047- 1054. doi: 10.3969/j.issn.0372-2112.2014.06.002
	ZOU K , LIAO G S , LI J , et al. Cognitive method for knowledge aided detection in non-Gaussian clutter[J]. Acta Electronica Sinica, 2014, 42 (6): 1047- 1054. doi: 10.3969/j.issn.0372-2112.2014.06.002

[1]	庞晓娇, 赵永波, 曹成虎, 胡毅立, 陈胜. 基于协方差拟合准则的降维空时自适应处理方法[J]. 系统工程与电子技术, 2022, 44(1): 86-93.
[2]	孙云柯, 方志耕, 陈顶. 基于动态灰色主成分分析的多时刻威胁评估[J]. 系统工程与电子技术, 2021, 43(3): 740-746.
[3]	霍超颖, 闫华, 冯雪健, 殷红成, 邢笑宇, 陆金文. HRRP稀疏自编码器深层特征与散射中心特征的关联性研究[J]. 系统工程与电子技术, 2021, 43(11): 3040-3053.
[4]	赵燕慧, 汤建龙, 李骥阳, 毕鲁浩. 对降维STAP机载雷达的延时混叠转发干扰方法分析[J]. 系统工程与电子技术, 2020, 42(8): 1718-1725.
[5]	庞晓娇, 赵永波, 曹成虎, 徐保庆, 陈胜. 基于时域自适应FIR滤波的空时处理方法[J]. 系统工程与电子技术, 2019, 41(12): 2669-2674.
[6]	徐乐, 吴日恒, 张小飞. L阵基于降维MUSIC的二维DOA与频率估计[J]. 系统工程与电子技术, 2019, 41(1): 1-8.
[7]	王卓, 郑学合, 常晓兰. 基于旋转降维的高速隐身目标检测算法[J]. 系统工程与电子技术, 2019, 41(1): 14-20.
[8]	简涛, 何友, 廖桂生, 王捷, 周强. 辅助数据缺失环境下结构化自适应目标检测器[J]. 系统工程与电子技术, 2017, 39(2): 277-281.
[9]	徐丽琴, 李勇. 单基地MIMO雷达低复杂度求根MUSIC角度估计方法[J]. 系统工程与电子技术, 2017, 39(11): 2434-2440.
[10]	施赛楠, 水鹏朗, 杨春娇, 许述文. 基于逆高斯纹理空间相关性的雷达目标检测[J]. 系统工程与电子技术, 2017, 39(10): 2215-2220.
[11]	黄湘远, 汤霞清, 武萌. #br# 基于降维CKF和平滑的SINS/OD动基座对准[J]. 系统工程与电子技术, 2016, 38(9): 2135-2141.
[12]	王秀红1,2, 毛兴鹏1,3, 张乃通1. 基于降维稀疏重构的相干信源二维DOA估计方法[J]. 系统工程与电子技术, 2016, 38(8): 1709-1715.
[13]	时艳玲, 林毓峰, 宛汀. 部分均匀海杂波中雷达目标的平滑自适应检测[J]. 系统工程与电子技术, 2016, 38(12): 2745-2751.
[14]	赵宜楠, 姜智卓, 唐晨亮, 周志权. 复合高斯杂波中极化MIMO雷达的自适应检测[J]. 系统工程与电子技术, 2015, 37(11): 2474-2479.
[15]	杨静林, 唐林波, 宋丹, 赵保军. 基于自适应聚类流形学习的增量样本降维与识别[J]. 系统工程与电子技术, 2015, 37(1): 199-205.

子空间约束秩1干扰下的雷达信号检测

Radar signal detection with subspace constrained rank one interference

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 4

参考文献 20

相关文章 15

编辑推荐

Metrics

本文评价