基于双阶段互信息准则的多目标检测波形设计

doi:10.12305/j.issn.1001-506X.2022.09.05

系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (9): 2736-2742.doi: 10.12305/j.issn.1001-506X.2022.09.05

基于双阶段互信息准则的多目标检测波形设计

肖宇^1,^2,*, 邓正宏¹, 张展¹

1. 西北工业大学自动化学院, 陕西西安 710072
2. 空军工程大学防空反导学院, 陕西西安 710051

收稿日期:2021-03-08 出版日期:2022-09-01 发布日期:2022-09-01
通讯作者: 肖宇
作者简介:肖宇(1986—), 男, 讲师, 博士研究生, 主要研究方向为雷达信号处理、武器系统总体、系统工程|邓正宏(1974—), 男, 教授, 博士, 主要研究方向为复杂系统理论、系统工程|张展(1990—), 男, 博士研究生, 主要研究方向为多智能体协同控制理论
基金资助:
国家自然科学基金(61901513);陕西省自然科学基础研究计划(2019JQ-709)

Waveform design based on two-stage mutual information for multi-target detection

Yu XIAO^1,^2,*, Zhenghong DENG¹, Zhan ZHANG¹

1. School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
2. School of Air Defense and Antimissile, Air Force Engineering University, Xi'an 710051, China

Received:2021-03-08 Online:2022-09-01 Published:2022-09-01
Contact: Yu XIAO

摘要/Abstract

摘要：

在有限信噪比情况下, 雷达对多目标的检测性能受限于参数估计精度和发射脉冲积累, 而波形设计为雷达性能提升提供了自由度。本文以信噪比为约束条件, 以假设概率与设计波形的加权和迭代波形发射, 分阶段提出了基于单假设互信息最大化、基于多假设间互信息最小化的波形优化方法, 实现了提升参数估计精度与降低发射脉冲次数的均衡处理。仿真验证了目标参数估计精度与目标检测性能间呈正相关关系, 结果表明，基于双阶段互信息准则设计的波形能够快速检测多目标方位, 提升目标检测性能。

关键词: 互信息, 多目标检测, 信噪比, 认知雷达, 波形设计

Abstract:

In the case of limited signal-to-noise ratio, the radar's detection performance for multiple targets is limited by parameter estimation accuracy and transmit pulse accumulation, and the waveform design provides a degree of freedom for radar performance improvement. In this paper, under the constraint of signal-to-noise ratio, the weighted sum of the hypothesis probability and the designed waveform is used to transmit the waveform iteratively, the waveform optimization method based on the mutual information maximization of a single hypothesis and the mutual information minimization between multiple hypotheses are proposed in stages. Parameter estimation accuracy improvement and the number of transmitted pulses reduction are realized. The simulation verifies the positive correlation between the target parameter estimation accuracy and the target detection performance. The results show that the waveform designed based on the two-stage mutual information criterion can quickly detect the orientation of multiple targets and improve the target detection performance.

Key words: mutual information, multi-target detection, signal-to-noise ratio, cognitive radar, waveform design

中图分类号:

TN951

肖宇, 邓正宏, 张展. 基于双阶段互信息准则的多目标检测波形设计[J]. 系统工程与电子技术, 2022, 44(9): 2736-2742.

Yu XIAO, Zhenghong DENG, Zhan ZHANG. Waveform design based on two-stage mutual information for multi-target detection[J]. Systems Engineering and Electronics, 2022, 44(9): 2736-2742.

图/表 4

参考文献 18

1	BENU S L. Cognitive radar: waveform design for target detection[C]//Proc. of the IEEE International Microwave Symposium, 2017: 330-332.
2	HAYKIN S, XUE Y, DAVIDSON T N. Optimal waveform design for cognitive radar[C]//Proc. of the Asilomar Conference on Signals, Systems and Computers, 2008: 3-7.
3	XIN F M , WANG B , LI S M , et al. Adaptive radar waveform design based on weighted MI and the difference of two mutual information metrics[J]. Complexity, 2021, doi: 10.1155/2021/8947450
4	TANG B , TANG J , PENG Y N . MIMO radar waveform design in colored noise based on information theory[J]. IEEE Trans.on Signal Processing, 2010, 58 (9): 4684- 4697. doi: 10.1109/TSP.2010.2050885
5	赵俊龙, 李伟, 王泓霖, 等. 基于长短时记忆网络的雷达波形设计[J]. 系统工程与电子技术, 2021, 43 (2): 376- 382.
	ZHAO J L , LI W , WANG H L , et al. Waveform design of radar based on long short-term memory network[J]. Systems Engineering and Electronics, 2021, 43 (2): 376- 382.
6	YU X , ALHUJAILI K , CUI G , et al. MIMO radar waveform design in the presence of multiple targets and practical constraints[J]. IEEE Trans.on Signal Processing, 2020, 68, 1974- 1989. doi: 10.1109/TSP.2020.2979602
7	TANG B , STOICA P . Information-theoretic waveform design for MIMO radar detection in range-spread clutter[J]. Signal Processing, 2021, 182 (5): 107961.
8	赵宜楠, 宋群, 冯翔, 等. 基于模糊函数构型的动目标探测波形设计[J]. 系统工程与电子技术, 2020, 42 (2): 263- 270.
	ZHAO Y N , SONG Q , FENG X , et al. Waveform design based on ambiguity function formulation for moving target detection[J]. Systems Engineering and Electronics, 2020, 42 (2): 263- 270.
9	GOODMAN N A , VENKATA P R , NEIFELD M A . Adaptive waveform design and sequential hypothesis testing for target recognition with active sensors[J]. IEEE Journal of Selected Topics in Signal Processing, 2007, 1 (1): 105- 113. doi: 10.1109/JSTSP.2007.897053
10	ROMERO R A , BAE J , GOODMAN N A . Theory and application of SNR and mutual information matched illumination waveforms[J]. IEEE Trans.on Aerospace Electronic Systems, 2011, 47 (2): 912- 927. doi: 10.1109/TAES.2011.5751234
11	ZHU B Q, GAO Y S, SHENG H, et al. Waveform design based multi-target hypothesis testing under unknown clutter parameters[C]//Proc. of the International Geoscience and Remote Sensing Symposium, 2016: 6617-6620.
12	WANG L , WONG K K , WANG H , et al. MIMO radar adaptive waveform design for extended target recognition[J]. International Journal of Distributed Sensor Networks, 2015, 11 (6): 154931. doi: 10.1155/2015/154931
13	肖宇, 邓正宏. 信杂噪比约束下基于互信息的雷达波形设计[J]. 系统工程与电子技术, 2021, 43 (7): 1775- 1780.
	XIAO Y , DENG Z H . MI-based radar waveform design under signal to interference plus noise ratio constraint[J]. Systems Engineering and Electronics, 2021, 43 (7): 1775- 1780.
14	WANG L , ZHU W , ZHANG Y L , et al. Multi-target detection and adaptive waveform design for cognitive MIMO radar[J]. IEEE Sensors Journal, 2018, 18 (24): 9962- 9970. doi: 10.1109/JSEN.2018.2873103
15	YANG Y , BLUM R S . MIMO radar waveform design based on mutual information and minimum mean-square error estimation[J]. IEEE Trans.on Aerospace and Electronic Systems, 2007, 43 (1): 330- 343. doi: 10.1109/TAES.2007.357137
16	HERBERT S , HOPGOOD J R , MULGREW B . Computationally simple MMSE (a-optimal) adaptive beam-pattern design for MIMO active sensing systems via a linear-Gaussian approximation[J]. IEEE Trans.on Signal Processing, 2018, 66 (18): 4935- 4945. doi: 10.1109/TSP.2018.2864571
17	HULEIHEL W , TABRIKIAN J , SHAVIT R . Optimal adaptive waveform design for cognitive MIMO radar[J]. IEEE Trans.on Signal Processing, 2013, 61 (20): 5075- 5089. doi: 10.1109/TSP.2013.2269045
18	CHEN Y . Adaptive distributed MIMO radar waveform optimization based on mutual information[J]. IEEE Trans.on Aerospace and Electronic Systems, 2013, 49 (2): 1374- 1385. doi: 10.1109/TAES.2013.6494422

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基于双阶段互信息准则的多目标检测波形设计

Waveform design based on two-stage mutual information for multi-target detection

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