电子学报 ›› 2021, Vol. 49 ›› Issue (11): 2117-2123.DOI: 10.12263/DZXB.20200983

• 学术论文 • 上一篇    下一篇

一种复域压缩感知目标方位估计方法

郑恩明1, 陈新华1, 周权斌1,2, 李嶷1, 杨鹤1,3, 孟浩4   

  1. 1.中国科学院声学研究所,北京 100190
    2.中国科学院大学,北京 100049
    3.哈尔滨工程大学水声工程学院, 黑龙江 哈尔滨 150001
    4.沈阳辽海装备有限责任公司,辽宁 沈阳 110003
  • 收稿日期:2020-09-06 修回日期:2021-01-23 出版日期:2021-11-25 发布日期:2021-11-25
  • 作者简介:郑恩明 男,1985年8月出生,河南省周口人.副研究员.2009年和2014年分别在哈尔滨工程大学、中国科学院大学获工学学士和工学博士学位,其后在中国科学院声学研究所从事阵列信号处理、水下目标检测与定位方面等研究工作.E‑mail:zhengembj@163.com
    陈新华 男,1978年7月出生,江苏省泰州人.研究员、博士生导师.1999年和2004年在哈尔滨工程大学获工学学士和工学博士学位.现为中国科学院声学研究所水声工程中心实验室副主任,主要从事水声信号处理、水声工程、水下目标检测与定位等方面研究.
  • 基金资助:
    武器装备预先研究项目(3020201030701)

A Target Azimuth Estimation Method Based on Complex Domain Compressed Sensing

En-ming ZHENG1, Xin-hua CHEN1, Quan-bin ZHOU1,2, Yi LI1, He YANG1,3, Hao MENG4   

  1. 1.Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190,China
    2.University of Chinese Academy of Sciences,Beijing 100049,China
    3.College of Underwater Acoustic Engineering,Harbin Engineering University,Harbin,Heilongjiang 150001,China
    4.Shenyang Liaohai Equipment Co. Ltd. ,Shenyang,Liaoning 110003,China
  • Received:2020-09-06 Revised:2021-01-23 Online:2021-11-25 Published:2021-11-25

摘要:

针对频域压缩感知目标方位估计方法的性能退化问题,本文通过对线列阵接收信号进行复解析变换,按预估方位在复域对各阵元信号进行时延补偿、相关和累积处理,构建复域感知矩阵和测量值,采用复域压缩感知方法实现空间谱合成和目标方位估计.数值仿真和实测数据处理结果表明,在同一检测概率下,相比频域压缩感知方法,该方法对输入信噪比的最低要求得到近10lgMdB(M为通道数)的降低,提升了对弱目标的检测能力.

关键词: 阵列信号处理, 目标方位估计, 复域压缩感知, 复域感知矩阵

Abstract:

For the performance degradation problem of target azimuth estimation method based on frequency domain compressed sensing, the complex domain signal was obtained via complex analytical transformation of the array pickup data, and the complex domain sensing matrix and measured value were constructed after the time delay compensating, correlation and accumulation processing of each channel data. Then, the spatial spectrum was synthesized through the compressed sensing method in complex domain, and the target azimuth estimation value was obtained. The processing results of numerical simulation and measured data show that, for the same detection probability and compared with frequency domain compressed sensing, the demand of input signal to noise ratio of this method was reduced by nearly 10lgMdB (M is the channel number of array), and the ability of weak target detection was enhanced.

Key words: array signal processing, target azimuth estimation, complex domain compressed sensing, complex domain sensing matrix

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