基于压缩感知的外辐射源雷达目标参数估计方法

Translated title of the contribution: Target Parameter Estimation Method for Passive Radar Based on Compressed Sensing

Quande Sun, Tao Shan*, Juan Zhao, Xia Bai, Yuan Feng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Passive radar can estimate the range-Doppler information of the target by calculating the cross ambiguity function. But this method represents some problems, for example, the weak target can be masked by high sidelobes of strong target and low resolution. To solve these problems, a target parameter estimation method was proposed for passive radar based on compressed sensing. Firstly, a distributed compressed sensing simultaneous subspace pursuit algorithm was proposed to achieve the range domain sparse reconstruction. Then, taking an enlarged orthogonal matching pursuit algorithm, the Doppler domain sparse reconstruction was carried out. The results of simulation and measured data show that the proposed method can reduce the influence of the sidelobe generated by cross ambiguity function, improve the resolution, and avoid the problems of large dictionary size and high time complexity.

Translated title of the contributionTarget Parameter Estimation Method for Passive Radar Based on Compressed Sensing
Original languageChinese (Traditional)
Pages (from-to)1298-1307
Number of pages10
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume43
Issue number12
DOIs
Publication statusPublished - Dec 2023

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