Waveform design and high-resolution imaging of cognitive radar based on compressive sensing

被引：22

作者：

Luo Ying ^{[1
]}

Zhang Qun ^{[1
]}

Hong Wen ^{[2
]}

Wu YiRong ^{[2
]}

机构：

[1] AF Engn Univ, Telecommun Engn Inst, Xian 710077, Peoples R China

[2] Chinese Acad Sci, Inst Elect, Beijing 100190, Peoples R China

来源：

SCIENCE CHINA-INFORMATION SCIENCES | 2012年 / 55卷 / 11期

关键词：

cognitive radar; waveform design; compressive sensing; radar imaging; TARGET RECOGNITION; SIGNAL RECOVERY; MB-OFDM; INFORMATION;

D O I：

10.1007/s11432-011-4527-x

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We introduce the compressive sensing (CS) theory for waveform design of cognitive radar, and then propose an algorithm for the high-resolution radar signal waveform and its corresponding imaging method based on the sparse orthogonal frequency division multiplexing-linear frequency modulation (OFDM-LFM) signal. We first present the principle of spectrum synthesis and high-resolution imaging based on OFDM-LFM signals. Then, we propose the spectrum-sparse waveform design criterion and the reconstruction algorithm for a high-resolution range profile (HRRP) based on CS. Based on this, we analyze in detail the relationship between the scattering characteristics of the target and the parameters of the designed signal, and we construct the feedback of the target characteristics on the waveforms. Therefore, the "cognitive" function of radar can be achieved by adaptively adjusting the waveform with the target characteristics. Simulations are given to validate the effectiveness of the proposed algorithm.

引用

页码：2590 / 2603

页数：14

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