基于壓縮感知的CFAR目標(biāo)檢測(cè)算法

馬俊虎; 劉長遠(yuǎn); 甘露

doi:10.11999/JEIT170382

基于壓縮感知的CFAR目標(biāo)檢測(cè)算法

doi: 10.11999/JEIT170382

基金項(xiàng)目:

國家自然科學(xué)基金委員會(huì)-中國工程物理研究院NSAF聯(lián)合基金(U1530126)

計(jì)量
- 文章訪問數(shù): 1855
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2017-04-26
- 修回日期: 2017-07-10
- 刊出日期: 2017-12-19

CFAR Target Detection Algorithm Based on Compressive Sensing

Funds:

The National Natural Science Foundation of China-China Academy of Engineering Physics Joint Foundation (NSAF) (U1530126)

摘要

摘要: 該文提出一種基于壓縮感知(Compressive Sensing, CS)的恒虛警率(Constant False Alarm Rate, CFAR)目標(biāo)檢測(cè)算法，首先分析了目標(biāo)在距離單元上具有稀疏特性，并構(gòu)造了目標(biāo)回波的稀疏字典，設(shè)計(jì)特定的測(cè)量矩陣以及基于CS的CFAR檢測(cè)結(jié)構(gòu)，然后實(shí)現(xiàn)了對(duì)回波信號(hào)的壓縮測(cè)量和CFAR檢測(cè)，無需對(duì)回波信號(hào)重構(gòu)。該文提出的算法具有很好的降噪性能并提高了檢測(cè)效率，可以對(duì)低信噪比、低信雜比信號(hào)成功檢測(cè)。仿真結(jié)果表明：當(dāng)信噪比為-14 dB，信雜比為-10 dB時(shí)，該算法與傳統(tǒng)匹配濾波檢測(cè)算法相比，減少了一半數(shù)據(jù)運(yùn)算量，性能明顯優(yōu)于壓縮匹配濾波檢測(cè)算法。
- 目標(biāo)檢測(cè) /
- 恒虛警率 /
- 壓縮感知 /
- 測(cè)量矩陣
Abstract: A new Constant False Alarm Rate (CFAR) target detection algorithm is proposed based on Compressive Sensing (CS). Firstly, the sparsity of target in the distance dimension is analyzed and the sparse dictionary is constructed for the echo signal. Secondly, a certain measurement matrix and CFAR detection structure are designed based on CS. The proposed detector can detect sparse signals directly with high accuracy without any signal reconstruction. The proposed algorithm has a good noise reduction performance, which can detect low SNR and low Signal-to-Interference Ratio (SIR) signals successfully. Finally, computer simulation results verify that when SNR is equal to -14 dB and SIR is equal to -10 dB, the proposed detector can reduce the half measurements via compared with classical Matched Filter (MF) algorithm. Whats more, the performance of the proposed detector is better than CS MF algorithm.
- Target detection /
- CFAR /
- Compressive Sensing (CS) /
- Measurement matrix

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