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基于聯(lián)合稀疏恢復(fù)的寬帶雷達(dá)動目標(biāo)檢測方法

方明,  戴奉周,  劉宏偉,  王小謨,  秦童

方明, 戴奉周, 劉宏偉, 王小謨, 秦童. 基于聯(lián)合稀疏恢復(fù)的寬帶雷達(dá)動目標(biāo)檢測方法[J]. 電子與信息學(xué)報(bào), 2015, 37(12): 2977-2983. doi: 10.11999/JEIT150442
引用本文: 方明, 戴奉周, 劉宏偉, 王小謨, 秦童. 基于聯(lián)合稀疏恢復(fù)的寬帶雷達(dá)動目標(biāo)檢測方法[J]. 電子與信息學(xué)報(bào), 2015, 37(12): 2977-2983. doi: 10.11999/JEIT150442
Fang Ming, Dai Feng-zhou, Liu Hong-wei, Wang Xiao-mo, Qin Tong. Detection of Moving Targets for Wideband Radar Based on Joint-sparse Recovery[J]. Journal of Electronics & Information Technology, 2015, 37(12): 2977-2983. doi: 10.11999/JEIT150442
Citation: Fang Ming, Dai Feng-zhou, Liu Hong-wei, Wang Xiao-mo, Qin Tong. Detection of Moving Targets for Wideband Radar Based on Joint-sparse Recovery[J]. Journal of Electronics & Information Technology, 2015, 37(12): 2977-2983. doi: 10.11999/JEIT150442

基于聯(lián)合稀疏恢復(fù)的寬帶雷達(dá)動目標(biāo)檢測方法

doi: 10.11999/JEIT150442 cstr: 32379.14.JEIT150442
  • 1.

    (西安電子科技大學(xué)雷達(dá)信號處理國家重點(diǎn)實(shí)驗(yàn)室 西安 710071) ②(中國電子科學(xué)研究院 北京 100041)

基金項(xiàng)目: 

國家自然科學(xué)基金(61271291，61201285)，新世紀(jì)優(yōu)秀人才支持計(jì)劃(NCET-09-0630)，全國優(yōu)秀博士學(xué)位論文作者專項(xiàng)資金(FANEDD-201156)和中央高校基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金

Detection of Moving Targets for Wideband Radar Based on Joint-sparse Recovery

  • 1.

    (National Laboratory of Radar Signal Processing, Xidian University, Xi&rsquo

Funds: 

The National Natural Science Foundation of China (61271291, 61201285)

  • 摘要: 針對寬帶雷達(dá)目標(biāo)回波存在越距離單元走動的問題，該文提出一種基于聯(lián)合稀疏恢復(fù)的寬帶雷達(dá)動目標(biāo)檢測方法。該方法先在頻域?qū)夭〝?shù)據(jù)進(jìn)行預(yù)白化處理，抑制雜波；然后在頻率-慢時(shí)間域推導(dǎo)出目標(biāo)信號的聯(lián)合行稀疏表示，并通過聯(lián)合稀疏恢復(fù)算法得到目標(biāo)的頻域估計(jì)；最后通過逆傅里葉變換得到目標(biāo)的時(shí)域估計(jì)。仿真結(jié)果驗(yàn)證了該方法的有效性。
    Abstract: Range migration is the basic and troublesome problem in moving target detection for wideband radar. To solve this problem, a detection algorithm of moving targets based on joint-sparse recovery is proposed for wideband radar. Firstly, a prewhitening processing is performed to filter the clutter. Then, a jointly row sparse representation of the wideband signals is derived in frequency/slow-time domain，thus the detection problem is solved via joint-sparse recovery. Finally, by using the inverse Fourier transform, the estimation of the targets scenario is achieved. Numerical results are presented to demonstrate the effectiveness of the proposed algorithm.
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出版歷程
  • 收稿日期:  2015-04-20
  • 修回日期:  2015-07-13
  • 刊出日期:  2015-12-19

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