雷達(dá)高分辨率緊湊感知矩陣追蹤算法

劉靜; 盛明星; 宋大偉; 尚社; 韓崇昭

doi:10.11999/JEIT151135

雷達(dá)高分辨率緊湊感知矩陣追蹤算法

doi: 10.11999/JEIT151135

1.
(西安交通大學(xué)電信學(xué)院西安 710049) ②(空間微波技術(shù)國(guó)家級(jí)重點(diǎn)實(shí)驗(yàn)室西安 710000)

基金項(xiàng)目:

CAST創(chuàng)新基金(J20141110)，國(guó)家自然科學(xué)基金(61573276)，國(guó)家973計(jì)劃(2013CB329405)

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- 文章訪問(wèn)數(shù): 1324
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出版歷程
- 收稿日期: 2015-10-10
- 修回日期: 2016-04-22
- 刊出日期: 2016-08-19

Compact Sensing Matrix Pursuit Algorithm for Radars with High Resolution

1.
(School of Electronics and Information Engineering, Xi&rsquo
2.
(National Key Laboratory of Science and Technology on Space Microwave, Xi&rsquo

Funds:

The Innovation Foundation of CAST (J20141110), The National Natural Science Foundation of China (61573276), The National 973 Program of China (2013CB329405)

摘要

摘要: 針對(duì)壓縮感知雷達(dá)的感知矩陣相干系數(shù)隨分辨率增加而增大以致不能以大概率對(duì)稀疏向量進(jìn)行完美重構(gòu)的問(wèn)題，直接基于原始感知矩陣，提出緊湊感知矩陣追蹤(CSMP)算法。該文將CSMP算法應(yīng)用于十字陣?yán)走_(dá)的2維波達(dá)方向(DOA)估計(jì)并進(jìn)行了計(jì)算機(jī)仿真。仿真結(jié)果表明與多信號(hào)分類(lèi)(MUSIC)算法，子空間追蹤(SP)算法，基追蹤(BP)算法和稀疏貝葉斯學(xué)習(xí)(SBL)算法相比，基于CSMP算法的DOA估計(jì)分辨率得到了較大提高。
- 壓縮感知雷達(dá)系統(tǒng) /
- 高分辨率 /
- 高相關(guān)性 /
- 緊湊感知矩陣追蹤算法
Abstract: In this paper, a novel algorithm named Compact Sensing Matrix Pursuit (CSMP) is proposed to deal with the high coherence problem encountered in the compressed sensing based radar system with high resolution. The CSMP algorithm is applied to the two dimensional Direction Of Arrival (DOA) estimation of cross-array. The simulation results show that the resolution can be increased largely compared with the MUltiple SIgnal Classification (MUSIC) algorithm, Subspace Pursuit (SP), Basis Pursuit (BP), and the Sparse Bayesian Learning (SBL) algorithms.
- Compressive sensing based radar system /
- High resolution /
- High coherence /
- Compact Sensing Matrix Pursuit (CSMP) algorithm

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參考文獻(xiàn)(20)

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