基于極化敏感陣列均勻線陣的二維DOA估計(jì)
doi: 10.11999/JEIT180832 cstr: 32379.14.JEIT180832
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哈爾濱工程大學(xué)信息與通信工程學(xué)院 ??哈爾濱 ??150001
基金項(xiàng)目: 國家自然科學(xué)基金(61571146)，中央高?；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金(HEUCFP201769)
Two Dimensional DOA Estimation Based on Polarization Sensitive Array and Uniform Linear Array
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College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
Funds: The National Natural Science Foundation of China (61571146), The Fundamental Research Funds for the Central Universities (HEUCFP201769)
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摘要: 針對(duì)殘缺電磁矢量傳感器的極化敏感陣列多參數(shù)聯(lián)合估計(jì)問題，該文提出一種基于正交偶極子的均勻線陣的2維波達(dá)方向(Direction-Of-Arrival, DOA)估計(jì)算法。首先，對(duì)極化敏感陣列的接收數(shù)據(jù)矢量的協(xié)方差矩陣進(jìn)行特征分解，然后將信號(hào)子空間劃分成4個(gè)子陣，根據(jù)旋轉(zhuǎn)不變子空間(ESPRIT)算法分別求出其中1個(gè)子陣與其它3個(gè)子陣的相位差，再對(duì)不同子陣間的相位差進(jìn)行配對(duì)，最后根據(jù)相位差求出信號(hào)的DOA估計(jì)和極化參數(shù)。由正交偶極子組成的均勻線陣使用極化MUSIC算法和傳統(tǒng)ESPRIT算法無法進(jìn)行2維DOA估計(jì)，該文提出的算法解決了這個(gè)問題，并且相較于極化MUISC算法降低了算法的復(fù)雜度。仿真結(jié)果驗(yàn)證了該文算法的有效性。Abstract: To solve the problem that polarization sensitive array of defective electromagnetic vector sensor estimate multi parameter, a two-dimensional DOA estimation algorithm based on orthogonal dipole is proposed in this paper. First, eigendecomposition of the covariance matrix is produced by the received data vectors of the polarization sensitive array. Then the signal subspace is divided into four subarrays, and the phase difference between one of the subarray and the others is obtained according to the ESPRIT algorithm. Then the phase difference between different subarrays is paired. Finally, the DOA estimation and polarization parameters of the signal are calculated according to the phase difference. The uniform linear array composed by orthogonal dipoles can not be two-dimensional DOA estimated by using the MUSIC algorithm and the traditional ESPRIT algorithm. The algorithm proposed in this paper solves this problem, and compared with the polarization MUISC algorithm greatly reduces the complexity of the algorithm. The simulation results verify the effectiveness of the proposed algorithm.
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表 1 方位角的判別方法
$\sin \theta \sin \phi > 0$ $\sin \theta \sin \phi < 0$ $\tan \theta > 0$ 第1象限 第3象限 $\tan \theta < 0$ 第2象限 第4象限 
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表 2 本文算法的仿真結(jié)果(°)
方位角 俯仰角 極化幅角 極化相位角 實(shí)際值 估計(jì)值 實(shí)際值 估計(jì)值 實(shí)際值 估計(jì)值 實(shí)際值 估計(jì)值 信號(hào)1 60.00 60.17 10.00 9.92 10.00 10.06 130.00 130.10 信號(hào)2 150.00 150.00 20.00 20.13 20.00 19.83 60.00 59.68 信號(hào)3 220.00 220.00 30.00 29.99 30.00 30.01 300.00 300.00
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