基于平面阵列的相干光源到达方向估计的矩阵重构

Hao Zhang, D. Zhen, Fang Zeng, Guojin Feng, Zhaozong Meng, F. Gu
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引用次数: 0

摘要

多信号分类(MUSIC)算法已成为空间频谱估计理论体系中具有里程碑意义的算法。该技术具有良好的估计性能和广阔的应用前景。准确的DOA估计在窄波源探测中起着至关重要的作用。然而,当信号部分相关甚至相干时,传统MUSIC算法的性能会大大降低。提出了空间平滑和Toeplitz矩阵重构等方法来实现MUSIC算法的去相干和最小化DOA估计误差。然而,这些方法只能应用于均匀线性阵列,这大大降低了算法的实用性。本文提出将消相干法与MUSIC算法相结合,在由两个正交最小冗余线阵(MRLA)组成的平面阵列中估计源的方位角(θ)和仰角(φ)。在不同信噪比下实现了该算法,并与其他去相干方法进行了比较。仿真结果表明,所提出的消相干算法能够达到较高的相干源DOA估计精度。
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Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array
The Multiple Signal Classification (MUSIC) algorithm has become a landmark algorithm in the theoretical system of spatial spectrum estimation. This technology has excellent estimation performance and wide application prospects. Accurate Direction of Arrival (DOA) estimation plays a pivotal role in the detection of narrow wave sources. Nevertheless, when the signals are partially correlated or even coherent, the performance of the traditional MUSIC algorithm is greatly reduced. Methods such as spatial smoothing and Toeplitz matrix reconstruction have been proposed to decoherence and minimize the DOA estimation error in the MUSIC algorithm. However, these methods can only be applied to uniform linear arrays, which greatly reduces the practicability of the algorithm. This paper proposes to combine a decoherence method with MUSIC algorithm to estimate the azimuth angle (θ) and elevation angle (φ) of the source in a planar array which is composed of two orthogonal minimum redundant linear arrays (MRLA). The algorithm is implemented under different Signal-to-Noise Ratio (SNR) and compared with other decoherence methods. Simulation results show the proposed decoherence algorithm can achieve higher DOA estimation accuracy for coherent sources.
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