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首页> 外文期刊>International journal of antennas and propagation >Fast DOA Estimation Based on the Transform Domain Weighted Noise Subspace Fitting Algorithm for Generalized Sparse Array
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Fast DOA Estimation Based on the Transform Domain Weighted Noise Subspace Fitting Algorithm for Generalized Sparse Array

机译：基于变换域加权噪声子空间拟合算法的快速DOA估计广义稀疏阵列

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摘要

Compared with uniform arrays, a generalized sparse array (GSA) can obtain larger array aperture because of its larger element spacing, which improves the accuracy of DOA estimation. At present, most DOA estimation algorithms are only suitable for the uniform arrays, while a few DOA estimate algorithms that can be applied to the GSA are unsatisfactory in terms of computational speed and accuracy. To compensate this deficiency, an improved DOA estimation algorithm which can be applied to the GSA is proposed in this paper. First, the received signal model of the GSA is established. Then, a fast DOA estimation method is derived by combining the weighted noise subspace algorithm (WNSF) with the concept of “transform domain” (TD). Theoretical analysis and simulation results show that compared with the traditional multiple signal classification (MUSIC) algorithm and the traditional WNSF algorithm, the proposed algorithm has higher accuracy and lower computational complexity.
机译：与均匀阵列相比，由于其较大的元件间隔，通常可以获得更大的阵列孔径，这提高了DOA估计的精度。 目前，大多数DOA估计算法仅适用于统一阵列，而可以应用于GSA的几个DOA估计算法在计算速度和准确性方面是不令人满意的。 为了补偿这种缺陷，本文提出了一种可以应用于GSA的改进的DOA估计算法。 首先，建立GSA的接收信号模型。 然后，通过将加权噪声子空间算法（WNSF）与“变换域”（TD）的概念组合来导出快速DOA估计方法。 理论分析和仿真结果表明，与传统的多信号分类（音乐）算法和传统的WNSF算法相比，所提出的算法具有更高的准确性和较低的计算复杂性。

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