基于空域平滑稀疏重构的DOA估计算法

蔡晶晶; 宗汝; 蔡辉

doi:10.11999/JEIT150538

基于空域平滑稀疏重构的DOA估计算法

doi: 10.11999/JEIT150538

1.
(西安电子科技大学电子工程学院西安 710071) ②(中国人民解放军95037部队武汉 430074)

基金项目:

国家自然科学基金(61405150, 61271300), 中央高校基本科研业务费专项资金(JB140229)

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- 文章访问数: 1467
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- 被引次数: 0
出版历程
- 收稿日期: 2015-05-07
- 修回日期: 2015-07-08
- 刊出日期: 2016-01-19

DOA Estimation Via Sparse Representation of theSmoothed Array Covariance Matrix

Funds:

The National Natural Science Foundation of China (61405150, 61271300), The Fundamental Research Funds for the Central Universities (JB140229)

摘要

摘要: 该文提出一种基于空域平滑稀疏重构的DOA估计算法，利用空域平滑理论对协方差矩阵进行处理，然后通过KR积变换改变其结构，并对变换后的矩阵进行稀疏重构获得角度估计。此外，该文还给出了两种不同的目标函数误差求解方法。从仿真实验可以看出，该算法与传统的基于压缩感知理论的DOA估计算法对比，明显降低了运算量，且对于相干和非相干信号的处理性能均有所提高，在低角度间隔、低信噪比和低采样数条件下优势更为突出。
- 压缩感知 /
- 空域平滑 /
- 稀疏重构 /
- DOA估计
Abstract: A novel Direction-Of-Arrival (DOA) estimation algorithm based on spatial smoothing and sparse reconstruction is proposed in this paper. Firstly, the covariance matrix is processed using spatial smoothing theory, and it is converted with the Khatri-Rao transformation, then DOA estimation is achieved by sparse reconstruction of the converted matrix. Furthermore, two different kinds of methods are given to deal with the error of the objective function. Experimental results show that the proposed algorithm can reduce the amount of computation, and exhibit better performance on both coherent and non-coherent signals compared with the other DOA algorithms based on compressed sensing, especially under the conditions of low angle interval, low signal-to-noise ratio and low sampling number.
- Compressed sensing /
- Spatial smoothing /
- Sparse reconstruction /
- DOA estimation

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参考文献(18)

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