On application of OMP and CoSaMP algorithms for DOA estimation problem
On application of OMP and CoSaMP algorithms for DOA estimation problem
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OMP和CoSaMP算法在DOA估计问题中的应用
DOI：
10.1109/iccsp.2017.8286749
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
P. Palanisamy
中科院分区：
文献类型：
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作者：
Abhishek Aich;P. Palanisamy
压缩传感（CS）的显着特性导致研究人员在需要解决线性方程式不确定系统的其他各个领域中利用它。一个这样的应用是在数组信号处理的区域中，例如在信号降解和到达方向（DOA）估计中。从CS恢复算法的两个突出类别中，即凸优化算法和贪婪的稀疏近似算法，我们研究了贪婪的稀疏近似算法在均匀线性阵列（ULA）环境中估算DOA的应用。我们对两种最先进的贪婪算法的行为进行实证研究：OMP和COSAMP。这项调查考虑了各种情况，例如不同程度的噪声水平和来源之间的相干性。我们执行模拟以证明这些算法的性能，并简要分析结果。
Remarkable properties of Compressed sensing (CS) has led researchers to utilize it in various other fields where a solution to an underdetermined system of linear equations is needed. One such application is in the area of array signal processing e.g. in signal denoising and Direction of Arrival (DOA) estimation. From the two prominent categories of CS recovery algorithms, namely convex optimization algorithms and greedy sparse approximation algorithms, we investigate the application of greedy sparse approximation algorithms to estimate DOA in the uniform linear array (ULA) environment. We conduct an empirical investigation into the behavior of the two state-of-the-art greedy algorithms: OMP and CoSaMP. This investigation takes into account the various scenarios such as varying degrees of noise level and coherency between the sources. We perform simulation to demonstrate the performances of these algorithms and give a brief analysis of the results.