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Remarkable properties of Compressed sensing (CS) has led researchers toutilize it in various other fields where a solution to an underdeterminedsystem of linear equations is needed. One such application is in the area ofarray signal processing e.g. in signal denoising and Direction of Arrival (DOA)estimation. From the two prominent categories of CS recovery algorithms, namelyconvex optimization algorithms and greedy sparse approximation algorithms, weinvestigate the application of greedy sparse approximation algorithms toestimate DOA in the uniform linear array (ULA) environment. We conduct anempirical investigation into the behavior of the two state-of-the-art greedyalgorithms: OMP and CoSaMP. This investigation takes into account the variousscenarios such as varying degrees of noise level and coherency between thesources. We perform simulations to demonstrate the performances of thesealgorithms and give a brief analysis of the results.

On application of OMP and CoSaMP algorithms for DOA estimation problem