To achieve frequency and direction-of-arrival(DOA)estimation for coherent dense signals,a dimensionality-reduced sparse dictionary is constructed by substituting the reference frequency for the actual frequency.Utilizing the theory of compressed sensing,the joint estimation of frequency and direction-of-arrival is realized.Additionally,an SVD-optimized method is proposed for complex scenes involving low signal-to-noise ratio,few snapshots,and coherent signals.Simulations reveal that the algorithm proposed in this paper and its optimized version can accurately estimate the frequency and DOA of dense coherent signals.Com-pared to the original algorithm,the optimized algorithm improves performance under low signal-to-noise ratio conditions,more suit-able for the scene of low signal-to-noise ratio and less snapshots.
维普
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