Title: Radar Signal Denoising Via Adaptive Iterative Sparsity Decomposition
Abstract:Sparse decomposition is effective in separating signal and noise,and it can be used to remove noise.In this paper,a redundancy match dictionary is designed for radar echo signal sparse representation,...Sparse decomposition is effective in separating signal and noise,and it can be used to remove noise.In this paper,a redundancy match dictionary is designed for radar echo signal sparse representation,and the signal sparsity is equal to the detecting target number.As the stop threshold of the sparsity adaptive matching pursuit(SAMP) algorithm is not applicable for sparse decomposition in low signal-to-noise ratio(SNR) conditions,the iteration adaptive matching pursuit(LAMP) algorithm is proposed u- sing normalized residual difference as stop condition,making sparse decomposition adaptively stop according to noise level.Signal sparsity estimation is implemented by way of successive approximation,and much improvement on decomposition accuracy is obtained. Extensive simulation results show that the IAMP algorithm is effective in radar echo signal sparse decomposition in low SNR conditions without sparsity information,and the SNR of sparse decomposition signal is largely improved.Read More
Publication Year: 2013
Publication Date: 2013-01-01
Language: en
Type: article
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