期刊名称：EURASIP Journal on Advances in Signal Processing
印刷版ISSN：1687-6172
电子版ISSN：1687-6180
出版年度：2021
卷号：2021
期号：1
页码：1
DOI：10.1186/s13634-021-00741-7
出版社：Hindawi Publishing Corporation
摘要：Resolution probability is the most important indicator for signal parameter estimator, including estimating time delay, and joint Doppler shift and time delay. In order to get high-resolution probability, some procedures have been suggested such as compressed sensing. Based on the signal’s sparsity, compressed sensing has been used to estimate signal parameters in recent research. After solving ℓ0 norm Optimization problem, the methods would achieve high resolution. These methods all require high SNR. In order to improve the performance in low SNR, a novel implementation is proposed in this paper. We give a sparsity representation for the generalized matched filter output, or ambiguity function, while the former methods utilized the sparsity representation for channel response in time domain. By deconvolving the generalized matched filter output, 2-dimension estimation for Doppler shift and time delay would be gotten by greedy method, optimization method based on relaxation, or Bayesian method. Simulation demonstrates our method has better performance in low SNR than the method by the channel sparsity representation.
关键词：Compressed sensing ; Matched filter ; Ambiguity function ; Time delay estimation ; Deconvolution
