Joint Doppler shift and time delay estimation by deconvolution of generalized matched filter

Abstract Resolution probability is the most important indicator for signal parameter estimator, including estimating time delay, and joint Doppler shift delay. In order to get high-resolution probability, some procedures have been suggested such as compressed sensing. Based on signal’s sparsity, sensing has used estimate parameters in recent research. After solving ? 0 norm Optimization problem, methods would achieve high resolution. These all require SNR. improve performance low SNR, a novel implementation proposed this paper. We give sparsity representation generalized matched filter output, or ambiguity function, while former utilized channel response domain. By deconvolving 2-dimension estimation delay be gotten by greedy method, optimization method based relaxation, Bayesian method. Simulation demonstrates our better SNR than representation.