Joint Doppler and time delay estimation by compressed sampling

Abstract

Joint Doppler shift and time delay estimation is an important topic in radar, sonar and communication applications. Least square (LS) is a classical and effective method for solving the problem. However, the performance degrades severely in the scenario of low ratio of signal-noise (SNR), due to the instability of matrix inversing. In this paper, a high-resolution method is proposed basing on the compressive sampling theory. The 2-dimension channel response can be sparsely recovered, and high-resolution Doppler shift-time delay estimation can be described with an underdetermined equation solving problem. Three categories of algorithms, including diagonal loading least squares, l1 Regularization, and Greedy Pursuit, are adopt to solve the problem and show outstanding resolving capabilities. The three categories of algorithms are analyzed and compared in different conditions. For the dictionary appears not to have unit norm columns, Greedy pursuit is not good as l1 Regularization in general, and simulation ...