A Sparse Decomposition-Based Algorithm for Estimating the Parameters of Polynomial Phase Signals

In this paper, we propose an algorithm in which fast sparse decomposition is used to estimate the polynomial phase signal (PPS) parameters. In the proposed algorithm, a fast sparse decomposition is applied to the second-order PPSs, which outperforms three other algorithms in decomposition rate and convergence. The proposed algorithm also estimates the PPS parameters more accurately than other sparse decomposition algorithms. For PPSs whose order exceeds two, the order can be reduced to two via phase differentiation, after which parameters can be estimated using fast sparse decomposition. The simulation results show that the proposed algorithm is characterized by a lower signal-to-noise ratio and higher estimation accuracy than high-order ambiguity function and other recently proposed algorithms.