An Improved FastICA Algorithm Based on Modified-M Estimate Function

In order to improve the detection rate of ship information, fast independent component analysis (FastICA) algorithm is adopted to separate satellite-based automatic identification system (AIS) mixed signals. FastICA algorithm has the advantages of fast convergence rate and simple form. However, it is sensitive to the initialization of the separation matrix and the robust performance is poor. Aimed at the problem, an improved FastICA algorithm is proposed. This new algorithm is based on constant model of AIS signal and chooses Modified-M estimation function as nonlinear function so as to improve the robustness of algorithm. The improved algorithm also modifies Newton iterative algorithm. The experimental simulation results indicate that the proposed method reduces the iteration times and the accuracy has been improved.