| Abstract: | To detect message collisions in multichannel spaced‐based automatic identification system (AIS), a dynamic complex symmetric fast independent component analysis (CSFICA) and feature‐based collision detection method is proposed in this paper. A fast and stable blind source separation algorithm, dynamic CSFICA, is utilized to separate signals dynamically and improve the signal‐to‐interference ratio (SIR) in each channel. A frequency and phase offset insensitive feature detection algorithm is used to calculate the test statistics in each channel. The false alarm is suppressed by applying the arithmetic to geometric mean (AGM) method, and test statistics of channels with sufficient signal quality are extracted to detect the preamble. Simulation results show that the proposed algorithm outperforms the reference feature detection algorithm under collision conditions and is insensitive to the SIR. The proposed algorithm is more resistant to false alarm caused by signal (FAS) than the differential correlation (DC) algorithm. |
