A separation algorithm for satellite-based AIS received signals based on SSA and RobustICA

Objectives In high-density traffic areas, the automatic identification system (AIS) signals of ships collision often occurs, so the separation performance and real-time performance of the receiver are put forward high requirements.

Methods For mixed signals with different signal-to-noise ratios(SNR), a separation algorithm S-RICA based on singular spectrum analysis(SSA) and robust independent component analysis (RobustICA) is proposed.The Hankel matrix of single-channel AIS signal was processed by singular value decomposition and reconstructed by time series respectively, SSA was used to replace whitening pre-processing in traditional independent component analysis (ICA), and the optimal step size of each iteration of the separation matrix was calculated by using kurtosis contrast function to quickly obtain the optimal separation matrix.

Results The simulation results show that the SMSE value of S-RICA is stable at about 1.5 when the signal length changes, while the SMSE of fast independent component analysis（FastICA） is very unstable. S-RICA has a bit error rate of 0.97 \times 10⁻² to 1.97 \times 10⁻² at a signal-to-noise ratio (SNR) of 0-9 dB, an order of magnitude improvement over RobustICA and FastICA, and an improvement of 4-6 dB over S-FICA at a SNR of 0-7 dB. The average calculation time and number of iterations of S-RICA are about 18.5 ms and 13.6 times, respectively, showing obvious advantages.

Conclusions When the sample size and SNR change, S-RICA can show better separation performance. The research has certain reference value for the application of S-RICA in the future satellite-based AIS system.