A Kalman Filter-Based Blind Adaptive Multi-User Detection Algorithm for Underwater Acoustic Networks

An underwater acoustic Kalman filter-based blind adaptive multi-user detection algorithm, suitable for underwater acoustic communication networks, is proposed in this paper. The algorithm can be employed to effectively improve the system capacity of multi-user communication in underwater acoustic sensor networks, reduce transmitting power and costs on power control, extend the multi-user communication distance, weaken or eliminate intersymbol interference, multiple access interference and near-far effect, thus effectively utilizing limited underwater frequency band resource. First, the dynamic model of underwater acoustic multi-user communication system and the optimal filter equation of the proposed algorithm are found. Second, computation complexity is analyzed, and convergence analysis is carried out in terms of excess mean output energy. Finally, pool, river, sea, and under-ice asynchronous communication experiments have been carried out for both the scalar and the vector hydrophones. Good experimental results verify the effectiveness of the proposed algorithm.