PROJECT TITLE :

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

ABSTRACT:

An underwater acoustic Kalman filter-based mostly blind adaptive multi-user detection algorithm, appropriate for underwater acoustic communication networks, is proposed in this paper. The algorithm will be utilized to effectively improve the system capability of multi-user communication in underwater acoustic sensor networks, scale back transmitting power and prices on power control, extend the multi-user communication distance, weaken or eliminate intersymbol interference, multiple access interference and close to-way result, so effectively utilizing restricted underwater frequency band resource. 1st, the dynamic model of underwater acoustic multi-user communication system and also the optimal filter equation of the proposed algorithm are found. Second, computation complexity is analyzed, and convergence analysis is administrated in terms of excess mean output energy. Finally, pool, river, sea, and underneath-ice asynchronous communication experiments are applied for both the scalar and also the vector hydrophones. Good experimental results verify the effectiveness of the proposed algorithm.