Distributed Target Tracking in UWSNs Under Stochastic Node Communication Scheme

This article deals with the problem of saving network energy in the field of distributed target tracking in underwater wireless sensor networks (UWSNs). Specifically, a modified distributed extended Kalman filter (DEKF) is proposed for distributed target tracking. To reduce the energy cost during the tracking process, the stochastic node communication scheme is introduced, where each node communicates with its neighboring sensors according to certain probabilities. By minimizing the estimation error, the optimal filter gain with stochastic node communications is derived. Considering the fact that the calculations of cross-covariance and the estimation of compensation matrix are impractical in UWSNs, a suboptimal Kalman gain is derived by matrix scaling. In addition, the estimation error of the modified DEKF is proved to be exponentially bounded in mean square. Finally, simulations and real-world experiments are carried out to reveal the effectiveness of the proposed algorithm.