Improved particle filter algorithms for target tracking in binary wireless sensor network

Particle filter algorithm with adaptive process noise variance is proposed for target tracking applications in binary wireless sensor network (BWSN). The algorithm adopts updated variance of system noise to eliminate the cumulative effect of particle filter prediction error. It has better tracking accuracy when target travel with constant velocity or variable velocity. The simulation results show that the algorithm is superior to the standard particle filter.