Simultaneous localization and tracking with belief propagation and particle swarm optimization

Simultaneous localization and tracking (SLAT) is known to significantly affect the geometric random deployment of wireless sensor networks (WSN). In this letter, we describe how a completely decentralized version of particle filter for SLAT algorithm can be implemented in the relative coordination for target state through belief propagation of suitable messages that are exchanged between neighbouring sensors, at the same time, a particle swarm optimization for unknown sensor localization parameter estimation is proposed with the celebrated target position to modify the sensor deployment even in non-line-of-sight (NLOS) environment. This algorithm is applied to solve the geometric placement for sensor networks.