Target tracking with line-of-sight identification in sensor networks under unknown measurement noises

Tracking a target is a fundamental and crucial problem in wireless sensor networks. It is well known that non-line-of-sight (NLOS) propagation will significantly degrade the tracking accuracy if its effects are ignored. In this paper, a line-of-sight (LOS) identification approach for range-based tracking systems is developed to discard the NLOS measurements. Based on L_p-norm LOS identification strategy, a novel target tracking method is devised with the use of cost-reference particle filter, which does not require the knowledge of the measurement noise distribution. Computer simulations are included to verify the effectiveness of the proposed approach under different noise distributions.