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 costreference 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.