Passive Target Localization in Non-Line-of-Sight Environments

In this paper, the problem of passive target localization based on Time-of-Arrival (TOA) in Non-Line-of-Sight (NLOS) environments is addressed. Considering the difficulties of acquiring a priori information on the distribution of NLOS errors in practice, we assume that there is no priori information of NLOS errors. Due to the complexity of signal prorogation model in passive target scenarios and the absence of priori information of NLOS errors, the target localization becomes very challenging. Fortunately, based on the NLOS mitigation method, the passive target localization problem can be solved efficiently via semi-definite programming (SDP). Moreover, inspired by the active localization methods, Min-Max algorithm (MMA) and Quadratic Programming (QP) are successfully extended to solve our passive target localization with NLOS errors. The simulation results reveal the effectiveness of the NLOS mitigation method and low computational complexity of MMA and QP methods.