TOA-based cooperative localization for mobile stations with NLOS mitigation

This paper studies the problem of cooperative localization for mobile stations in a mixed line-of-sight (LOS) and non-line-of-sight (NLOS) environment. A two-state Markov chain is used to represent the switching behavior of the LOS/NLOS time-of-arrival (TOA) measurements so that the cooperative localization problem can be cast into the state estimation for a class of jump Markov nonlinear system with multiple switching parameters. A multi-sensor multi-model filter has been developed by applying the interacting multiple model (IMM) approach and the extended Kalman filter (EKF) technique, in which all the anchor sensor measurements and the cooperative measurements are handled sequentially instead of the centralized fashion. To overcome the difficulty of lacking the actual positions of the mobile stations in the cooperative measurements, the position estimates derived by the anchor sensor measurements are communicated to generate the predicted cooperative measurements in the EKF. A numerical example is provided involving localization of three mobile stations and simulation results show a promising performance for the proposed filter.