An intelligent IMM-REKF algorithm for mobile tracking in probabilistic NLOS environments

This paper deals with mobile localization in environments with probabilistic occurrences of non-line-of-sight (NLOS) errors. We introduce the construction of validated measurement regions using real-time LOS-assisted information. To ameliorate both NLOS errors and mobility variations of a mobile target, we propose an intelligent robust extended-Kalman filter-based interacting multiple-model (intelligent IMM-REKF). The proposed approach is distinct from other existing methods. Simulation results illustrate the superior performance of the proposed algorithm under various NLOS occurrence probabilities.