Road-constraint assisted target tracking in mixed LOS/NLOS environments based on TDOA measurements

Abstract

This paper proposes an approach to improving the target tracking accuracy in mixed line-of-sight/non-line-of-sight (LOS/NLOS) environments based on individual measurement detection (IMD) and road constraints. Utilizing the IMD algorithm, most LOS time-difference-of-arrival (TDOA) measurements can be correctly selected from mixed LOS/NLOS TDOA measurements. Incorporating the prior knowledge of the road constraint as a pseudo-measurement, the augmented dynamic extended Kalman filter (EKF) is then implemented to track a moving target. Simulation results demonstrate that the road constraint assisted algorithm, in conjunction with the IMD method, performs better than the road constraint assisted algorithm without the IMD method, or tracking algorithm with the IMD method but without the road constraint. The proposed method is especially useful when the number of selected LOS TDOA measurements is less than three.