NLOS error mitigation in mobile location based on TOA reconstruction

In order to improve accuracy and reliability of wireless location in the mixed line-of-sight (LOS) and non-line-of-sight (NLOS) environment, a real-time NLOS identification and LOS reconstruction algorithm in connection with the positive characteristic of the NLOS error are presented to estimate the position of a mobile station (MS). A Kalman filter (KF) based on innovation vectors is utilized to identify the change of the measured value between NLOS and LOS, which is a real-time identification. According to the positive deviation can be as a part of the NLOS error, the original estimation curve by moving down will be nearly to the true curve, where the LOS reconstructed measurement can be obtained. Computer simulation results show that the location error of the proposed algorithm is significantly smaller in comparison with those of the conventional extended Kalman filter (EKF) algorithm and the Wylie algorithm. Moreover, the experiments suggest that this algorithm supports real-time applications.