Location and tracking algorithm based on two-step Kalman filter in NLOS environments

Concerning the problems that Non-Line-Of-Sight (NLOS) error affects the location accuracy in cellular wireless location systems, a location and tracking algorithm based on the two-step Kalman filter algorithm was proposed. The algorithm first used the mean value of new information which was produced in the Kalman filter iteration process to identify and to eliminate the NLOS error, and then got the reconstructed measurements. Then the Kalman filter system noise covariance was improved and adjusted adaptively. The simulation results show that the proposed algorithm can mitigate NLOS error greatly, improve location accuracy in NLOS environments and obtain better location effect, which is much better than the classic EKF.