An improved Kalman filter positioning method in NLOS environment

Abstract

In the precision positioning system, NLOS (Non Line of Sight) propagation and clock synchronization error caused by multiple base stations are the main reasons for reducing the reliability of communication and positioning accuracy. So, in the NLOS environment, it has an important role to eliminate the clock synchronization problem in the positioning system. In order to solve this problem, this paper proposes an improved Kalman filter localization method NLOS-K (Non Line of Sight-Kalman filter). First, the maximum likelihood estimation algorithm is used to iterate. Then, the Kalman filter algorithm is implemented and the Kalman gain matrix is redefined. The clock drift is compensated so that the clock between the master and slave base stations remains synchronized. The experimental results show that in the non-line-of-sight environment, compared with other algorithms, the positioning accuracy error of the improved algorithm is about 5 cm, and the accuracy compared with other algorithms is 97%. In addition, the influence of bandwidth and spectral density on the method is analyzed, and the accuracy and stability of positioning are improved as a whole.