An UWB location algorithm for indoor NLOS environment

摘要

In the UWB indoor wireless positioning system, to solve the problem of the NLOS error caused by the complex indoor environment and the changeable obstacles makes the positioning precision reduced. This paper uses ranging residuals to identify NLOS error, Kalman Filter is performed on the range of the LOS environment, Bias Kalman Filter based on ranging residuals compensation is performed in NLOS environment, if the ranging residuals compensation caused by some NLOS error mutations failed to reach the threshold value, according to the redundant range value after compensation, which adjusts the gain of Bias Kalman Filter automatically to reconstruct the range of LOS environment further. Least Square algorithm and Sliding Window Filter are used to calculate coordinate and smooth trajectory, experimental results show that the algorithm can effectively reduce the effect of NLOS error on location. The error of static positioning of 95% probability is not less than 0. 075m, the maximum positioning error is no more than 0. 082m, and the accuracy of dynamic positioning can be stabilized within 0. 26m, which satisfies the needs of most indoor locations.