Indoor Positioning System Based on Improved Kalman Filter

With the increasingly complex indoor environment nowadays, people still have high requirements for indoor positioning accuracy. Indoor positioning errors are mainly caused by signal band interference and non-line-of-sight. In the face of frequency band interference, this paper chose Ultra-Wide-Band signal as the positioning basis. Deal with the non-line-of-sight, this paper proposed an indoor positioning system based on improved Kalman filter, which reduces the new error caused by Kalman filter in complex scene conversion and improves the positioning accuracy. The system used five or more base stations for positioning, and selected the CHAN algorithm, which is sensitive to positioning errors, to solve the initial position. Residual processing was performed on the initial position and the positions of each base station to generate a credible factor, and then different confidence regions were divided according to the factor. For different confidence regions, the Kalman filter gain coefficient K was pre-set to improve the stability of the positioning results for frequent transitions between line-of-sight and non-line-of-sight scenes. The experimental results show that the system can reduce the error to 80cm in the simulation environment. And in actual scenes, it can reduce to 60cm.