Simulation of Indoor Pseudolite Positioning Accuracy Based on EKF

This paper proposes an ergodic robust Kalman filter(ERKF) algorithm to improve the positioning accuracy of pseudo-satellite. This algorithm will look for and compare all the threshold independently in the given range, choose the one that is most suitable for the measurement environment as the threshold of the algorithm, then bring it into the ERKF model, ERKF finally gets the filtered data. Emulations by Matlab were performed, and the results show that after ERKF, the average standard deviations of X-axis, Y-axis and X-Y plane have reduced by 0.9126m, 1.323m and 7.9161m. This paper also compares the filtering performance of ERKF with that of ordinary Kalman filter(KF), and the results show that ERKF has higher accuracy and stability. The ERKF presented in this paper can effectively improve the accuracy of indoor pseudo-satellite system.