TOA Mine Personnel Location Method based on Improved Wavelet - Kalman Filter

Abstract

In view of the complex environment of mine roadways and the large number of equipment, which may cause the Time delay of electromagnetic wave NLOS(Non Line of Sight) and affect the positioning accuracy of mine TOA(Time of Arrival), a TOA mine personnel positioning method based on improved wavelet-kalman filtering was proposed. First of all, a symmetrical two-channel ranging method (SDS-TWR) is adopted to eliminate the influence of synchronization delay and timing error on TOA positioning accuracy. Secondly, Three-layer decomposition of data through db1, db5 wavelet, and the decomposed data is reconstructed after threshold quantization. Finally, the improved kalman filter is used to filter the pulse noise from the wavelet data. The simulation results show that the average error of the method proposed in this paper is 1.3m. Compared with the SDS-TWR method and the kalman filter algorithm based on the innovation threshold, the average positioning error is reduced by 2.4m and 1.1m respectively, which verifies the effectiveness of the positioning performance of this method.