In the harsh working environment of mines, the traditional cable reeling method cannot guarantee the power supply of electric shovel for a long time, and there are hidden safety hazards in the process of power supply. A new cable reel car which follows the shovel is proposed to address the above problems. In order to realize the autonomous following of electric shovel by cable reel car and ensure the long time power supply of electric shovel in mining environment, the positioning algorithm of electric mine shovel based on ultra wide-band (UWB) technology is proposed and time difference of arrival (TDOA) algorithm is used to construct the positioning model of electric mine shovel. Based on the TDOA ranging algorithm, the distance from each base station to the target electric shovel position is measured and the difference is calculated. The distance difference information obtained is moving average filtered to suppress the noise generated in the ranging process and achieve smooth data. The tag position is calculated according to the distance difference after filtering correction. The target electric shovel position is tracked with the strong tracking extended Kalman filter (STFEKF) algorithm to further eliminate noise and improve the positioning accuracy of the target electric shovel during movement. The simulation results show that under the influence of different observation noises, the error of the moving filter + STFEKF positioning method is smaller than that of the traditional EKF algorithm. This method effectively solves the problem of positioning error increasing with the distance increasing or the sudden change of shovel movement. The positioning mean square deviation is reduced by more than 70% compared with the traditional EKF algorithm, and the positioning trajectory is closer to the real movement trajectory of the target with good performance of positioning tracking and noise suppression.
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