Underground Coal Mines Tracking Way Based on Improved Kalman Filter Algorithm

The environment of underground coal mine is very special, the confined wireless channel which is affected by the multipath fading is a great challenge to tracking technology. A novel underground tracking algorithm is proposed, which combines the fingerprint matching algorithm with Kalman filter. Firstly, by Kalman-mean filter, the sampled RSSI value is disposed of noise, and then the position coordinates of the observation points are drawn from implementation of fingerprint matching algorithm as the observation values of the tracking, at the same time, the observation values and actual values estimate jointly underground measurement noise covariance, finally, we use improved Kalman filter algorithm to track the trajectory of the target. The experimental results show that the improved algorithm can meet the requirements of tracking accuracy and the error of underground target, enhances the reliability of tracking system.