Processing and filtering analysis of navigation data of underground strapdown inertial navigation system

In view of problems of large errors and low accuracy of positioning technology in coal mine, the strapdown inertial navigation system was introduced into coal mine personnel and equipment for precise positioning and navigation. In order to further improve positioning accuracy of strapdown inertial navigation system, filtering algorithms of extended Kalman filter and unscented Kalman filter for system data were proposed, filtering principles of extended Kalman filter and unscented Kalman filter were analyzed, and formulas and algorithms and filtering effect were simulated. The simulation results show that unscented Kalman filter has less jitter and curve is more smoother, that is, filtered data is closer to real data, and it can reflect accurately coordinate information and its error is controlled within allowable range under precondition of assuming the underground noise is Gaussian white noise, which has a better filtering effect.