Research on location algorithm of opencast mine vehicle based on improved adaptive H ∞ CKF and IAGA

Aiming at the problems of non-line-of-sight delay and low positioning accuracy in the location of transport vehicles in the complex environment of the non-coal opencast mine, an improved adaptive H ∞ CKF and IAGA-TDOA positioning algorithm for transport vehicles in non-coal opencast mine is proposed, a Lora + 4G positioning platform is built, and the effectiveness of the algorithm is verified through simulation and field test. Improved Adaptive Genetic Algorithm (IAGA) updates the optimal preservation strategy of traditional genetic algorithm and redefines the adaptive cross rate and variation rate. The improved adaptive H ∞ Cubature Kalman Filter (CKF) algorithm reduces the effect of noise by weighting new and old noise. The simulation results show that the relative error of the improved adaptive H ∞ CKF algorithm is reduced by 85% compared with the traditional Kalman Filter. Comparing IAGA with other four algorithms to solve the TDOA positioning model, the IAGA algorithm has the smallest positioning error, and the minimum error is only 0.8 m. The field test shows that the average error of the system is within 7.4 m, and it can display the historical running track of the vehicle, which has a certain guiding significance for the automatic production of the mining area.