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Abstract: Based on the genetic particle filter tracking algorithm of fast MH mutation, it is proposed to add the genetic evolution idea to the genetic particle filter algorithm, using the number of fast-moving particle crossovers and mutation operators, and at the same time produce a new genetic algorithm together with the wheel selection. Extract the typical particles that reflect the target probability feature faster. Experiments show that the genetic resampling method based on rapid MH mutation can avoid particle degradation, quickly increase the diversity of particles, reduce tracking errors, reduce the running time of the algorithm, and greatly improve the real-time tracking performance. After comprehensive comparison, MHGAPF algorithm has the shortest computing time. The tracking accuracy is expressed by root mean square error. Compared with GAPF algorithm and PF algorithm, MHGAPF algorithm has the lowest root mean square error in position and speed (position is 0.0313, 0.0270, speed is 0.02021, 0.0102). Among them, PF algorithm has the lowest tracking accuracy and MHGAPF algorithm has the highest tracking accuracy, which further shows that MHGAPF algorithm has good tracking performance.