Abstract: In order to measure deviations of intelligent sniper system's line of sight and improve firing accuracy by controlling firing time, filter weighted fusion method and linear predicting firing criterion are proposed in this paper.Kalman predicting filter is firstly used to compensate missing distance delay and line of sight deviation is obtained, meanwhile data filtered of gyroscope is integrated and another line of sight deviation is obtained. Secondly, weighted line of sight deviation based on weighted fusion algorithm is obtained. As a result, linear predicting firing criterion is built, which is based on data of gyroscope, weighted fusion algorithm and characteristic of electric firing device. Finally, dSPACE test system is built for experimental measurement of line of sight deviation and simulation of firing contrast experiment respectively. Results indicate that data of filter weighted fusion can basically present real line of sight deviation. When firing simulation is carried with filter weighted fusion method and linear predicting firing criterion, chances of impact point distributed in a circle with a diameter of 0.05 mrad is 85.7%, higher than chance of simple control firing mode which is 53.33%.