Intelligent Aiming Method Based on Target Trajectory Prediction

The gun intelligent aiming system can calculate the aiming point real-timely for the stationary target, but for the moving target, the shooter still needs to estimate the preaiming position by himself. In order to realize the unmanned intelligent gun system, a smart aiming method based on target trajectory prediction was proposed in this paper. Firstly, we measure the target through sensors and video images, obtain the target motion trajectory and preprocess it to obtain the target space-time trajectory sequence. Secondly, we build an ARIMA model to predict the target path, decompose the trajectory into simple sub-trajectory, which are classified by moving state and stationary state. Finally, we use the prediction algorithm based on Kalman filter to predict the trajectory position of the target at the future moment in the sub-trajectory segment combined with the target motion trend estimation. We carried out simulation experiments to simulate different motion modes of the target and constructed time-space trajectory sequences for prediction. Experimental results demonstrated that the method proposed in this paper has high prediction accuracy.