An Anti-jamming Approach for Infrared Target Tracking Using Trajectory Prediction and Network Flow

With the infrared imaging tracking system widely used in the target tracking field, various infrared jamming methods make the infrared target tracking algorithm face severe challenges. How to effectively resist infrared jamming has always been an important problem of infrared target tracking. Infrared jamming mainly manifests as occlusion jamming and similar object jamming. In this paper, a robust anti-jamming approach is proposed. Firstly, a detection method of continuous strong jamming is used to accurately detect the location when the jamming occurs exactly. Then the trajectory prediction algorithm based on a particle filter deals with the occlusion jamming. And an improved multi-target tracking algorithm based on the minimum cost network flow is used to eliminate the similar object jamming. Finally, using simulated data to evaluate the proposed approach. The simulation results show that compared with the existing anti-jamming method, the anti-jamming approach has good robustness and accuracy for solving the similar object jamming and occlusion jamming caused by infrared jamming.