DP-TBD Algorithm of Multi-frame Accumulation Detection Based on Adaptive State Transition Set

In view of the problems existing in the multi-frame accumulation detection algorithm of maneuvering target, a multi frame accumulation detection and tracking algorithm based on adaptive state transition set is proposed, and the corresponding simulation experiments are designed to verify the effectiveness of the algorithm. Aiming at the existing problems, the corresponding improvement strategies are introduced in detail, and the current statistical model is used to improve the adaptability to the maneuvering target. In order to effectively limit the search space of the target state, the target prediction path in the process of value function accumulation is used to estimate the transfer acceleration of the target in real time and constrain the acceleration. By combining the correlation of transfer acceleration in time dimension with the current statistical model, the range of target state transfer set is adaptively adjusted,so as to reduce the interference information in target search space and improve the detection accuracy and calculation efficiency of the algorithm. Finally, the improved algorithm and the existing algorithm are simulated in different maneuvering target scenarios. The simulation results show that the improved algorithm proposed in this chapter has better detection and tracking performance.