Radar Target Detection And Tracking Algorithm Based On Multi-Frame Accumulation

It is significant to realize the stable detection and accurate tracking of targets in complex environment,with the continuous development of radar technology.Different from the traditional radar detection technology,multi-frame accumulation detection and tracking technology uses the correlation of target signal in time dimension to accumulate multi-frame energy.The performance of target detection and tracking can be improved effectively by giving target estimated track at the same time of target detection decision.Therefore,the algorithm has been concerned by scholars at home and abroad.However,there are still many problems to be solved in theory and practice as a developing technology.This paper discusses and studies the multi-frame accumulation detection and tracking technology,the main work and content are as follows:The basic theory of multi-frame accumulation detection and tracking technology is introduced.Two kinds of target detection technology and algorithm model are analyzed combining with radar system.The basic idea of the algorithm,the iterative steps of the algorithm and the selection of the accumulated value function are studied,according to the principle of multi-frame accumulation detection algorithm.The evaluation index of the algorithm is given,which lays a theoretical foundation for the follow-up study of this paper.Aiming at the multi-frame accumulation detection algorithm of non-maneuvering single target,this paper analyzes the design process and existing problems of the state transition set in the existing methods,and proposes a dual threshold multi-frame accumulation detection and tracking algorithm based on state prediction.In this method,the first level threshold is used to filter the noise like interference information,and the second level threshold is used to further filter the target state.In the process of reducing the amount of state data in search space,there may be no state information in the state transition set of a frame,then improving the iterative method of the accumulation function to solve the problem.This method can greatly reduce the computational complexity of the algorithm while ensuring the detection performance.Aiming at the multi-frame accumulation detection algorithm of non-maneuvering multi-target,this paper analyzes the existing detection ideas and problems,and proposes a multi-frame detection and tracking algorithm based on cluster management.According to the distribution of multiple targets in the radar surveillance area,the target tracks are clustered to form a corresponding search area.The track management strategy is used to detect and judge the target candidate track,then the estimated track of multiple targets is obtained.This method can effectively solve the problems of large computation and mutual interference between adjacent targets,and improve the detection performance and track estimation accuracy for multiple targets.Aiming at the multi-frame accumulation detection algorithm of maneuvering target,the existing search methods and problems are analyzed,and this paper proposes a multi-frame accumulation detection and tracking algorithm based on adaptive state transition set.By using the relationship between the mobility of the model and the moving state of the target in the current statistical model,the predicted acceleration information of the target transfer is introduced into the current statistical model,so that the state transfer set of the target can adjust the range adaptively.This method can effectively alleviate the contradiction between the search complexity and the maneuvering target model,and improve the performance of accurate detection and stable tracking of maneuvering targets.All the improved algorithms proposed in this paper are verified by simulation experiments,and the effectiveness of the improved algorithm is proved by comparing with the existing algorithm.