| Distributed multi-target and multi-sensor management is a fundamental problem in nonlinear control theory.Multi-sensor management is a management algorithm combining Bayesian recursive filter and information theory objective function of the whole multi-sensor and multi-target system.Due to the increasing number of sensors applied in the scene,the distributed fusion of multi-target and multi-sensor network is also developing.In this paper,under the framework of labeled Random Finite Set theory,and combined with the robust Generalized Covariance Intersection fusion criterion,we mainly study the multi-target tracking algorithm,distributed fusion algorithm,multi-sensor management and so on.The main contents of this paper are as follows:(1).In view of the advantages of distributed information fusion algorithm,such as low communication cost,high fault tolerance and strong robustness,distributed fusion criterion is adopted to process the posterior information fusion in this paper.A distributed fusion algorithm based on robust Generalized Covariance Intersection fusion criterion(R-GCI)is proposed,and the analytic expression of the posteriori distribution of R-GCI-LMB is derived,which provides the precondition for the fusion of the distributed multi-target multi-sensor management algorithm.The simulation results prove that the R-GCI-LMB fusion algorithm proposed in this paper is robust and the accuracy of tracking target.(2).For multi-target tracking and multi-sensor management: a multi-sensor and multi-target tracking sensor control method based on LMB filter is proposed in this paper.The Cauchy Schwarz(CS)divergence of information theory is taken as the target function of multi-sensor control,the labeled dobernuli filter is adopted,the distributed fusion of the probability density of multi-target is achieved based on the robust Generalized Covariance Intersection(R-GCI)fusion criterion,and obtained the track estimationof multi-target motion.Based on the sequential Monte Carlo(SMC)method,the approximation execution of CS divergence and LMB filter is obtained,and a local search algorithm is proposed to obtain the suboptimal solution of the multi-sensor control problem.The simulation results show the feasibility and superiority of the proposed multi-target tracking and multi-sensor control algorithm.Based on the LMB filter,this paper mainly studies the distributed multi-target tracking and multi-sensor management algorithm.In the distributed multi-sensor network,the fusion problem of multiple sensors is solved by using the robust GCI distributed fusion criterion.After the fusion,the tracking track of the target is generated,and the detailed expression of the R-GCI-LMB fusion algorithm is obtained.Based on this fusion algorithm,the CS divergence is chosen as the objective function to study the decision-making problem in multi-sensor management,and the local search method is proposed to replace the exhaustive method.In the case of reducing the computation,the sub optimal sensor decision-making is obtained to track the target more accurately. |
