Distributed robust cooperative tracking against multiple maneuvering targets based on random finite set

This paper considers the distributed multi-target tracking problem with mobile sensor network. Based on random finite set and consensus methods, a algorithm is designed by local filtering stage fusion stage. In stage, state measurement information of are described set. Each node in network obtains estimates individually applying probability hypothesis density algorithm. To reduce computational complexity, Jacobian matrix Hessian used to calculate priori density. With neighboring interactions, estimate results system obtained after Besides, stochastic boundedness estimation error proved constructing process. final, simulation example given verify performance proposed