Tracking a maneuvering target in a nonlinear interference environment has been discussed in some literature，and this paper considers the problem of tracking with multiple passive sensors in the non-Gaussian noise environment. The measurements possibly include random interference and Glint noise. The method of target state estimation in this paper is a dynamic programming approach. Unlike the traditional method，we reduce the estimating problem to a multiple hypothesis-testing problem，and then use the dynamic programming algorithm to solve the problem of tracking with non-Gaussian noise. The simulation results show the superiority of the new method.