RAM target tracking based on improved SR-UPF algorithm

RAM target has complex motion, which puts forward higher requirements for tracking system. Aiming at particle degradation and other problems existing in the process of particle filter solving RAM target tracking, this paper calculates the posterior probability density function as the prior probability density function of the particle filter through unscented transformation, so as to improve the fitting degree of the posterior probability density function and finally improve the particle effectiveness. At the same time, qr decomposition is used to replace part of Cholesky decomposition in the process of unscented transformation, so that the variance matrix of the output signal remains non-negative. Finally, this paper establishes a dynamic model for a reentry target trajectory, and simulates with Matlab to verify the effectiveness of the proposed algorithm.