A target estimation algorithm based on unscented particle filter

Aiming at the problem of target information acquisition in passive homing guidance, a target estimation algorithm is designed based on the unscented particle filter. Particle filtering is not constrained by Gaussian hypothesis and linearity, and the global optimal state estimation can be realized. In order to solve the problem of particle degeneracy, the proposed distribution obtained by the Uunscented Kalman Filter (UKF) is used as the important density function in Particle Filter (PF) and the resampling is also introduced. The Unscented Particle Filter (UPF) is designed to realize the accurate estimation of the target information. The simulation results show that this algorithm can realize the high accuracy estimation of the target information, and after the target radar is switched off, it can output the measurement information and realize the normal work of the passive guidance system.