Unscented Particle Filter Algorithm Based on Particle Swarm Optimization

Aiming at the problem of Unscented Particle Filter(UPF) algorithm such as particles degeneracy and particles impoverishment,by comparing particles' present values with the fitness value of objective function,it uses Particle Swarm Optimization(PSO) algorithm to make particles of UPF move towards the higher likelihood area,and finds the optimal position,and relieves the problem of particles degeneracy and impoverishment by improving re-sampling process.Experimental result proves that the state estimation precision of the improved algorithm is superior to traditional UPF algorithm.