Application of Untracked Particle Filter (PSO-UPF) Based on Particle Swarm Optimization in Indoor Target Tracking
Zhong Wu Yu, Lexiang Lin, Xue Chen, Zhuo Lei, Jialiang Yuan · 2024
To address the issue of particle depletion caused by resampling in traditional particle filter algorithms, an unscented particle filter algorithm (PSO-UPF) based on particle swarm optimization is proposed to enhance the number of particles and improve estimation accuracy. The study first examines the principles and implementation process of the particle swarm optimization algorithm, then compares the similarities and differences between particle swarm optimization and particle filter algorithms, focusing on how particle swarm optimization can alleviate the particle depletion problem. The effect of each particle is improved, and the basic steps of PSO-UPF algorithm are given. Simulation results indicate that the proposed algorithm significantly improves the system's robustness, real-time performance and effectiveness of the system compared with PF, UPF and PSO-PF.