Particle Swarm Optimized Unscented Particle Filter for Target Tracking

2009 ◽  
Author(s):  
Shuying Yang ◽  
Qin Ma ◽  
Wenjuan Huang
Keyword(s):  
Particle Filter ◽  
Target Tracking ◽  
Particle Swarm ◽  
Unscented Particle Filter

Niche PSO Particle Filter with Particles Fusion for Target Tracking

2012 ◽  
Vol 239-240 ◽  
pp. 1368-1372
Author(s):  
Hai Tao Yao ◽  
Hai Qiang Chen ◽  
Tuan Fa Qin
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Filter ◽  
Target Tracking ◽  
Video Sequence ◽  
Population Distribution ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Weight Calculation ◽  
Dynamic Target ◽  
Particle Filter Algorithm

An improved particle filter algorithm is proposed to track a randomly moving target in video. In particle filter framework, a particle swarm optimization improved by niche technique which implemented by restricted competition selection is integrated. It can move particles into high likelihood area of target and form multi-population distribution, so that the searching capability of particles is enhanced and then the adaptation to the change of dynamic target state is improved. The particles of niching particle swarm optimization and the particles of particle filter are integrated for new particle weight calculation and finally realize a new particle filter for target tracking in video sequence.

Unscented Particle Filter Algorithm for Ballistic Target Tracking

2011 ◽  
Vol 130-134 ◽  
pp. 369-372
Author(s):  
Jun Wei Zhao ◽  
Ming Jun Zhang ◽  
Yong Gang Yan ◽  
Yong Peng Yan
Keyword(s):  
Convergence Rate ◽  
Particle Filter ◽  
Target Tracking ◽  
State Vector ◽  
The State ◽  
Convergence Speed ◽  
Matlab Software ◽  
Unscented Particle Filter ◽  
Simulation Results ◽  
Particle Filter Algorithm

At present, the ballistic Target tracking has a higher demand in convergence rate and tracking precision of filter algorithm. In the paper, a filter algorithm was improved based on particle filter. The algorithm was carried out from the aspects such as particle degradation and particle diversity lack. A novel ballistic coefficient parameter model was built, and was expanded to the state vector for filtering. Finally, the improved algorithm was simulated by MATLAB software. The simulation results show that the algorithm can obtain better convergence speed and tracking precision.

Sign in / Sign up

Export Citation Format

Share Document