Research Article
Research of Particle Filter Based on Immune Particle Swarm Optimization

Long-Hua Ma, Yu Zhang, Zhe-Ming Lu and Hui Li

Information Technology Journal, 2013, 12(1), 155-161.


Particle degradation, as a main limitation of particle filter, can be resolved by making use of common re-sampling method, but it always bring about the problem of sample dilution. The Immune Particle Swarm Optimization (IMPSO) was introduced into particle filter and a new kind of particle filter named IMPSO-based particle filter was proposed. In the IMPSO-based particle filter algorithm, particles are driven to the area with a higher posterior probability density and maintain big particle diversity at the same time. Simulation results show that IMPSO-based particle filter can eliminates the degeneracy phenomenon, avoid the sample dilution problem and guarantee the effectiveness.

ASCI-ID: 28-1778

Cited References Fulltext

Similar Articles

A Kind of Truncated Particle Filter

Information Technology Journal, 2013, 12(4), 847-851.

Multi-features Fusion Tracking Method under Unknown Noise

Information Technology Journal, 2013, 12(4), 614-622.

Multi-human Tracking in Crowds Based on Head Detection and Energy Optimization

Information Technology Journal, 2013, 12(8), 1579-1585.

Algorithm of Head Detection and Tracking Based on Adaboost and Improved Resampling for Particle Filter

Information Technology Journal, 2013, 12(23), 7124-7130.

Cited By

State and Error Estimation in Multisource Bayesian Tracking

Procedia Computer Science, 2013, 19(), 998. DOI: 10.1016/j.procs.2013.06.139