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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Meng Yang Wei Gao |
| Copyright Year | 2010 |
| Description | Author affiliation: Automation College, Harbin Engineering University, Heilongiang Province, China (Meng Yang; Wei Gao) |
| Abstract | As an important nonlinear filter theory, the particle filter(PF) is a heated issue in domestic and foreign reseaches. The option of importance density and resampling are the key steps of particle filter algorithm. The application of UKF algorithm based on SSUT to create the importance probability density function(PDF), with the particle swarm optimization(PSO), can form a new algorithm of particle filter(PSO-SSUPF). PSO can make the paticles move to high likelihood area before the weights updating. Consequently, sample impoverishment can be restrained to some extent. With the SSUT cutting down the number of sigma points, the efficiency of the algorithm can be considerably improved in the condition of ensuring the precision being similar with standard UPF,and its performance is confirmed with the simulation. |
| Starting Page | 1857 |
| Ending Page | 1861 |
| File Size | 117223 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424457014 |
| e-ISBN | 9781424457045 |
| DOI | 10.1109/ICINFA.2010.5512257 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-06-20 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Decision support systems Automation PF Virtual reality SSUT Particle filters Improtance density PSO |
| Content Type | Text |
| Resource Type | Article |
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