A New Modified Particle Filter With Application in Target Tracking
The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introd...
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| Format: | Article |
| Language: | English |
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Iran University of Science and Technology
2020-12-01
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| Series: | Iranian Journal of Electrical and Electronic Engineering |
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| Online Access: | http://ijeee.iust.ac.ir/article-1-1606-en.html |
| _version_ | 1818115868322693120 |
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| author | R. Havangi |
| author_facet | R. Havangi |
| author_sort | R. Havangi |
| collection | DOAJ |
| description | The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome these problems. The proposed method uses an adaptive unscented Kalman filter (AUKF) filter to generate the proposal distribution, in which the covariance of the measurement and process of the state are online adjusted by predicted residual as an adaptive factor based on a covariance matching technique. In addition, it uses the genetic operators based strategy to further improve the particle diversity. The results show the effectiveness of the proposed approach. |
| first_indexed | 2024-12-11T04:13:27Z |
| format | Article |
| id | doaj.art-5fd210a0eb1d40e7935bb431a2d60d4b |
| institution | Directory Open Access Journal |
| issn | 1735-2827 2383-3890 |
| language | English |
| last_indexed | 2024-12-11T04:13:27Z |
| publishDate | 2020-12-01 |
| publisher | Iran University of Science and Technology |
| record_format | Article |
| series | Iranian Journal of Electrical and Electronic Engineering |
| spelling | doaj.art-5fd210a0eb1d40e7935bb431a2d60d4b2022-12-22T01:21:19ZengIran University of Science and TechnologyIranian Journal of Electrical and Electronic Engineering1735-28272383-38902020-12-01164449460A New Modified Particle Filter With Application in Target TrackingR. Havangi0 Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, Iran. The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome these problems. The proposed method uses an adaptive unscented Kalman filter (AUKF) filter to generate the proposal distribution, in which the covariance of the measurement and process of the state are online adjusted by predicted residual as an adaptive factor based on a covariance matching technique. In addition, it uses the genetic operators based strategy to further improve the particle diversity. The results show the effectiveness of the proposed approach.http://ijeee.iust.ac.ir/article-1-1606-en.htmlparticle filtergenetic algorithmunscented kalman filtertarget tracking. |
| spellingShingle | R. Havangi A New Modified Particle Filter With Application in Target Tracking Iranian Journal of Electrical and Electronic Engineering particle filter genetic algorithm unscented kalman filter target tracking. |
| title | A New Modified Particle Filter With Application in Target Tracking |
| title_full | A New Modified Particle Filter With Application in Target Tracking |
| title_fullStr | A New Modified Particle Filter With Application in Target Tracking |
| title_full_unstemmed | A New Modified Particle Filter With Application in Target Tracking |
| title_short | A New Modified Particle Filter With Application in Target Tracking |
| title_sort | new modified particle filter with application in target tracking |
| topic | particle filter genetic algorithm unscented kalman filter target tracking. |
| url | http://ijeee.iust.ac.ir/article-1-1606-en.html |
| work_keys_str_mv | AT rhavangi anewmodifiedparticlefilterwithapplicationintargettracking AT rhavangi newmodifiedparticlefilterwithapplicationintargettracking |