Knowledge Commons of Institute of Automation，CAS
| Multi-Source Adaptive Selection and Fusion for Pedestrian Dead Reckoning | |
| Yuanxun Zheng; Qinghua Li; Changhong Wang; Xiaoguang Wang; Lifeng Hu | |
| Source Publication | IEEE/CAA Journal of Automatica Sinica
 |
| ISSN | 2329-9266 |
| 2022 | |
| Volume | 9Issue:12Pages:2174-2185 |
| Abstract | Accurate multi-source fusion is based on the reliability, quantity, and fusion mode of the sources. The problem of selecting the optimal set for participating in the fusion process is nondeterministic-polynomial-time-hard and is neither sub-modular nor super-modular. Furthermore, in the case of the Kalman filter (KF) fusion algorithm, accurate statistical characteristics of noise are difficult to obtain, and this leads to an unsatisfactory fusion result. To settle the referred cases, a distributed and adaptive weighted fusion algorithm based on KF has been proposed in this paper. In this method, on the basis of the pseudo prior probability of the estimated state of each source, the reliability of the sources is evaluated and the optimal set is selected on a certain threshold. Experiments were performed on multi-source pedestrian dead reckoning for verifying the proposed algorithm. The results obtained from these experiments indicate that the optimal set can be selected accurately with minimal computation, and the fusion error is reduced by 16.6% as compared to the corresponding value resulting from the algorithm without improvements. The proposed adaptive source reliability and fusion weight evaluation is effective against the varied-noise multi-source fusion system, and the fusion error caused by inaccurate statistical characteristics of the noise is reduced by the adaptive weight evaluation. The proposed algorithm exhibits good robustness, adaptability, and value on applications. |
| Keyword | Adaptive reliability evaluation adaptive weight evaluation Kalman filter (KF) multi-source fusion optimal set selection |
| DOI | 10.1109/JAS.2021.1004144 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/50587 |
| Collection | 学术期刊_IEEE/CAA Journal of Automatica Sinica |
| Recommended Citation GB/T 7714 | Yuanxun Zheng,Qinghua Li,Changhong Wang,et al. Multi-Source Adaptive Selection and Fusion for Pedestrian Dead Reckoning[J]. IEEE/CAA Journal of Automatica Sinica,2022,9(12):2174-2185. |
| APA | Yuanxun Zheng,Qinghua Li,Changhong Wang,Xiaoguang Wang,&Lifeng Hu.(2022).Multi-Source Adaptive Selection and Fusion for Pedestrian Dead Reckoning.IEEE/CAA Journal of Automatica Sinica,9(12),2174-2185. |
| MLA | Yuanxun Zheng,et al."Multi-Source Adaptive Selection and Fusion for Pedestrian Dead Reckoning".IEEE/CAA Journal of Automatica Sinica 9.12(2022):2174-2185. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| JAS-2020-1317.pdf（7050KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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