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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/19677
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| タイトル: | Iterative Model Identification and Tracking with Distributed Sensors |
| 著者: | Jiang, Lei
Zribi, Amin
Matsumoto, Tad
Takada, Jun-ichi |
| 発行日: | 2024-09-26 |
| 出版者: | Institute of Electrical and Electronics Engineers (IEEE) |
| 誌名: | 2022 International Symposium on Information Theory and Its Applications (ISITA) |
| 開始ページ: | 214 |
| 終了ページ: | 218 |
| 抄録: | In this report, we propose a new iterative model identification and tracking technique for distributed sensor systems using a factor graph (FG). The idea is initiated from a position identification technique we proposed [4], however, this report aims to provide an algorithm which is applicable to more generic identification and tracking purposes. With the proposed technique, each sensor performs signal processing for compression of the measurement data and sends the compressed data to the fusion center. The marginal probability of the compressed sensing results are calculated over the FG at the fusion center. At the final stage, a maximum a posteriori probability (MAP) estimate of the model can be obtained during the tracking phase through the FG. The MAP over FG will be used for the prediction at the next state of model identification to further improve the estimation accuracy without requiring unacceptably high computation effort. |
| Rights: | Copyright (C) 2024 Institute of Electronics, Information and Communication Engineers (IEICE). Lei Jiang, Amin Zribi, Tad Matsumoto, and Jun-ichi Takada, 2022 International Symposium on Information Theory and Its Applications (ISITA), Tsukuba, Japan, October 17-19, 2022, pp. 214-218. |
| URI: | http://hdl.handle.net/10119/19677 |
| 資料タイプ: | publisher |
| 出現コレクション: | b11-1. 会議発表論文・発表資料 (Conference Papers)
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このアイテムのファイル:
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記述 |
サイズ | 形式 |
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| T-MATSUMOTO-I-1022.pdf | | 700Kb | Adobe PDF | 見る/開く |
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