Statistical iterative indoor positioning based on turbo principle
| Project/Area Number |
16K06354
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Communication/Network engineering
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| Research Institution | Osaka University |
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Principal Investigator |
Ibi Shinsuke 大阪大学, 工学研究科, 准教授 (10448087)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
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| Keywords | 位置推定 / BLE / 最大事後確率推定 / フィンガープリント / 多次元信号処理 / カメラ / WiFi / 信号処理 / 繰り返し推定 |
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| Outline of Final Research Achievements |
In this project, we aimed to establish a statistical signal processing method that comprehensively estimates the results of indoor positioning by means of BLE (Bluetooth Low Energy) fingerprint and surveillance camera as prior knowledge for each other. Indoor experiments using a transceiver equipped with commercially available BLE dongles were conducted. As a result, we clarified that it is possible to improve the estimation accuracy by the statistical signal processing. Also, we confirmed the validity of the proposed unified position estimation method that compensates for each other's drawbacks by the advantages of camera images and wireless beacons.
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| Academic Significance and Societal Importance of the Research Achievements |
「BLEによる位置推定」と「監視カメラによる位置推定」の結果を，互いに事前知識としながら繰り返し推定を行う統計的統合信号処理に対してターボ原理を適用するため，適切な尤度の定義を明確にすることを学術的な特色である．位置推定精度の向上は，今後の高度IoT（Internet of Things）社会基盤を支える重要な課題であり，本研究成果と今後期待することのできる研究成果は，人々の生活をより豊かにするための社会基盤構築の一助となるであろう．
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Report
(4 results)
Research Products
(10 results)
