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논문 기본 정보

자료유형
학술저널
저자정보
Feyissa Woyano (Korea University of Science and Technology) Sangjoon Park (Electronics and Telecommunications Research Institute) Soyeon Lee (Electronics and Telecommunications Research Institute)
저널정보
한국통신학회 한국통신학회지(정보와통신) 한국통신학회지 (정보와통신) 제35권 제12호
발행연도
2018.11
수록면
36 - 45 (10page)

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The advancement of wireless technology, self-contained body wearable sensor and mobile smart devices has leverages, the booming era of indoor position tracking and wireless indoor localization. It employee inertial navigation systems(INS) based attitude tracking, pedestrian dead reckoning(PDR), Wi-Fi-based indoor positioning technology, and Bluetooth Low-Energy (BLE) fingerprinting based position tracking, and synergism of both INS and PDR approaches for MEMS based pedestrian navigation. In this survey, the performance of all these different techniques used for an indoor navigation system using body wearable sensors and smart phone embedded IMU based PDR can be presented. In general, in order to provide location-based services in an indoors, we need to improve - the performance of our evaluation method, reliability of location variance due the internal characteristics of inertial sensors, rebuilding tracking algorithm, frequent changing of indoor environment ,the sensors attachments and orientations that affect the accuracy of navigation solution. Detailed comparisons has to be made among different MEMS sensor based navigation solutions with emphasis on the INS based attitude tracking and PDR position tracking as well as unconstrained smart phone position models. We conducted a test on pedestrian dead reckoning using inertial device embedded in smartphone-based approaches, in conjunction with other techniques such as Wi-Fi and BLE to compensate trajectory of PDR estimation and improve estimation precision.

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Abstract
Ⅰ. Introduction
Ⅱ. Pedestrian dead reckoning Technology using multi- sensor fusion
Ⅲ. Self-contained navigation system
IV. PDR heading Estimation
V. Multi-Sensor Fusion model in PDR
VI. COOPERATIVE FUSION FILTER
VII. Open research issues
VIII. Conclusion
Reference

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