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Sensors 2013, 13(9), 11280-11288; doi:10.3390/s130911280
Article

GPS/MEMS INS Data Fusion and Map Matching in Urban Areas

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Received: 20 June 2013; in revised form: 19 August 2013 / Accepted: 22 August 2013 / Published: 23 August 2013
(This article belongs to the Special Issue Modeling, Testing and Reliability Issues in MEMS Engineering 2013)
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Abstract: This paper presents an evaluation of the map-matching scheme of an integrated GPS/INS system in urban areas. Data fusion using a Kalman filter and map matching are effective approaches to improve the performance of navigation system applications based on GPS/MEMS IMUs. The study considers the curve-to-curve matching algorithm after Kalman filtering to correct mismatch and eliminate redundancy. By applying data fusion and map matching, the study easily accomplished mapping of a GPS/INS trajectory onto the road network. The results demonstrate the effectiveness of the algorithms in controlling the INS drift error and indicate the potential of low-cost MEMS IMUs in navigation applications.
Keywords: map-matching; GPS; MEMS IMU; Kalman filter map-matching; GPS; MEMS IMU; Kalman filter
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Chu, H.-J.; Tsai, G.-J.; Chiang, K.-W.; Duong, T.-T. GPS/MEMS INS Data Fusion and Map Matching in Urban Areas. Sensors 2013, 13, 11280-11288.

AMA Style

Chu H-J, Tsai G-J, Chiang K-W, Duong T-T. GPS/MEMS INS Data Fusion and Map Matching in Urban Areas. Sensors. 2013; 13(9):11280-11288.

Chicago/Turabian Style

Chu, Hone-Jay; Tsai, Guang-Je; Chiang, Kai-Wei; Duong, Thanh-Trung. 2013. "GPS/MEMS INS Data Fusion and Map Matching in Urban Areas." Sensors 13, no. 9: 11280-11288.



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