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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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,
 and
*
Department of Geomatics, National Cheng Kung University, No.1, University Road, Tainan 701, Taiwan
* Author to whom correspondence should be addressed.
Received: 20 June 2013 / Revised: 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 (CC BY 3.0).
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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.

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