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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/4848

Title: An extended Kalman filter algorithm for integrating GPS and low cost dead reckoning system data for vehicle performance and emissions monitoring
Authors: Zhao, L.
Ochieng, Washington Y.
Quddus, Mohammed A.
Noland, Robert B.
Issue Date: 2003
Publisher: © The Royal Institute of Navigation
Citation: ZHAO, L....et al., 2003. An extended Kalman filter algorithm for integrating GPS and low cost dead reckoning system data for vehicle performance and emissions monitoring. The Journal of Navigation, 56(2), pp. 257-275.
Abstract: This paper describes the features of an extended Kalman filter algorithm designed to support the navigational function of a real-time vehicle performance and emissions monitoring system currently under development. The Kalman filter is used to process global positioning system (GPS) data enhanced with dead reckoning (DR) in an integrated mode, to provide continuous positioning in built-up areas. The dynamic model and filter algorithms are discussed in detail, followed by the findings based on computer simulations and a limited field trial carried out in the Greater London area. The results demonstrate that use of the extended Kalman filter algorithm enables the integrated system employing GPS and low cost DR devices to meet the required navigation performance of the device under development.
Description: This is an article from the journal, The Journal of Navigation [© The Royal Institute of Navigation]. It is also available at: http://dx.doi.org/10.1017/S0373463303002212
Version: Published
DOI: 10.1017/S0373463303002212
URI: https://dspace.lboro.ac.uk/2134/4848
ISSN: 0373-4633
1469-7785
Appears in Collections:Published Articles (Civil and Building Engineering)

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