Navigation_2003.pdf (1020.38 kB)
An extended Kalman filter algorithm for integrating GPS and low cost dead reckoning system data for vehicle performance and emissions monitoring
journal contribution
posted on 2009-06-16, 15:32 authored by Lin Zhao, Washington Y. Ochieng, Mohammed A. Quddus, Robert B. NolandThis 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.
History
School
- Architecture, Building and Civil Engineering
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.Publisher
© The Royal Institute of NavigationVersion
- VoR (Version of Record)
Publication date
2003Notes
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/S0373463303002212ISSN
0373-4633;1469-7785Language
- en