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 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 as well as a limited field trial carried out in the Greater London area. The results of using the extended Kalman filter algorithm demonstrate that the integrated system employing GPS and low cost dead reckoning devices is capable of meeting the required navigation performance of the device under development.