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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. INTRODUCTIONProblems posed by the environmental impact of transport are serious, growing and constitute a major challenge to policy makers at all levels (DETR, 1999). The current array of technological, institutional and planning tools available to deal with these problems are inadequate and need urgently to be upgraded. A key feature of the problems is that they arise from the interaction of human behavioural systems and physical systems. Thus, to improve the understanding of environmental and health problems associated with vehicle emissions it is necessary to combine data on both travel and traffic behaviour with environmental data. There are currently no such databases available.A research and development project is currently underway which aims to contribute to the realisation of these data requirements by developing and applying state-of-the art environmental monitoring, positioning, communications, data mining and warehousing technologies to create and demonstrate the capabilities of an accurate, reliable and cost effective real time data collection device, the vehicle performance and emissions monitoring system (VPEMS). The VPEMS will be fitted on vehicles to monitor vehicle and driver performance and, the level of emissions and concentrations.The navigation function of the VPEMS is responsible for the derivation of all spatial, temporal and spatiotemporal data about the vehicle including location in 3-D space, time, slope, speed and acceleration. The level of positioning accuracy for VPEMS has been specified at 50m (95%) and 100m (99.9%). The availability of the positioning system has been specified at 99% (corresponding to an outage of 14 minutes of 24 hours) [Sheridan and Ochieng, 2000]. To achieve this level of performance in built-up areas, where the impact of pollution from traffic is most serious, the navigation function cannot be supported by the global positioning system (GPS) alone. A solution under consideration is the integrated use of data from GPS with dead reckoning (DR) and map matching. The Global Positioning SystemThe Global Positioning System (GPS) provides 24-hour, all-weather 3-D positioning and timing all over the world, with a predicted horizontal accuracy of 22m ...