| At present the explosive growth of cars brings great convenience to our life, meanwhile it causes more traffic congestion and traffic accidents as well. Therefore, many developed countries have carried out researches on intelligent transportation technology to improve traffic conditions. Vehicles' real-time and accurate positioning technology is an important prerequisite for intelligent transportation.This paper studied the research on the hybrid positioning strategy for vehicle using dual-mode global navigation satellite system (GNSS) and multi-sensors based on vehicle bus, which focused on complex environment such as urban canyon. In urban canyon area single-mode GNSS can't provide continuous, reliable positioning service. The main research is as follows:1) The multi-sensor collection platform has been constructed. The platform can realize synchronous sampling, saving, and processing of multi-sensors' data.2) Based on the original data from dual-mode GNSS, the adjusted pseudo-range and satellites' location can be obtained. Signals with strong noise can be eliminated via satellites' altitude angle and signals' carrier to noise ratio.3) Vehicle positioning model is established according to the complex environment. The hybrid positioning strategy is developed to fuse the data from dual-mode GNSS and other sensors.4) The observation model has been improved owing to the fuzzy algorithm, which would lead to better location accuracy.5) The proposed hybrid positioning strategy is proved by the real vehicle experiments. Those experiments include the trail using different fusion algorithms and observation model with better accuracy.At present, the project has completed the work above. Based on experimental results, the proposed hybrid positioning strategy can realize vehicles' reliable, continuous positioning under complex environment, which also has advantages like low cost, good robustness, and high positioning accuracy. |
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