The Study And Implementation Of WAVE-based Wireless Location

Intelligent Transportation is an important development direction of urban road traffic system, vehicle networking (IOV, Internet of Vehicles) as the concrete practice of intelligent transportation, has received strong support and research countries. Vehicle location technology is one of the important support technologies which support vehicle networking systems work effectively. Almost all of the system functional applications are based on the premise accurate positioning of vehicles, accuracy and real-time of vehicle positioning is directly related to the practical value and overall performance of vehicle networking. Currently, the GPS-based vehicle positioning is widely use, however, the GPS signals are susceptible to obstructions interference and blocking. When in the indoor, tunnels or tall buildings, due to the smaller number of visible GPS satellites, the positioning accuracy would reduce and the error becomes barge, or even the system would be unable to locate. Fully understand the basis of the definition of the WAVE protocol stack, we propose an algorithm for fingerprint positioning based on a Gaussian mixture model(GMM) in the WAVE system, which consists of an offline training phase and a real time localization phase. On offline training phase, we use GMM clustering process the whole fingerprint database, and use the multi-point average method processing results of the positioning on a real time localization phase, which not only reduces the system positioning errors, but also reduces the amount of computation, and improves real-time positioning. Experimental results show that the algorithm has better performance in both accuracy and real-time, and also provides effective reference value for further researching the fast positioning in WAVE environment.The main contents of this paper are as follows:first of all, we studied the development status of vehicle networking technology and vehicle location, and analyzed the deficiencies of the prior art. Secondly, we conducted a specific in-depth research for WAVE protocol stack and its various amendments, and in detail analyzed of the existing ranging method, positioning algorithms and wireless communication technology used in wireless location systems. Then we conducted an in-depth research for the position of the fingerprint algorithm based on RSSI (Received Signal Strength Indication), and gave a GMM-based fingerprint positioning algorithm. Finally, we used the C/S’s development model to design and implement a prototype of a wireless location system under the WAVE system, and verify the feasibility of the prototype by specific experimental tests.