The Terminal Research Design Of WAVE And Positioning Technology Study

With the rapid development of Intelligent Transportation Systems, and with the rapid development of Internet of Things, as a solution to urban highway traffic,“Internet of Vehicles” the concept has been widely concerned in the world, since the first time raised by the General Motors. It has been an important part of the Internet of Things, and will be an important direction of the Internet of things in the future.WAVE is the studying background of this paper. Firstly, study timing synchronized issues of the baseband in WAVE system. Secondly, study vehicle location issues in WAVE system. The main content of this paper are as follows.First, made a brief introduction to the basic theoretical knowledge of the baseband synchronized section and made a brief introduction to the basic theoretical knowledge of the vehicle location. Briefly introduced the physical layer PPDU frame structure in IEEE802.11 p protocol of WAVE protocol family, introduced OFDM technology the core principles of WAVE terminal design in detail, and made a detailed presentation on synchronization errors. Introduced the location algorithm based on the base station Then made a detail introduction on the current popular TDOA location method, and described the evaluation index of wireless channel model and positioning and the impaction of wireless channel on location.Secondly, studied the timing synchronization algorithms based on training symbols.Described in detail the classic SC synchronization algorithm, including training symbol structure, timing estimation, fractional part of frequency offset estimation. And detailed analyzed the advantages and disadvantages of SC algorithm. Then introduced the timing synchronization algorithm of the ten short training symbol defined in the physical layer frame format defined in IEEE 802.11 a protocol, and analyzed the timing performance of the algorithm. Finally, according to SC algorithm and ten short training symbols’ timing synchronization algorithm, progressively derived a new training symbol, and also proposed it’s timing synchronization algorithm and fractional frequency offset estimation algorithm. Finally, throw the simulation analysis, verified that the new algorithm eliminates the effects of the platform area due to cyclic prefix and improves the accuracy of timing estimated and fractional frequency offset.Finally, studied the location algorithm based on the base station. First introduced the least squares method, and summarized several channel models and the distribution of base stations based on the base station network topology, which would be used in this paper’ simulations, and through simulations, analyzed the number of base stations required for a suitable location and the effect on positioning due to choosing different base station. Then analyzed Taylor algorithm, and simulated the targeting performance of Taylor algorithm in the actual channel environment. Finally, focus on introducing the improved linear least square method and comprehensive Initial Taylor iterative positioning method with the rational use of the RSU location, and the simulation results proved that the positioning error of the comprehensive Initial Taylor iterative positioning method is the lowest.