Research Of City Rail Transit Network Design And Positioning Algorithm

In recent years, with the rapid development of the transport industry, the new modern high-speed rail transport, urban subway construction and other city traffic tool used in national gradually become the mainstream of transport to travel and facilitate people’s lives. However, the case of frequent disturbances have occurred in the high-speed railway, urban subway communication signals, seriously affecting the railroad dispatching,even cause transportation safety impacting to people’s lives and property.To solve these problems, this paper presents the detection of urban rail transit network, and the article focuses on the following schedule:1、This study program will supplement the existing fixed station in Kunming, which is the secondary monitor of electromagnetic environment. At the same time, this paper will focus on monitoring the Kunming Urban Rail Transit subway, the TETRA digital clusters nearby800MHz, between700MHz-900MHz. Network needs to pay attention to the compatibility with the original equipment, network protocol and interface standard. Project in my paper based on three-tier structure supervision center-fixed station-small base station node (RF sensors). According to grid classification, completed real-time monitoring in buildings and people gathered, key areas, key businesses.The distribution of radio frequency sensors based on the grid size, building and population density, the grid planning area is relatively small at important regional like city center, the subway entrances, and subway line intersection area. The electromagnetic environment at the city suburb is simpler, we can set the grid area larger.2、In locating the source of interference, the paper compares the four basic wireless positioning technology, evaluation index of positioning accuracy and the key reason influenced wireless positioning accuracy. TDOA has many advantages such as mature theory, high precision, simple structure, so it is widely used in modern supervision system. According to the calculation method, this paper presents an improved calculation method which integrates the Chan and the Taylor. By introducing the use of gradient descent stretch factor gradually recursive iterations, then the initial value calculated by Chan substitute into Taylor, obtaining the final positioning coordinates. In this paper, an improved combination of two methods, not only reduces the TDOA error (NLOS environment), but also avoids the problem which is difficult to determine the initial value. The simulation results show that compared with other algorithms in NLOS environment, our algorithm gets a higher positioning accuracy.