The Combination Of High-speed Train Navigation System Algorithm Study

Today, guaranteeing a high security, improving railway operational efficiency and enhancing the capacity of the railway system are the main goal of the railway industry. Globally, with vigorous development of high-speed railway, high-speed train has reached the speed of 300km/h or more. So, train precise positioning is increasing attention. Now, chinese railway system is lack of way variety, and their applications are limited by nature. In view of such circumstances, the GPS positioning technology is used to accomplish integrated position by combining with the existing positioning method in railway. This is not only out of many restrictions on natural conditions, but also to provide precision positioning information for the train driver and dispatch control center. And this will also provide a strong guarantee for the safe operation of trains and the railway efficient scheduling, maximizing the railway transport capacity.In this paper, to direct toward the above-mentioned problem, the main research object is integrated navigation systems and navigation signal processing algorithms. And combined with integrated navigation system working principle and the actual situation in engineering, the advantages and disadvantages of integrated navigation system are researched and analyzed. And the KF and EKF algorithm are introduced. The paper puts forward the optimal fixed-interval smoother filter algorithm based on the Kalman filter. In the overall system design, navigation system design is divided into two parts:(1) A Kalman filter algorithm and the optimal fixed-interval smoother filter algorithm are adopted for SINS/GPS integrated navigation design. And carried out a simulation analysis, numerical results demonstrate that the proposed the SINS/GPS integrated navigation overcomes the shortcomings of SINS (or GPS) navigation alone. In order to ensure real-time and accurately determine high-speed train's location and speed, we have proposed SINS/GPS integrated navigation based on the Kalman algorithm and Kalman smoother algorithm. The SINS/GPS integrated navigation system performance is improved. Meanwhile, the Kalman smoothing algorithm which can obtain better filtering effect than KF algorithm is demonstrated.(2) The SINS/GPS integrated navigation system have several demerits which are the more inertial components needed, more complex equation of state and the large computational load. In order to reduce the costs and the computational load, the paper also proposes the DR/GPS high speed train integrated navigation system based on EKF algorithm. Further, two filter algorithms which are second-order EKF and EKF smoother filter derived the EKF are put forward. By comparing the EKF, second-order EKF and EKF smoother algorithm, the numerical results show that the EKF smoother algorithm gives a better precision of navigation positioning.Finally, this article gives a summary of the full text and prospects, and draws some useful conclusions.