Research On Optimization Of Train GPS Positioning Algorithm In Track Digital Map

With the rapid growth of the global economy,the railway transportation is becoming more and more important in the development of the national economy.The train positioning plays a key role in the train control system.So it is particularly important to improve the real time ability of information and reduce the error.The current train positioning is determined by the track circuit,balise,etc,but they are difficult to maintain.GPS(Global Positioning System),which is a kind of GNSS (Global Navigation Satellite System) positioning technology,has been widely used in the field of railway.However,the inherent defect of GPS is that it is a considered failure in the condition of GPS incomplete.The system can't carry on positioning process if the number of the visible satellites is less than 4.For example,the train is travelling in an area with tall buildings around,under bridges or in tunnels,and when GPS is used to monitor the train's integrity,the availability and accuracy of GPS-based systems can be degraded due to blocking of the satellite signals at the end of the train.So normal methods are constrained under these special conditions.The thesis presents a train positioning algorithm based on the digital track map and optimization method.The map data can be used directly into positioning process.This is determined by the characteristic that the train travels on certain tracks.The basic idea of the algorithm in the thesis is that the track map is viewed as a series of segments with orders.And the coordinates of head nodes and tail nodes of each piece are accurately measured.When 3 satellites are visible,first of all,which piece the train's location belongs to is identified when 3 satellites are visible.Then a straight line equation which can constrain the pseudo-range equation is made.At last,the result of the non-linear equation is got using the gradient optimization algorithm.The result is constrained by minimizing the total square error,and compared with the actual data in track map.Specific mathematical derivation and simulation have been put up on the basis of the theory proposed in the thesis.The algorithm is different from the previous algorithms which neglected the elevation change or established a virtual satellite.The map data which is a stable information source could reduce the error produced in setting parameters effectively,when it is used for solving equations.On the basis of the theory,the experimental verification for the proposed method is carried out in Sanjiadian Station,Beijing,and the performance is evaluated and analyzed.The results demonstrate that,the accuracy and stability of train positioning employing the proposed method are improved under the same conditions,compared to the current solutions both in normal and GPS incomplete environments.