Research On The Method Of GNSS-based Track Occupancy Identification

GNSS-based train positionsing system can not only reduce the trackside equipment, but also cut the construction and operation cost in a great way. With the development of BeiDou navigation System (BDS), applying BDS into railway field such as train positionting system will be the future research direction. Being a part of train positioning, track occupancy detection directly influence the safety of train running, train interaction and shunting operation. Based on the above background, the thesis discusses and researches on the method of GNSS-based track occupancy identification.The main research area and innovative work of the thesis include:(1) The thesis proposes a track occupancy detection method using multiple hypothesis testing, which turns the track identication problem into a hypothesis and testing process. The two identification scenarios of parallel tracks and tracks at the turnout adopt Bayesian estimation and Dempster-Shafer (D-S) evidence theory respectively.(2) The thesis uses Bayesian estimation to determine the track occupancy between parallel tracks. The traditional methods are easy to be affected by gross error, and cannot give a clear occupation time. In Bayesian estimation-based track occupancy determination method, the history information is used as the prior probability and is combined with the current measurement to obtain the posterior information. Once the posterior probability is greater than the predefined threshold, the occupied track is found out.(3) The thesis puts forward an extraction method of turnout curve information based on Time-enriched sequence. The rate of the heading angular velocity of Inertial Measurement Unit (IMU) when passing through the turnout has distinguished characteristics. The thesis trains the field data to acquire the database of turnout feature, and the output information of IMU meets the characteristics of time sequence. Then the Euclidean distance is applied to calculate the similarity between IMU output and feature database which provides evidence support for D-S evidence theory later.(4) The thesis proposes a track occupancy identification method at turnout in the station throat area based on D-S evidence theory. In this method, train location information provided both by GNSS and digital track map and angular velocity of train heading output by IMU are the two important pieces evidence to determine the occupied track.The thesis carries out the off-line simulation and experiment on MATLAB platform using the field data of Qinghai-tibet Railway Line. The results show that the two methods are able to identify the track occupancy, and even in GNSS weak environment, D-S evidence can still determine the occupied track quickly.