Curvature Classification for Trains using Along-Track and Cross-Track Accelerometer and a Heading Rate Gyroscope

摘要: Real time curvature classification is crucial for all train localization problems. A reliable method to detected the track taken by after a switch necessary and essential collision avoidance systems. At larger scale, this should be included in global surveillance system. In paper, we discuss three possible detection methods based on two accelerometers one gyroscope. We define analyze corresponding test statistics that determine actual curvature. Given system safety requirements, i.e., maximum allowable probabilities of false alert miss-detection, derive minimum detectable difference (MDCD) between tracks compare these values with standard curvatures used Germany. it shown MDCDs strongly depend sensor quality (for which an analytical form Gaussian error overbound derived) dynamics (velocity). This analysis shows detectors very promising results suggests optimal combination their statistics.