EKF-based state estimation for train localization

摘要: Determination of longitudinal acceleration a land-vehicle regardless its inclination is common problem for systems localization. This paper addresses solution railway applications by combining low-cost MEMS IMU (Inertial Measurement Unit) equipped with 3-axis accelerometer and gyrometer an algorithm data fusion. In particular, the impact adding attitude velocity observations into Kalman filter studied. Compared to conventional methods that use regular external aiding sensors such as GPS or tachometers, proposed approach uses Extended Filter which exploits augmented state vector. A estimation obtained method observing spectral analysis vertical complementary compose observation vector data. At last, experimental results performed on urban train are presented.