A signal process algorithm of relative position detection sensor for high speed maglev trains based on KF-UKF

摘要

The relative position detection sensor can detect the tooth-slot structure of long stator track and generate periodic sinusoid signals. A signal process algorithm based on KF-UKF and a state space model for the sensor are proposed in this paper, which can estimate the position and speed of maglev trains, even when lots of Gaussian noises exits. Actual comparison experiments and numerical simulations demonstrate the performance of the proposed algorithm is better than others, meanwhile with a lower computation complexity, which can satisfy the requirement of actual applications.