A Fault Detection Algorithm Using an Adaptive Fading Kalman Filter for Various Types of GNSS Fault

Abstract

In this paper, a fault detection algorithm using an adaptive fading Kalman filter is introduced to detect various types of GNSS fault signal. In order to detect GNSS fault signal, the fading factor of the filter is used as a detection parameter. In simulations, the types of fault signal are represented by the ramp bias error and random bias error of the pseudo range, respectively. The change of the fading factor value according to bias error is used to compare with the detection threshold. In addition, the value of the fading factor is applied to adjust the Kalman gain and the effect of fault signal is mitigated by controlling the Kalman gain of the filter. To verify the performance of the proposed algorithm, two simple simulations are implemented. Through the results of simulation, we confirmed that the proposed algorithm works well when various types of GNSS fault signal exist.