Dah-Jing Jwo1,*, Wei-Yeh Chang2
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 755-773, 2022, DOI:10.32604/cmc.2022.025040
Abstract This paper investigates the navigational performance of Global Positioning System (GPS) using the variational Bayesian (VB) based robust filter with interacting multiple model (IMM) adaptation as the navigation processor. The performance of the state estimation for GPS navigation processing using the family of Kalman filter (KF) may be degraded due to the fact that in practical situations the statistics of measurement noise might change. In the proposed algorithm, the adaptivity is achieved by estimating the time-varying noise covariance matrices based on VB learning using the probabilistic approach, where in each update step, both the system state and time-varying measurement noise… More >
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