A Rapid Computation Method for Kalman Filtering in Vehicular SINS/GPS Integrated System

Abstract:

A new rapid computation method for Kalman filtering is proposed. In this method, the prediction of state covariance matrix is expanded directly rather than computing by a looping program. Sequential filtering for measurement update is also applied. Furthermore, the subsidiary elements in system matrix are set to zero and a reduced-dimensions sub-optimal Kalman filter is presented. The proposed method greatly decreases computational burden and it is only 6.59% of the classic method. In the end, a vehicular test is carried out to prove the feasibility of the filtering.

• Periodical: Applied Mechanics and Materials (Volumes 182-183)
• Pages: 541-545
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.182-183.541
• Online since: June 2012
• Authors: Qi Ju Zhu, Gong Min Yan, Peng Xiang Yang, Yong Yuan Qin
• Keywords: Computational Micromechanics Method, Kalman Filter (KF), Strapdown Inertial Navigation System (SINS)

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