2021/03/27 by Yarong Luo, Luo, Yarong, Chi Guo +3
Computer Science · Earth and Planetary Sciences · Engineering · #FOS: Computer and information sciences #Geophysics and Gravity Measurements #Inertial Sensor and Navigation #Robotics (cs.RO) #Target Tracking and Data Fusion in Sensor Networks #cs.RO
paper · pdf · doi:10.48550/arxiv.2103.14873
arXiv admin note: text overlap with arXiv:2102.12897
openalex publication_date 2021/03/27 · arxiv created 2021/04/18 · arxiv updated 2021/04/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes a equivariant filtering (EqF) framework for the inertial-integrated state estimation problem. As the kinematic system of the inertial-integrated navigation can be naturally modeling on the matrix Lie group SE2(3), the symmetry of the Lie group can be exploited to design a equivariant filter which extends the invariant extended Kalman filtering on the group affine system. Furthermore, details of the analytic state transition matrices for left invariant error and right invariant error are given.