Accurate Pose Estimation for Flight Platforms Based on Divergent Multiaperture Imaging System
Vision-based pose estimation plays a crucial role in the autonomous navigation of flight platforms. However, the field of view and spatial resolution of the camera limit pose estimation accuracy. This paper designs a divergent multi-aperture imaging system (DMAIS), which is equivalent to a single imaging system capable of simultaneously achieving a large field of view and high spatial resolution observations. The DMAIS overcomes traditional observation limitations, allowing accurate pose estimation for the flight platform. Before conducting pose estimation, the DMAIS must be calibrated. To this end, we propose a calibration method for DMAIS based on the 3D calibration field. The calibration process determines the imaging parameters of the DMAIS, which allows us to model the DMAIS as a generalized camera. Subsequently, a new algorithm for accurately determining the pose of flight platform is introduced. We transform the absolute pose estimation problem into a nonlinear minimization problem. Using Lagrange multipliers, new optimality conditions are established for solving this problem. Finally, real calibration experiments show the effectiveness and accuracy of the proposed method. Results from real flight experiments validate the system’s ability to achieve centimeter-level positioning accuracy and arc-minute-level orientation accuracy.
Authors
- Shunkun Liang (ORCID: https://orcid.org/0000-0002-2020-2414)
- Banglei Guan (ORCID: https://orcid.org/0000-0003-2123-0182)
- Bin Li (ORCID: https://orcid.org/0000-0003-1695-1145)
- Xianwei Zhu
- Yang Shang (ORCID: https://orcid.org/0000-0002-5836-5016)
- Qifeng Yu (ORCID: https://orcid.org/0000-0002-9286-7642)
Institutions
- National University of Defense Technology (CN)
- Shenzhen University (CN)
Publication Details
- Journal
- IEEE Transactions on Instrumentation and Measurement
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tim.2025.3586339
- Citations
- 1
- Primary Topic
- Inertial Sensor and Navigation
- Type
- article
- Field-Weighted Citation Impact
- 4.99