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- Title
High-Precision Image Aided Inertial Navigation with Known Features: Observability Analysis and Performance Evaluation.
- Authors
Weiping Jiang; Li Wang; Xiaoji Niu; Quan Zhang; Hui Zhang; Min Tang; Xiangyun Hu
- Abstract
A high-precision image-aided inertial navigation system (INS) is proposed as an alternative to the carrier-phase-based differential Global Navigation Satellite Systems (CDGNSSs) when satellite-based navigation systems are unavailable. In this paper, the image/INS integrated algorithm is modeled by a tightly-coupled iterative extended Kalman filter (IEKF). Tightly-coupled integration ensures that the integrated system is reliable, even if few known feature points (i.e., less than three) are observed in the images. A new global observability analysis of this tightly-coupled integration is presented to guarantee that the system is observable under the necessary conditions. The analysis conclusions were verified by simulations and field tests. The field tests also indicate that high-precision position (centimeter-level) and attitude (half-degree-level)-integrated solutions can be achieved in a global reference.
- Subjects
KALMAN filtering; COMPUTER simulation; DATA modeling; DISTRIBUTED interactive simulation; PSYCHODIAGNOSTICS
- Publication
Sensors (14248220), 2014, Vol 14, Issue 10, p19371
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s141019371