期刊
SENSORS
卷 18, 期 7, 页码 -出版社
MDPI
DOI: 10.3390/s18072069
关键词
SINS/DVL integrated navigation; unscented information filter; square root; state probability approximation; most suitable parameter form
资金
- Hunan Provincial Science and Technology Plan Project, innovation platform and talent plan (leading talent) [2017RS3045]
- National Key R&D Program of China [2016YFC0303002]
To address the problem of low accuracy for the regular filter algorithm in SINS/DVL integrated navigation, a square-root unscented information filter (SR-UIF) is presented in this paper. The proposed method: (1) adopts the state probability approximation instead of the Taylor model linearization in EKF algorithm to improve the accuracy of filtering estimation; (2) selects the most suitable parameter form at each filtering stage to simply the calculation complexity; (3) transforms the square root to ensure the symmetry and positive definiteness of the covariance matrix or information matrix, and then to enhance the stability of the filter. The simulation results indicate that the estimation accuracy of SR-UIF is higher than that of EKF, and similar to UKF; meanwhile the computational complexity of SR-UIF is lower than that of UKF.
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