Trajectory Estimation Filtering Algorithm for Underwater Equipment Based on UKF

The underwater equipment carried by the East China Sea seabed observation network is often lost due to human activities. When solving the trajectory of underwater equipment by inertial navigation, the noise caused by the complex ocean environment and sudden motion leads to large calculation errors....

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Bibliographic Details
Published inHai yang kai fa yu guan li Vol. 42; no. 1; pp. 52 - 60
Main Authors CHEN Ziyue, JI Fuwu, ZHOU Wei
Format Journal Article
LanguageChinese
Published Editorial Office of Ocean Development and Management 01.01.2025
Subjects
adaptive filtering algorithm
advanced algorithm
underwater equipment towing
unscented kalman filter
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Summary:The underwater equipment carried by the East China Sea seabed observation network is often lost due to human activities. When solving the trajectory of underwater equipment by inertial navigation, the noise caused by the complex ocean environment and sudden motion leads to large calculation errors. Aiming at the limitation that the classic unscented Kalman filter needs accurate noise model and dynamic model to output better filtering results in the trajectory estimation process, an adaptive filtering algorithm based on Sage-Husa unscented Kalman filter is proposed for solving the trajectory of underwater equipment being towed. Firstly, the implementation process of the classic unscented Kalman filter is explained, and the idea of Sage-Husa adaptive adjustment of noise is introduced; then, on this basis, the prediction residual vector is introduced to reduce the influence of gross error on the filtering result, and a tracking factor is introduced to improve the adaptability of the filter to sudden motion; fina
ISSN:1005-9857