An LBL positioning algorithm based on an EMD–ML hybrid method

An LBL positioning algorithm based on an EMD–ML hybrid method

Autonomous underwater vehicles (AUVs) are essential assets for ocean exploration requiring reliable underwater positioning technology. Aiming to improve the latter technology in a low SNR and reverberation environment, the Chan–Taylor hybrid positioning algorithm establishes a long-baseline system (...

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Bibliographic Details
Main Authors: Gao, X. (Author), Huang, H. (Author), Li, B. (Author), Xiao, B. (Author), Yang, H. (Author)
Format: Article
Language:English
Published: Springer Science and Business Media Deutschland GmbH 2022
Subjects:
Autonomous underwater vehicles
Chan–taylor hybrid positioning
Chan–Taylor hybrid positioning
EMD
Empirical Mode Decomposition
Hybrid positioning
Hybrid positioning algorithms
Long baseline systems
Ma ximum likelihoods
MATLAB
Maximum likelihood estimation
Maximum-likelihood
ML
Positioning technologies
Reverberation
TDOA
Time difference of arrival
Time-difference-of-arrival
Underwater positioning
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