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Sensors 2018, 18(12), 4339; https://doi.org/10.3390/s18124339

Adaptive Kalman Filter-Based Single-Beacon Underwater Tracking with Unknown Effective Sound Velocity

Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China
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Received: 9 November 2018 / Revised: 3 December 2018 / Accepted: 4 December 2018 / Published: 8 December 2018
(This article belongs to the Special Issue Smart Ocean: Emerging Research Advances, Prospects and Challenges)
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Abstract

In the single-beacon underwater tracking system, vehicles rely on slant range measurements from an acoustic beacon to bound errors accumulated by dead reckoning. Ranges are usually obtained based on a presumed known effective sound velocity (ESV). Since the ESV is difficult to determine accurately, traditional methods suffer from large positioning error. By treating the unknown ESV as a state variable, a novel single-beacon tracking model (the so called “5-sv” model) and an extended Kalman filter (EKF)-based solution method have been discussed to solve the problem of ESV estimation. However, due to the uncertainty of underwater acoustic propagation, the probabilistic characteristics of the ESV uncertainty and acoustic measurement noise are unknown and varying both with time and location. EKF, which runs with presupposed noise parameters, cannot describe the practical noise specifications. To overcome the divergence issue of EKF-based single-beacon tracking methods, this paper proposes an adaptive Kalman filter-based single-beacon tracking algorithm which employs the “5-sv” model as the baseline model. Through numerical examples using simulated and field data, both the filter and smoother results show that while implementing the proposed algorithm, the tracking accuracy can be significantly improved, and the estimated noise parameter agrees well with its true value.
Keywords: single-beacon underwater tracking; adaptive Kalman filter; extended Kalman filter; effective sound velocity single-beacon underwater tracking; adaptive Kalman filter; extended Kalman filter; effective sound velocity
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Deng, Z.-C.; Yu, X.; Qin, H.-D.; Zhu, Z.-B. Adaptive Kalman Filter-Based Single-Beacon Underwater Tracking with Unknown Effective Sound Velocity. Sensors 2018, 18, 4339.

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