Velocity Estimation of Underwater Vehicle Based on Abnormal Magnetic Field Waveform
It is of great significance to measure real-time surface vessel magnetic field characteristics based on underwater vehicle equipped with magnetometers. In order to obtain the position information of the vehicle at the bottom of the vessel, it is crucial to estimate its speed and apply it to the auxi...
Gespeichert in:
Veröffentlicht in: | IEEE sensors journal 2024-01, Vol.24 (1), p.367-376 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | It is of great significance to measure real-time surface vessel magnetic field characteristics based on underwater vehicle equipped with magnetometers. In order to obtain the position information of the vehicle at the bottom of the vessel, it is crucial to estimate its speed and apply it to the auxiliary navigation of acoustic positioning systems. In this article, we proposed a novel method for estimating moving velocity of an underwater vehicle by processing anomaly magnetic field signals measured by two magnetometers. First, we established a detecting model for anomaly magnetic field of a fixed magnetic object using two magnetometers at different positions on the same straight line. Theoretical analysis based on the detecting model indicated that the speed of underwater vehicle can be obtained by fusing the spatial distance of the magnetometers and the time interval of the anomaly magnetic field waveforms. Then, the sparrow search algorithm (SSA) was introduced to estimate the time interval considering that this optimization algorithm has the advantage of simple structure and fast convergence. Finally, computer simulation and real-word experiments have been conducted to verify the performance of the method. The results demonstrated that the method can calculate the speed of the magnetometers correctly with an error of less than 2% and a calculation time of less than 3 s. The features of easy implementation and low computational complexity make the proposed method a potential candidate for the application in underwater-assisted navigation and other fields. |
---|---|
ISSN: | 1530-437X 1558-1748 |
DOI: | 10.1109/JSEN.2023.3324431 |