Abstract
This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV.
Highlights
An AUV is applied to execute all kinds of underwater tasks, including ocean exploration, underwater mine clearance and collecting bathymetry data of ocean and rivers [1,2,3,4]
This paper, directed at deficiencies in existing underwater positioning technology, proposes an underwater positioning system based on the mutual assistance of strapdown inertial navigation system (SINS)/DVL/magnetic compass pilot (MCP) and LBL
The underwater positioning system based on the mutual assistance of SINS/DVL/MCP and LBL
Summary
An AUV (autonomous underwater vehicle) is applied to execute all kinds of underwater tasks, including ocean exploration, underwater mine clearance and collecting bathymetry data of ocean and rivers [1,2,3,4]. An, L. et al came up with an ambiguity-solving algorithm based on underwater acoustic propagation characteristics [16] This method, by studying the distribution rule of cross-correlation peaks forming the multipath transmission of underwater signal channels, tracks stable correlation peaks, which can effectively correct the miscalculation of the TDOA value caused by the ambiguity of the correlation peaks. AUV), correct accumulative errors of SINS/DVL, use of resolving results of SINS/DVL to adopt the hyperbolic model to solve the position the sound source (namely, the assist in solving ambiguous correlation peaks when is launching underwater acoustic position of the AUV), correct accumulative errors of SINS/DVL, use resolving results of SINS/DVL to positioning, estimate the TDOA valuepeaks and improve theissolution accuracy of LBL positioning. We verify the effectiveness of the algorithm through a simulation experiment
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