Calibration Algorithm of Underwater Navigation System Based on Multi-orthogonal Signals

Zhang, Sen; Guo, Jinbiao; Hai-ping, Hou

doi:10.1145/3191442.3191461

Cited by 3 publications

(4 citation statements)

References 3 publications

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“… is used to describe the rotational state of the moving platform , and vector V ν is used to describe the translational movement of the moving platform. Substituting (3), (11) and into Equation (10) to expand further, we can get:…”

Section: Specificallmentioning

confidence: 99%

“…The MOSUNS calibration algorithm based on Gauss-Newton method, the nonlinear underwater beacon calibration problem is approximately linearized, and the relationship between the estimation accuracy of underwater signal position and GPS measurement error and acoustic ranging error is deduced [9] . For the transmitter attitude Angle estimation problem of MOSUNS static platform type, put forward the system calibration algorithm based on rodrigo matrix transformation method, the advantages of the algorithm in the absence of posture of prior knowledge, can be accurate estimate to the transmitter posture, nonlinear approximation, and at the same time, the algorithm does not need to avoid the error caused by the linearization [10] .In this paper, the positioning error caused by the rotation of MOSUNS's moving platform is studied and the corresponding compensation algorithm is studied.…”

Section: Introductionmentioning

confidence: 99%

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Rotation compensation algorithm of Multi-Orthogonal Signal Underwater Navigation System of moving platform

zhang

zhou

YIN

et al. 2022

Preprint

Self Cite

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When the transmitter of Multi-Orthogonal Signal Underwater Navigation System(MOSUNS) is installed on a moving platform, the rotation of the platform leads to positioning error. In order to solve this problem, the motion error modeling is carried out in this paper, the relationship platform motion parameters (translation rate, rotation rate, etc.) and the linear velocity difference between each transmitter element and the phase error is deduced, and the relationship between the positioning error of the MOSUNS and the platform motion parameters is further deduced. Based on the motion error modeling of moving platform, a rotation compensation algorithm was proposed to compensate the phase error caused by platform rotation, and then the positioning error was compensated. The motion error modeling is quantified by computer simulation, and the validity of the phase compensation algorithm is verified by simulation.

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Section: Specificallmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rotation compensation algorithm of Multi-Orthogonal Signal Underwater Navigation System of moving platform

zhang

zhou

YIN

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…T is the target terminal, and ½x, y, z is its coordinates. The receiver terminal T with the launch of the distance between A and B, respectively, is R A and R B , the distance between the origin O, and the target terminal T is R. The angle between attachment OT and X axis is α, and the angle between the ABT plane and the XOY plane is β [3][4][5].…”

Section: Working Principlementioning

confidence: 99%

Research on Towed Linear Array Shape Measurement Method Based on Biorthogonal Signal

Zhang

Wang

Jun

et al. 2022

Wireless Communications and Mobile Computing

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Systematic error and random error are main factors affecting the positioning of biorthogonal signal underwater positioning system. Based on the operation theory of USBL, this paper quantitatively analyzes a theoretical analysis and simulation calculations on influence of different error sources on the positioning accuracy and qualitatively analyzes the effectiveness of the towed linear array shape measurement method based on biorthogonal signal through practical experiments. By comparing the measurement effect after correction by using the measurement array with the measurement effect based on the linear array, the effectiveness of the method is verified.

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“…During the conventional calibration process, the workboat sails on the water surface above the beacon release position, following a preset trajectory with the release position as the center. The vessel's GPS position and slant range data are recorded, and then the estimated position of each beacon is obtained through a least squares calculation based on geometric relationships [12]. This method necessitates considerable time to calibrate each beacon, thus limiting the operational efficiency.…”

Section: Introductionmentioning

confidence: 99%

A Novel Positional Calibration Method for an Underwater Acoustic Beacon Array Based on the Equivalent Virtual Long Baseline Positioning Model

Zhang,

Yi,

Wei

et al. 2024

JMSE

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The performance of long baseline (LBL) positioning systems is significantly impacted by the distribution and positional calibration accuracy of underwater acoustic beacon arrays. In previous calibration methods for beacon arrays based on autonomous underwater vehicle (AUV) platforms, the slant range information of each beacon was processed independently, and each beacon was calibrated one at a time. This approach not only decreases the calibration efficiency but also leaves the positional calibration accuracy of each beacon highly susceptible to the navigation trajectory of the AUV. To overcome these limitations, an equivalent virtual LBL (EVLBL) positioning model is introduced in this paper. This model operates by adjusting the positions of each beacon according to the dead reckoning increments computed during the AUV’s reception of positioning signals, effectively forming a virtual beacon array. Consequently, the AUV is capable of mitigating LBL positioning errors that arise from its motion by simultaneously receiving positioning signals from all beacons. Additionally, an overall calibration method for beacon arrays based on particle swarm optimization (PSO) is proposed. In this approach, the minimization of the deviation between the EVLBL trajectory and the dead reckoning trajectory is set as the optimization objective, and the coordinates of each beacon are iteratively optimized. The simulation results demonstrate that the proposed EVLBL-based PSO algorithm (EVPSO) significantly enhanced the calibration efficiency and positional accuracy of the beacon array. Compared with conventional methods, the estimation error of the beacon positions was reduced from 6.40 m to within 1.00 m. After compensating for the beacon array positions, the positioning error of the LBL system decreased from approximately 5.00 m (with conventional methods) to around 1.00 m (with EVPSO), demonstrating the effectiveness of the proposed approach.

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Calibration Algorithm of Underwater Navigation System Based on Multi-orthogonal Signals

Cited by 3 publications

References 3 publications

Rotation compensation algorithm of Multi-Orthogonal Signal Underwater Navigation System of moving platform

Rotation compensation algorithm of Multi-Orthogonal Signal Underwater Navigation System of moving platform

Research on Towed Linear Array Shape Measurement Method Based on Biorthogonal Signal

A Novel Positional Calibration Method for an Underwater Acoustic Beacon Array Based on the Equivalent Virtual Long Baseline Positioning Model

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