Inertia and ultra-short baseline multi-parameter joint calibration method based on graph optimization

Through the graph-optimized inertia and ultra-short baseline multi-parameter joint calibration method, the problem of reducing positioning accuracy caused by installation error in inertia/acoustic systems is solved, and high-precision and fast multi-parameter error estimation is achieved.

CN119714348AActive Publication Date: 2025-03-28SOUTHEAST UNIV
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Patent Information

Application Number
CN202411683591.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-22
Publication Date
2025-03-28
Estimated Expiration
2044-11-22

AI Technical Summary

Technical Problem

During the integration of inertial/acoustic systems, there are manual installation errors, such as transponder position error, lever arm error and installation angle error, resulting in system errors that seriously reduce the positioning accuracy of combined navigation.

Method used

The inertia and ultra-short baseline joint calibration method based on graph optimization is adopted. By establishing a multi-error parameter state model and constructing a multi-error parameter calibration factor graph optimization model, the interval incremental smoothing method is used to update the state, and the nonlinear problem of optimization equations is solved repeatedly iterated and re-linearized.

Benefits of technology

It realizes the simultaneous estimation of transponder position error, lever arm error and installation angle error, improves calibration accuracy and speed, and can quickly and accurately estimate system multi-parameter error in nonlinear and non-Gaussian noise environments.

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Abstract

The invention provides an inertia and ultra-short baseline multi-parameter joint calibration method based on graph optimization, a graph optimization technology is applied to inertia / ultra-short baseline multi-parameter joint calibration, and the whole process comprises the steps of establishing a multi-error parameter state model, constructing a multi-error parameter calibration factor, and calculating a nonlinear optimization problem based on increment interval balance. And finally, accurate multi-error parameters are obtained. Compared with the prior art, the method has the advantages that the position error, the lever arm error and the installation angle error of the transponder can be estimated at the same time, historical observation data are fully utilized, the nonlinear problem of an optimization equation is solved through repeated iteration and relinearization, and the method has the advantages of being high in calibration precision and high in calibration speed.
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