Integrated navigation system fault diagnosis method based on Gaussian process regression

Abstract

The invention discloses an integrated navigation system fault diagnosis method based on Gaussian process regression. The integrated navigation system fault diagnosis method comprises five steps: 1, collecting a sample, and setting a fault detection threshold; 2, initializing a Gaussian process regression model; 3, training the Gaussian process regression model; 4, inputting a system measurement quantity to the Gaussian process regression model so as to obtain a predicted value of Kalman filtering information and a variance of the predicted value; 5, constructing a fault detection quantity, comparing the fault detection quantity with a fault detection threshold, and judging whether a fault occurs. The integrated navigation system fault diagnosis method has the advantages of being easy to realize, being capable of giving the variance of a predicted output value, and the like, and provides an assurance to the reliability and accuracy of combined navigation. Model parameters are remarkably reduced, and hyper-parameters can be conveniently calculated through a numerical analysis method, thus the integrated navigation system fault diagnosis method has the advantage of being easy to realize.

Description

technical field [0001] The invention relates to the field of navigation system fault diagnosis, in particular to a Gaussian process regression-based combined navigation system fault diagnosis method. Background technique [0002] The correctness of the measurement information of each subsystem in integrated navigation directly affects the accuracy of integrated navigation. After the main filter fuses the measurement values ​​of each subsystem, it gives a state estimate and resets the SINS. If a subsystem sensor When a gradual or abrupt fault occurs, all subsystems will be polluted by the fault after information filtering, fusion and reset. Therefore, in order to avoid cross-contamination among subsystems, once a subsystem fails, it needs to be isolated immediately, so the accuracy and speed of fault diagnosis are particularly important. [0003] At present, in the fault diagnosis methods of integrated navigation, the residual chi-square test method and the state chi-square ...

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Problems solved by technology

[0006] Purpose of the invention: In order to solve the problems of low detection sensitivity and high error rate of detection results in the prior art, the present invention provides a fault diagnosis method for an integrated navigation system based on Gaussian process regression, which can give the variance of the predicted value, so that the predicted value can be Quantitative analysis of uncertainties can quickly and accurately judge faults, which overcomes the shortcomings of existing technologies

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