Integrated navigation system fault diagnosis method based on Gaussian process regression

A technology of Gaussian process regression and integrated navigation system, applied in the direction of measuring devices, instruments, etc., can solve the problems of high error rate of detection results and low detection sensitivity

Active Publication Date: 2014-09-17
SOUTHEAST UNIV
View PDF3 Cites 21 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Integrated navigation system fault diagnosis method based on Gaussian process regression
  • Integrated navigation system fault diagnosis method based on Gaussian process regression
  • Integrated navigation system fault diagnosis method based on Gaussian process regression

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0068] The present invention will be further explained below in conjunction with the accompanying drawings.

[0069] The present invention can be better understood from the following examples. Such as figure 1 As shown, a kind of Gaussian process regression based integrated navigation system fault diagnosis method of the present invention, concrete steps are as follows:

[0070] Step 1) Collect the system observation Z={Z when the sensor is fault-free k |k=1,2,...n} and its corresponding Kalman filter innovation R={r k |k=1,2,…n} as samples, and set fault detection threshold λ 0 ;

[0071] Step 2) Gaussian process regression model initialization: set the covariance function and the initial value of the hyperparameter, and use the mean square index covariance function; the variable Z p with Z q The mean square exponential covariance function for :

[0072] k ( Z p , Z ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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 ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01C25/00
CPCG01C25/00
Inventor 程向红朱倚娴王磊胡杰
Owner SOUTHEAST UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap