Supercharge Your Innovation With Domain-Expert AI Agents!

Genetic algorithm based optimal design method for self-calibration test for inertial navigation platform system

A genetic algorithm and optimization design technology, applied in the field of inertial navigation platform system self-calibration test optimization design, can solve problems such as high dependence and long time consumption

Active Publication Date: 2016-08-24
HARBIN INST OF TECH
View PDF3 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The continuous rolling self-calibration test is characterized by more identifiable model parameters and higher accuracy, but it has disadvantages such as long time consumption and high dependence of calibration accuracy on the rotation trajectory of the platform body.

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
  • Genetic algorithm based optimal design method for self-calibration test for inertial navigation platform system
  • Genetic algorithm based optimal design method for self-calibration test for inertial navigation platform system
  • Genetic algorithm based optimal design method for self-calibration test for inertial navigation platform system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0075] A self-calibration test optimization design method for inertial navigation platform system based on genetic algorithm, the flow of the whole multi-level optimization algorithm is as follows: figure 1 As shown, it includes a large cycle and a small cycle, wherein each large cycle must execute several small cycles, and the number of small cycles is related to the algebra of population reproduction. The optimal design method includes test time optimization and information matrix determinant value optimization, and uses Fibonacci method and genetic algorithm to solve it respectively. The specific steps are as follows:

[0076] Step 1: Solve the misalignment angle equation of the calculation system relative to the station system

[0077] ψ · = ψ × ω + ϵ - - - ( 3 )

[0078] In the formula ψ—th...

Embodiment 2

[0144] The first-level optimization algorithm is as follows:

[0145] (1) First-level optimization algorithm process based on Fibonacci method

[0146] Step 1. Determine the initial interval [a 1 = l T ,b 1 = u T ], and give the final interval δ, which is the precision of the optimal value T*;

[0147] Step 2. Calculate the initial observation value λ 1 ,μ 1 ,

[0148] λ 1 = a 1 + F n - 2 F n ( b 1 - a 1 ) , μ 1 = a 1 + F n - 1 ...

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 relates to a genetic algorithm based optimal design method for self-calibration test for an inertial navigation platform system. The method comprises optimization of two stages, wherein the optimization of a first stage aims at test time and is carried out by adopting a Fibonacci method, the optimization of a second stage aims at determinant values of an information matrix, and a genetic algorithm is adopted to carry out solving. The method is used for optimizing the test time under the condition that test accuracy requirements are given, i.e., shortening the test time as much as possible on the premise of guaranteeing test accuracy, so as to achieve the aim of increasing test efficiency. According to the method, under the condition of guaranteeing test accuracy, the test time can be greatly shortened, and the test efficiency can be increased.

Description

technical field [0001] The invention relates to a genetic algorithm-based self-calibration test optimization design method for an inertial navigation platform system. Background technique [0002] In the continuous rolling self-calibration test of the inertial navigation platform system, the platform system works in a stable state in the inertial space, and the slow continuous rotation of the platform relative to the inertial space is realized by adding a moment to the gyroscope, so that the various instruments installed on the platform are sensitive to The changing gravitational acceleration projection and rotational angular velocity components stimulate each error model item and calibrate the model parameters by means of the identification method. The continuous rolling self-calibration test is characterized by more identifiable model parameters and high accuracy, but it has disadvantages such as long time consumption and high dependence of calibration accuracy on the plat...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/12G01C25/00
CPCG01C25/005G06F30/17G06F30/333G06F30/367G06N3/12
Inventor 刘雨于志伟曾鸣杨毓王毅
Owner HARBIN INST OF TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com