Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Sage-Husa adaptive unscented Kalman Filter attitude data fusion method

An unscented Kalman and adaptive filtering technology, applied in navigation computing tools and other directions, can solve the problems of noise statistical deviation, non-positive definite variance matrix, large filtering error, etc.

Active Publication Date: 2019-07-05
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
View PDF4 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method is likely to cause the variance matrix to be non-positive definite, and the filtering effect is poor when the noise changes greatly. At the same time, the noise statistics will be biased due to factors such as changes in the surrounding environment noise, which will eventually lead to a large filtering error or even failure.

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
  • Sage-Husa adaptive unscented Kalman Filter attitude data fusion method
  • Sage-Husa adaptive unscented Kalman Filter attitude data fusion method
  • Sage-Husa adaptive unscented Kalman Filter attitude data fusion method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0098] The following describes the embodiment of the present invention in detail, and this embodiment is exemplary, and is only used to explain the present invention, and should not be construed as limiting the present invention. A Sage-Husa adaptive unscented Kalman filter attitude data fusion method of the present invention will be described in detail below with reference to the accompanying drawings.

[0099] In order to better reflect the implementation and effect of the concrete steps of the present invention, the following simulation experiments are set up: use the MATLAB simulation platform to check the performance of the algorithm. In this experimental environment, the following measurement models can be built:

[0100] The gyroscope attitude measurement model and error model are where ω o and ω represent the angular velocity vector and the real angular velocity vector measured by the gyroscope in continuous time, respectively, n g and n εg represent zero-mean whi...

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 provides a Sage-Husa adaptive unscented Kalman filter attitude data fusion method, belongs to the technical field of digital filter and multi-sensor data fusion and is mainly used for improving carrier attitude estimation precision. According to the method, error quaternion unscented Kalman filter is taken as a frame, data of a gyroscope, an accelerometer and a magnetometer are fused, through analysis of sensor errors, a relatively accurate sensor measurement model is established, and through combination of an error quaternion method and a UKF (Unscented Kalman Filter) filter algorithm, data fusion of the sensors is realized. The method is applicable to a nonlinear attitude measurement system and has relatively good anti-interference performance and attitude calculation precision. A carrier attitude calculation problem under a complex environment can be effectively solved.

Description

technical field [0001] A Sage-Husa adaptive unscented Kalman filter attitude data fusion method provided by the invention belongs to the technical field of digital filtering and multi-sensor data fusion, and the method provided by the invention is suitable for nonlinear attitude measurement systems. Background technique [0002] The attitude measurement system of the carrier is actually a nonlinear system. In order to achieve accurate calculation of the attitude, it is necessary to use nonlinear filtering to fuse the data of the gyroscope, accelerometer, and magnetometer. However, the sensor itself is susceptible to external interference and the sensor output The data contains a lot of noise. Both process noise and measurement noise are unknown and have time-varying characteristics. Wrong parameter estimation may lead to filtering divergence, so a suitable filtering algorithm needs to be used. Therefore, a Sage-Husa adaptive unscented Kalman filter algorithm came into being....

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): G01C21/20
CPCG01C21/20Y02T90/00
Inventor 周翟和刘颀绮程遵堃
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com