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

Method for estimating noise covariance of unmanned aerial vehicle

A noise covariance, UAV technology, applied in the UAV field, can solve the problems of easy deviation and high operator requirements, and achieve the effect of ensuring accuracy and saving debugging time.

Active Publication Date: 2018-02-23
SHENZHEN SPROCOMM TECH CO LTD
View PDF5 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical solution of the present invention is to overcome the problem that in the existing filtering algorithm for processing the process noise and measurement noise of the UAV, when the noise characteristics are unknown, it is necessary to use empirical values ​​or obtain the covariance matrix value of the noise by debugging methods , which have high requirements for operators and are prone to bias, design an estimation method that can automatically estimate the covariance matrix value caused by process noise and observation

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
  • Method for estimating noise covariance of unmanned aerial vehicle
  • Method for estimating noise covariance of unmanned aerial vehicle
  • Method for estimating noise covariance of unmanned aerial vehicle

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0100] Since the UAV dynamics model is a 12-dimensional equation system, when using the covariance least squares theory method to estimate the noise covariance in the model, in order to shorten the program running time, the noise covariance in the linear motion and the angular motion are respectively Make an estimate. The values ​​of the parameters in the model used in the simulation are shown in Table 1.

[0101] Table 1 parameter values

[0102] parameter name

parameter value

parameter name

parameter value

UAV mass m

1.5kg

acceleration of gravity g

9.79m / s 2

x-axis moment of inertia I xx

0.024kg·m 2

y-axis moment of inertia I yy

0.024kg·m 2

Z-axis moment of inertia I zz

0.112kg·m 2

L

0.232m

Blade pull coefficient b

1.0643×10 -5

Blade torque coefficient d

2.3528×10 -7

Air resistance coefficient k

-0.2334

[0103] ①Line motion

[0104] The state...

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 method for estimating a noise covariance of an unmanned aerial vehicle. A dynamics model of the unmanned aerial vehicle is linearized in combination with a control quantity and an observation value by utilizing an extended Kalman filter to obtain a linearized state estimation equation; and a coefficient matrix, a Kalman gain and an innovation obtained by the linearized state estimation equation are substituted into an auto-covariance least squares algorithm to obtain estimated values of a covariance matrix composed of an expected value of the innovation and an auto-covariance matrix composed of the expected value of the innovation, and through a semi-definite programming algorithm, a process noise covariance and a measurement noise covariance are obtained. Throughthe method for estimating the noise covariance of the unmanned aerial vehicle, the estimation accuracy of the process noise covariance Q and the measurement noise covariance R is high. Meanwhile, theestimation method provides a numerical value reference for operators, so that in general, the operators can debug the process noise covariance Q and the measurement noise covariance R more conveniently and quickly.

Description

technical field [0001] The invention relates to the technical field of unmanned aerial vehicles, and more specifically, relates to a method for estimating the noise covariance of an unmanned aerial vehicle. Background technique [0002] Unmanned aircraft, referred to as "UAV", is an unmanned aircraft controlled by radio remote control equipment and its own program control device. It has a wide range of uses and is widely used in military and civilian fields, such as air early warning, agriculture, geological , meteorology, electric power, emergency rescue, video shooting and other industries. As a UAV controlled by a self-contained program control device, it has the characteristics of strong coupling, nonlinearity, and high control difficulty, and its dynamic modeling is relatively complicated. The disturbances faced by the control and manipulation of UAVs include: external disturbance moments such as gravity, as well as system noise in the UAV dynamics model and observatio...

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): G06F17/50
CPCG06F30/15G06F30/367G06F30/00Y02T90/00
Inventor 刘国良邬静云黄涛张瑞
Owner SHENZHEN SPROCOMM TECH CO LTD
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