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

State fusion target tracking method based on predicted value measurement conversion

A technology for measurement conversion and target tracking, which is used in measurement devices, radio wave measurement systems, and radio wave reflection/re-radiation. It can solve problems such as biased state estimation and Kalman gain dependence.

Active Publication Date: 2017-07-14
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF5 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the algorithm only derives the mean and covariance matrix of the transformed measurement error under the condition of the measured value, resulting in a correlation between the covariance matrix and the measurement error
This correlation causes the Kalman gain to depend on the measurement error, and thus the state estimate is biased

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
  • State fusion target tracking method based on predicted value measurement conversion
  • State fusion target tracking method based on predicted value measurement conversion
  • State fusion target tracking method based on predicted value measurement conversion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0116] In the embodiment, it is considered to perform tracking simulation on two kinds of target movement scenarios in polar coordinates.

[0117] In the polar coordinate system, the sensor is located at the origin of the coordinates, and provides the target's slant range, azimuth and Doppler measurement data with a sampling period of 1s, and the noise standard deviation of the measurement process is 0.001m 2 / s. The target initial value position is (50km, 50km), and the initial speed is (5m / s, 5m / s). 500 Monte Carlo simulations were performed for different values ​​of process noise standard deviation, distance, azimuth, Doppler measurement noise standard deviation, and correlation coefficient between Doppler velocity and distance.

[0118] Scenario 1: The distance measurement error of the sensor is 10m, the azimuth measurement error is 0.5 degrees, the Doppler velocity measurement error is 0.1m / s, and the correlation coefficient between Doppler velocity and distance is 0.1. ...

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 discloses a target tracking method based on measurement conversion Kalman filtering state fusion, which belongs to the field of radar target tracking, and particularly relates to a statistical property calculation method utilizing Doppler radar measurement conversion errors. The state fusion target tracking method comprises the steps of: calculating statistical properties of converted measurement errors based on a predicted value measurement conversion method, regarding a position predicted value in a rectangular coordinate system as a condition to obtain a mean value and a covariance of the converted measurement errors, and eliminating correlation between the covariance of the converted measurement errors and measurement errors; and then performing state estimation on a position and Doppler measurement, and finally using a least mean square error criterion to fuse estimation results of the position and Doppler measurement, so as to obtain a final state estimation. The tracking method can be further extended to CV and CA motion models of a 3D radar.

Description

technical field [0001] The invention belongs to the field of radar target tracking, in particular to a method for calculating the statistical characteristics of measurement conversion errors using Doppler radar. Background technique [0002] At present, in the target tracking system, the state equation of the target is generally established in the Cartesian coordinate system, and the measured values ​​are generally obtained in the polar coordinate system. In this way, object tracking becomes a nonlinear estimation problem. A common method to solve this problem is the conversion measurement Kalman filter (CMKF) algorithm, which uses the conversion measurement method to express the measurement transformation in polar coordinates into the measurement in the rectangular coordinate system, so that target tracking becomes a Linear Estimation Problem. However, the traditional conversion measurement method will produce deviations when converting the measurement (see literature: Le...

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): G01S13/70
CPCG01S13/70
Inventor 程婷李姝怡陆晓莹魏雪娇
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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