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

Strong tracking Kalman filer method for target tracking

A Kalman filtering and target tracking technology, applied in the field of target tracking, which can solve the problems of inaccurate noise statistical characteristics, weak ability to suddenly change the target state, and volumetric Kalman filtering algorithm to deal with inaccurate models.

Inactive Publication Date: 2015-03-11
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF2 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention mainly solves the problem that volumetric Kalman filter algorithm is inaccurate in dealing with models, inaccurate noise statistical characteristics, or weak in ability of sudden change of target state, and proposes a strong tracking volumetric Kalman filter for target tracking method

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
  • Strong tracking Kalman filer method for target tracking
  • Strong tracking Kalman filer method for target tracking
  • Strong tracking Kalman filer method for target tracking

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0046] First, a discrete nonlinear dynamic system model is established; the ST-CKF filter is initialized; the ST-CKF filter is updated in time, and the time-varying fading factor λ is introduced k ; The ST-CKF filter performs measurement update; the ST-CKF filter performs filter update. Its implementation flow chart is as follows figure 1 As shown, it specifically includes the following five steps:

[0047] 1. Establish a discrete nonlinear dynamic system model as follows:

[0048] x k =f(x k-1 )+w k-1

[0049] z k =h(x k )+v k

[0050] where x k is the state vector at time k, and the dimension is n, similarly x k-1 is the state vector at time k-1, the dimension is n, z k is the measured value at time k, w k-1 and v k are the process noise and the measurement noise respectively, they are independent of each other, and the covar...

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 strong tracking Kalman filter method for target tracking, belongs to the field of target tracking, and relates to a maneuvering target method based on a strong tracking Kalman filter. The method comprises the steps of building a disperse nonlinear dynamic system model; carrying out system initialization; carrying out time updating, and introducing a time varying and fading factor [lambda k]; measuring and updating; and finally carrying out filtering updating. According to the method, the time varying and fading factor is introduced into a Kalman filter, therefore, the method has the advantages that the Kalman filter is simple to realize and high in filter precision; meanwhile, the strong tracking Kalman filter has a real-time tracking capacity on the sudden change of the system.

Description

technical field [0001] The invention belongs to the field of target tracking, and relates to a maneuvering target tracking method based on a volumetric Kalman filter (Cubature Kalman Filter based on Strong Tracking, ST-CKF). Background technique [0002] With the continuous development of science and technology, various new technical means are applied to the target tracking technology, but the application environment is becoming more and more complex, how to quickly improve the target tracking algorithm has become an urgent problem to be solved. The filtering algorithm and the data association algorithm are the core and difficult points in the maneuvering target tracking, and the present invention focuses on the research on the nonlinear filtering algorithm. However, nonlinear filtering algorithms widely exist in engineering applications. Many sensors currently used, such as infrared, electronic support measures, passive sonar, etc., are passive detection systems. Passive d...

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): G06T7/20G06T5/00
CPCG06T7/277G06T2207/20024
Inventor 于雪莲周云崔明雷钱璐张存
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

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