Clutter-oriented multi-sensor asynchronous detection tsbf multi-target tracking method

A multi-target tracking and multi-sensor technology, which is applied in the field of multi-sensor asynchronous detection and multi-target tracking, achieves the effect of clear configuration structure and small amount of calculation

Active Publication Date: 2020-08-25
HANGZHOU DIANZI UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the clutter environment, there is no specific fusion algorithm that can solve the optimal effect of multi-sensor data fusion results. Therefore, a multi-sensor multi-level fusion multi-target tracking method in the clutter environment is proposed to achieve effective and High-precision tracking effect

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
  • Clutter-oriented multi-sensor asynchronous detection tsbf multi-target tracking method
  • Clutter-oriented multi-sensor asynchronous detection tsbf multi-target tracking method
  • Clutter-oriented multi-sensor asynchronous detection tsbf multi-target tracking method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0011] The specific implementation manner of the present invention will be described in detail below in combination with the technical scheme and accompanying drawings.

[0012] (1) Construct a multi-sensor multi-target tracking scene, and initialize the motion model of the target. Sensor measurements can come from targets or clutter.

[0013] If the measurement information comes from the target, the motion model of the target, the measurement model of the sensor and the clutter model are constructed and initialized.

[0014]

[0015] In the formula, k represents a discrete time variable, i (i=1,2,...,N) represents a sequence of targets, and j (j=1,2,...,m) represents a sequence of sensors. ω k Indicates that the mean is zero and the variance is Q k Gaussian white noise, υ k means that the mean is zero and the variance is The measurement Gaussian white noise of , and the process noise and measurement noise at each moment are independent of each other. Map f k|k-1 In...

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 clutter-oriented multi-sensor asynchronous detection TSBF multi-target tracking method. According to the invention, a complete processing method flow is provided according toa asynchronous multi-sensor data fusion multi-target tracking problem in a clutter environment; a multi-sensor multi-stage fusion structure is constructed; and a sensor measurement information-basedtime registration method is provided. The method of the invention has the advantages of concise configuration structure and small calculation amount, and can be widely applied to the multi-target tracking field.

Description

technical field [0001] The invention belongs to the field of multi-sensor multi-target tracking, and relates to a multi-sensor asynchronous detection multi-target tracking method, which is used to solve the problem of multi-target tracking in a clutter environment, improve the tracking quality of unknown targets in the monitoring space, and perform multi-target tracking. Provide reference for engineering application of technology. Background technique [0002] Multi-sensor multi-target tracking is a kind of technically complex problem. The process of multi-sensor multi-target tracking mainly includes two aspects of target state estimation and data fusion. Traditional multi-target tracking methods mainly include track start and end, data association, tracking maintenance, etc. Among them, data association and tracking algorithm are the two most important issues, and representative algorithms such as Joint Probability Data Association Algorithm (Joint Probability Data Associat...

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 Patents(China)
IPC IPC(8): G01S7/41
CPCG01S7/414
Inventor 申屠晗刘嵩
Owner HANGZHOU DIANZI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap