Self-adaptive sensor management method for multi-sensor multi-target tracking

A multi-target tracking and multi-sensor technology, applied in the field of sensor data processing, can solve the problem that the optimal control technology cannot be directly applied

Active Publication Date: 2021-08-31
SHAANXI NORMAL UNIV
View PDF14 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Multi-sensor multi-target tracking is one of the most critical low-level technologies. Its difficulties mainly include two aspects: on the one hand, there is uncertainty in the data association between measurement and target, and multi-sensor data fusion is challenging; on the other hand, The system needs to imp...

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
  • Self-adaptive sensor management method for multi-sensor multi-target tracking
  • Self-adaptive sensor management method for multi-sensor multi-target tracking
  • Self-adaptive sensor management method for multi-sensor multi-target tracking

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] In one embodiment, such as Figure 1 to Figure 7 As shown, the present disclosure provides an adaptive sensor management method for multi-sensor multi-target tracking, which includes the following steps:

[0019] S100: according to the sensor network bandwidth limitation and the real-time requirement of tracking processing, specify the number of sensors selected at each moment to be P;

[0020] S200: Modeling sensor management as a partially observable Markov decision model;

[0021] S300: Estimate the amount of information that each sensor in the sensor network can obtain by using the partially observable Markov decision model;

[0022] S400: From all the sensors, select P sensors that obtain the most information;

[0023] S500: Sort the selected P sensors in ascending order of the amount of information;

[0024] S600: Send a control command to the sensors, activate the selected P sensors, acquire target measurements, and use the generalized label multi-Bernoulli fi...

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 self-adaptive sensor management method for multi-sensor multi-target tracking. The method comprises the following steps of S100, according to sensor network bandwidth limitation and tracking processing real-time requirements, the number of sensors selected at each moment being stipulated to be P; S200, modeling sensor management as a partially observable Markov decision model; S300, estimating the amount of information which can be acquired by each sensor in the sensor network by using the partially observable Markov decision model; S400, P sensors with the most information amount being selected from all the sensors; S500, sorting the selected P sensors according to the sequence of the information amount from small to large; and S600, a control instruction being sent to the sensors, the selected P sensors being activated, target measurement being acquired, and target number and state estimation being realized by using a generalized label multi-Bernoulli filter.

Description

technical field [0001] The disclosure belongs to the technical field of sensor data processing, and in particular relates to an adaptive sensor management method for multi-sensor and multi-target tracking. Background technique [0002] Sensor networks composed of mobile robots or static sensing nodes have received extensive attention in the fields of monitoring and scene analysis. Multi-sensor multi-target tracking is one of the most critical low-level technologies. Its difficulties mainly include two aspects: on the one hand, there is uncertainty in the data association between measurement and target, and multi-sensor data fusion is challenging; on the other hand, The system needs to implement sensor management to obtain high-quality object measurements and reduce the energy consumption of the sensor network. In highly complex multi-objective systems, sensor management is essentially an optimal nonlinear stochastic control problem, to which standard optimal control techniq...

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): G01D3/028G06F30/20G06K9/62
CPCG01D3/028G06F30/20G06F18/25Y02D30/70
Inventor 朱昀梁爽李豪唐泽栋
Owner SHAANXI NORMAL 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