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Data association method for utilizing sensing network to carry out multi-target tracking

A multi-target tracking and data association technology, applied in the direction of using re-radiation, radio wave reflection/re-radiation, measurement devices, etc., can solve the requirements of increasing cost, computing, communication and energy overhead, increasing hardware complexity, and measurement Distortion and other issues

Active Publication Date: 2016-06-29
STATE GRID CORP OF CHINA +2
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

In the second stage, the targets are close to each other, which eventually distorts the measurement
However, introducing additional attribute information increases the hardware complexity requirements and also increases the cost, computation, communication and energy overhead

Method used

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  • Data association method for utilizing sensing network to carry out multi-target tracking
  • Data association method for utilizing sensing network to carry out multi-target tracking
  • Data association method for utilizing sensing network to carry out multi-target tracking

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Embodiment Construction

[0038] Such as figure 2 Shown is the method flow chart of the present invention, the data association method that utilizes sensor network to carry out multi-target tracking provided by the present invention, comprises the following steps:

[0039] S1. Taking the receiving intensity sensor as an example, the sensor nodes in the sensor network are clustered according to distance;

[0040] S2. When the target enters the monitoring area of ​​the sensor network, the measurement information of the target is collected through the sensor node: the signal strength received by node i at time t is:

[0041]

[0042] Among them, v i (t) is background noise, N is the number of targets, a k (t) is the signal strength of target k at time t, x k (t) is the position vector of target k at time t, ξ i is the position vector of sensor node i.

[0043] S3. Calculate the state discrete time equation of the target:

[0044] the y k (t)=A·y k (t-1)+ω k

[0045] in, is the state transi...

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Abstract

The invention provides a data association method for utilizing a sensing network to carry out multi-target tracking. The method comprises the steps of: clustering sensor nodes; collecting measurement information of targets by the nodes; calculating state discrete time equations of the targets; calculating state prediction results of the targets; calculating the posterior probability of a target k in a node I; carrying out target tracking by means of a Bayes framework; calculating the posterior probability distribution of the targets; and repeating the above steps to finish target tracking. In order to carry out accurate tracking on multiple targets, the invention provides the new method to solve the data association problem in wireless sensor network multi-target tracking, the method is based on the Bayes framework, the target position state information is utilized, and the speed state information is also utilized; and compared with the modeling methods, the method provided by the invention is low in calculation amount, high in precision and is capable of accurately carrying out multi-target tracking under a low-cost condition especially in the aspect of cross and maneuvering target tracking.

Description

technical field [0001] The invention belongs to the field of measurement and control, and in particular relates to a data association method for multi-target tracking by using a sensor network. Background technique [0002] In wireless sensor networks, the ability to track objects is critical in many applications. But they pose challenges to implement traditional object tracking solutions in wireless sensor network applications due to limitations in energy, perception capabilities, communication, storage, and computing capabilities. Since any operation of data collection, processing, and dissemination of information results in an increase in resource consumption, the target tracking algorithm for wireless sensor networks should be able to use resources efficiently and reduce computational complexity. [0003] Currently, single object tracking is well studied, but the problem of multiple object tracking (MTT) still has some key issues to be solved. Among them, data associat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/66
CPCG01S13/66
Inventor 肖克江王睿魏鹏飞曾少华刘俊
Owner STATE GRID CORP OF CHINA
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