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A Track Soft Correlation Method Based on the Thought of Data Correlation

A technology of data association and track, applied in the field of multi-sensor track association, can solve the problems of declining accuracy rate of track association, complicated calculation, large amount of communication, etc., to achieve excellent performance and suppress false tracks.

Active Publication Date: 2021-11-02
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

However, in this algorithm, the sensor uploads all possible tracks to the fusion center, which requires a large amount of communication and complex calculations
Moreover, in the track association stage, the method uniquely determines a set of track combinations through the method of hypothesis testing, that is, a certain track from sensor a is uniquely associated with a certain track from sensor b, and this method belongs to one-to-one Hard association method, the accuracy rate of track association drops sharply in complex environments

Method used

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  • A Track Soft Correlation Method Based on the Thought of Data Correlation
  • A Track Soft Correlation Method Based on the Thought of Data Correlation
  • A Track Soft Correlation Method Based on the Thought of Data Correlation

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Embodiment Construction

[0061] The specific implementation manner of the present invention will be described in detail below in combination with the technical scheme and accompanying drawings.

[0062] figure 1 It is a flow chart of the track soft association method based on the idea of ​​data association.

[0063] Assumption: There are 2 sensors in the space, namely a and b, and the monitoring areas of the two sensors are the same. In the monitoring area, there are 3 targets moving in a straight line at a uniform speed. When the tracking system tracks the target in the monitoring area, it will generate the target track. while the track contains the track state x k , error covariance P k and target existence probability ψ k . This description is expressed in mathematics as a probability density function, as follows

[0064] p(x k ,χ k |Z k )

[0065] Through the above description, start to carry out the implementation steps of the present invention:

[0066] Step (1), several sensors comp...

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Abstract

The invention discloses a track soft association method based on the idea of ​​data association. The track soft association method avoids the one-to-one hard association of the traditional association algorithm through the "soft" association method, and can greatly improve the association performance in complex environments, and the track association has higher fault tolerance. In this method, the track of the auxiliary sensor is used as a measurement, and the soft association is realized by calculating the association probability of each track of the auxiliary sensor and updating the track of the main sensor to realize the "soft" association of the track.

Description

technical field [0001] The invention relates to the field of multi-sensor track correlation, and relates to a track soft correlation method based on data association, which is used to solve the problem of multi-sensor track fusion in complex environments such as high clutter and high missed detection, and can effectively improve the complex environment. In the multi-sensor target tracking problem, the target track is fused to the center to confirm the velocity and reduce the number of false tracks. Background technique [0002] The technical implementation of multi-sensor target tracking in a complex environment is quite complicated. There are generally two system structures for multi-sensor target tracking, which are generally divided into centralized systems and distributed systems. Due to the disadvantages of centralized fusion, such as high communication cost, large amount of calculation, and unstable system operation, distributed systems are generally used as multi-sens...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/12G06K9/62
CPCG05D1/12G06F18/22G06F18/251
Inventor 石义芳郭志伟洪帅鑫彭冬亮
Owner HANGZHOU DIANZI UNIV