Weighted nearest-neighbor data association method for centralized multi-radar data processing process

A nearest neighbor and data processing technology, applied in radio wave measurement systems, instruments, etc., can solve problems such as easy-to-follow targets

Active Publication Date: 2016-04-20
成都能通科技股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The main disadvantage is: when the target density is high, it is easy to follow the wrong target

Method used

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  • Weighted nearest-neighbor data association method for centralized multi-radar data processing process
  • Weighted nearest-neighbor data association method for centralized multi-radar data processing process
  • Weighted nearest-neighbor data association method for centralized multi-radar data processing process

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0082] A weighted nearest neighbor data association method for centralized multi-radar data processing. The scores of the seven parts are associated with each other, and then the scores of the seven parts are calculated through the weighted scoring algorithm to calculate the correlation between the track and the track to obtain the final score update value; The initial score value of the track is preset as Score=0xF0000. After the calculation of the correlation between the point track and the track, the smaller the final score update value of the score correlation result, the stronger the pairing relationship; After the calculation of the correlation between the point track and the track, if the final score update value of the score correlation result is greater than 0x9FFFF, the pairing requirement is not met.

Embodiment 2

[0084] This embodiment is further optimized on the basis of the above-mentioned embodiments, further to better realize the present invention, such as figure 1 As shown, the following setting method is adopted in particular: the scoring association through the seven parts of wave gate, heading angle or angular velocity, attribute similarity, acceleration, response times, vertical distance, and track state specifically includes the following steps:

[0085] 1) Initialize the scoring according to different distances, that is, the wave gate restriction correlation scoring step: Divide the wave gates into 14 according to the weight value from small to large, and initialize each wave gate separately, and when initializing, the small Weights start, including:

[0086] 1-1) Initialize outside the central area, use the combination of direct projection difference comparison, Cartesian distance and normalized distance to initialize the wave gate respectively to obtain the initialization ...

Embodiment 3

[0096] This embodiment is further optimized on the basis of the above-mentioned embodiments, further to better realize the present invention, such as figure 1 As shown, the following setting method is adopted in particular: the outer initialization of the central area, that is, ρ est > R center , including the following specific steps:

[0097] 1-1-1) Use the formula of the first seven wave gates The normalized distance is performed, and then the relationship between the normalized distance and the gate is compared, so as to obtain the initialization values ​​of the first seven wave gates outside the central area; the relationship between the normalized distance and the gate is shown in Table 1

[0098] Table 1

[0099] Bomen

Sigma number

Confidence

door limit

Score

1

0.5

0.3829

0.9654

Score = 0x00000

2

1

0.6827

2.2958

Score = 0x10000

3

2

0.9545

6.1801

Score = 0x20000

4

...

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Abstract

The invention discloses a weighted nearest-neighbor data association method for a centralized multi-radar data processing process. The scores of seven parts including a gate, a course angle/angular velocity, attribute similarity, accelerated speed, response times, vertical distance and track status are associated, and the scores of the seven parts are subjected to the calculation of trace point and track relevancy based on the weighted scoring algorithm. In this way, the updated value of a final score is obtained. During the score associating process, after the calculation of trace point and track relevancy, the smaller the updated value of the final score of the associated values, the stronger the matching relationship. When the updated value of the final score of the associated values is larger than 0x9FFFF, the matching requirement is not met. In the condition of limited hardware resources and high requirement on real-time performance, the above data associated processing method is relatively efficient and accurate. Meanwhile, on the basis of an original nearest-neighbor associated processing method, other associated reference factors are introduced at the same time. Therefore, an optimal matching group between trace points and the track can be gradually found out.

Description

technical field [0001] The invention relates to the technical field of radar data processing, in particular to a weighted nearest neighbor data association method for centralized multi-radar data processing. Background technique [0002] In the shore-based air traffic control centralized multi-radar data processing system, track tracking is a key part of the entire system, and data association is the core and most important content of the multi-sensor multi-target tracking system. It can be said that the data association is correct Whether or not, the efficiency is directly related to the effect and efficiency of radar data processing. [0003] The data association needs to solve the problem of suppressing the false alarm rate under the condition of low false alarm rate. Especially in the case of multi-radar data processing, information such as position information, echo length, echo amplitude, and Doppler velocity from the primary radar, and information data such as positi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41
CPCG01S7/415
Inventor 唐伟
Owner 成都能通科技股份有限公司
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