Air target clustering method based on K-means clustering

A k-means clustering, aerial target technology, applied in the field of target processing, can solve the problems of inaccurate grouping results, no grouping threshold division, and the target grouping method is not universal, and achieves consistency, stability and good universality. sexual effect

Active Publication Date: 2020-02-11
XIDIAN UNIV
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Problems solved by technology

However, the disadvantages of this method are that the effect of target grouping depends on the Z-axis threshold value of the stratification when pre-processing target information, and the number of clusters for the same target group is unstable, resulting in inaccurate clustering results. The problem
However, the disadvantages of this method are that the threshold range cannot be obtained by using the inverse chi-square distribution function for measuring targets that obey other probability and statistical characteristics, and there is no grouping threshold to divide the targets, which makes the target grouping method not universal. suitability

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  • Air target clustering method based on K-means clustering
  • Air target clustering method based on K-means clustering
  • Air target clustering method based on K-means clustering

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[0038] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0039] combined with figure 1 The concrete steps of the present invention are described as follows:

[0040] Step 1, read in the air target information containing air target position measurement data and air target identification data observed by the sensor at the current moment, wherein the air target measurement data refers to the position components of the target on the X axis, Y axis and Z axis, Air target recognition data includes target attributes and target types.

[0041] Step 2, generate air target dataset.

[0042] All the air targets with the same attributes in the air target recognition data form the air target data set T={t 1 ,t 2 ,...,t n}, where t n Indicates the nth air target in the air target data set T.

[0043] Step 3, generate the total number of aerial target groups.

[0044] The first step ...

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Abstract

The invention discloses an air target clustering method based on K-means clustering. The method comprises the following steps: (1) reading air target information; (2) generating an aerial target dataset; (3) generating the total number of aerial target groups; (4) according to the obtained group centers of the aerial target groups and the total number of the aerial target groups, adopting K-meansclustering to perform aerial target grouping; and (5) outputting a grouping result. According to the method, the problem that the grouping number needs to be given in advance when a K-means clustering method is used for aerial target grouping is solved; effective and accurate grouping of aerial targets in actual conditions can be realized, and the method can be used for situation estimation and command control systems.

Description

technical field [0001] The invention belongs to the technical field of target processing, and further relates to a K-means clustering-based air target grouping method in the technical field of target recognition. The invention can be used to identify air target information acquired by real-time sensors in situation assessment, so as to realize grouping of air targets. Background technique [0002] Air target grouping, also known as air target clustering, is the process of air target group formation. The basic idea of ​​air target grouping is to decompose the air target information from the bottom up according to the first-level fusion input, and abstract and divide the air target information according to certain knowledge. The current target grouping method based on clustering is susceptible to the influence of the initial cluster center and is more dependent on parameter settings, which will cause the accuracy of target grouping to be unstable. [0003] Dong Bing proposed...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/23213
Inventor 柴慧敏宋雅楠李欣粤吕少楠陈奋增
Owner XIDIAN UNIV
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