Target behavior mode online classification method based on multi-dimension features

A technology of multi-dimensional features and classification methods, applied in character and pattern recognition, instruments, calculations, etc., can solve the problem of not making full use of the target's position, speed, and heading features, and achieve high accuracy and simple parameter settings.

Active Publication Date: 2016-12-07
NAVAL AERONAUTICAL UNIV
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Problems solved by technology

Many scholars at home and abroad have studied the trajectory classification problem, but the existing methods mainly consider the position and shape characteristics of the target, and do not make full use of the position, speed and heading characteristics of the target, and the existing methods are mainly used for offline classification. It is not applicable to the field of early warning and surveillance, which requires high real-time intelligence processing

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  • Target behavior mode online classification method based on multi-dimension features
  • Target behavior mode online classification method based on multi-dimension features
  • Target behavior mode online classification method based on multi-dimension features

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Embodiment Construction

[0028] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0029] Step 1: Define related variables:

[0030] 1) The number k of neighbors to be considered;

[0031] 2) Training track data set where l 1 +…+l t +…+l m =l, 1, 2,..., m is the behavior pattern category label of the target corresponding to the track in the training track data set, and l is the total number of training samples;

[0032] 3) Multi-factor oriented Hausdorff distance matrix M1, M2,..., Mm, where each element M1 of matrix M1 i,j :i=1,...,l 1 ,j=1,...,k means z 1i to sample set The multi-factor directional Hausdorff distance between the jth nearest samples, each element in M2,...,Mm is the same, the specific definition of the multi-factor directional Hausdorff distance is as follows:

[0033] (1) Considering the position characteristics, velocity characteristics and course characteristics of two targets, the multi-factor distanc...

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Abstract

The invention discloses a target behavior mode online classification method based on multi-dimension features. The method comprises a step 1 of defining correlation variables, a step 2 of using one class of training track data sets and calculating the p value of a current track point in a testing track, a step 3 of repeating the step 2, and calculating p values of the current track point corresponding to other classes, a step 4 of comparing p values corresponding to all classes, and determining a target behavior mode class corresponding to the current track point, a step 5 of updating the training track data sets after target behavior modes corresponding to all track points of the current testing track are classified, a step 6 of updating a multi-factor Hausdorff distance matrix, and a step 7 of classifying target behavior modes corresponding to a next testing track. The method comprehensively utilizes the position, speed and course features of targets, is advantaged by simple parameter setting, high accuracy and good timeliness, and has a wide application prospect in the early warning surveillance field.

Description

technical field [0001] The invention relates to an online classification technology in data mining and a high-level fusion technology in information fusion, and belongs to the field of pattern recognition and intelligent information processing. Background technique [0002] In the field of early warning and surveillance, with the continuous improvement of target detection technology and information fusion technology, various targets are detected, tracked and identified, forming a constantly updated target track. A large amount of historical track data is stored and accumulated in various target intelligence processing systems in the field of early warning and surveillance. Using data mining and cluster analysis technology in trajectory data mining, the target track can be divided into different categories, so as to dig out the behavior rules of the target. The behavior pattern of the target refers to the category of the target behavior law that the current observation targe...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/214G06F18/2413
Inventor 何友潘新龙王海鹏
Owner NAVAL AERONAUTICAL UNIV
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