Aerial target identification method and system based on improved decision tree

A technology of air target and identification method, which is applied in the field of air target identification method and system based on improved decision tree, can solve the problems of inability to effectively mine historical activity trajectory behavior patterns of targets, and achieve fast moving speed, wide moving range and accurate identification Effect

Active Publication Date: 2020-05-26
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention aims at the few existing researches on target recognition using the features of the target’s motion trajectory. Different methods are used to match the target’s motion trajectory with the historical trajectory, and the target is identified according to

Method used

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  • Aerial target identification method and system based on improved decision tree
  • Aerial target identification method and system based on improved decision tree
  • Aerial target identification method and system based on improved decision tree

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Experimental program
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Embodiment 1

[0054] Such as figure 1 As shown, an air target recognition method based on an improved decision tree, including:

[0055] Step S101: Detecting a set of position points of an air target during navigation by a sensor to form a target navigation trajectory data set, and dividing the target navigation trajectory data set into a training set and a test set;

[0056] As a possible implementation mode, the position points of the four key air targets of the reconnaissance plane U2, the fighter F15, the bomber B52, and the tanker KC135 are detected by the sensor to form a target navigation track (history) data set, and each type of aircraft Includes 500 complete trajectories. All the track data collected are divided into training set and test set. The training set contains 400 complete trajectories, and the test set contains 100 complete trajectories. There is no cross content between the training set and the test set. The number of target position sampling points (position points) ...

Embodiment 2

[0095] Such as image 3 As shown, an air target recognition system based on an improved decision tree, including:

[0096] The acquisition module 301 is used to detect the position point set of the air target during navigation through the sensor to form a target navigation trajectory data set, and divide the target navigation trajectory data set into a training set and a test set;

[0097] The feature extraction module 302 is used to perform feature extraction on the training set and the test set: extract the motion features of the target at each position point from the target navigation trajectory data to form a first feature vector, and the motion features include position occurrence time, position longitude , position latitude, position height, movement speed and movement direction;

[0098] The refinement and discretization processing module 303 is used to refine and discretize the training set and test set after feature extraction: refine each dimension of the first feat...

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Abstract

The invention discloses an air target recognition method based on an improved decision tree, and the method comprises the steps of constructing a target navigation track data set which is divided intoa training set and a test set; performing feature extraction, refinement and discretization processing on the training set and the test set; constructing a target classification decision-making treeby adopting a C4.5 decision-making tree algorithm based on the processed training set; inputting the processed test set into a target classification decision tree, performing hierarchical judgment along the root node according to the target classification decision tree until the target type of the leaf node is used as a target identification result of the position point, and adding 1 to the support degree of the type used as the identification result; traversing all position points of the target navigation track in the processed test set, counting recognition results, and taking the recognition result with the highest support degree as a final target recognition result of the target navigation track. The invention further discloses an aerial target recognition system based on the improveddecision tree. According to the invention, the behavior mode in the target historical movement track can be effectively mined.

Description

technical field [0001] The invention belongs to the technical field of machine learning, and in particular relates to an air target recognition method and system based on an improved decision tree. Background technique [0002] With the continuous development of modern aircraft technology, the types of spacecraft performing various combat missions are increasing. In modern warfare, timely and accurate identification of high-value air targets on the battlefield can ensure full control of the battlefield situation, and is conducive to real-time analysis and judgment of the battlefield situation to make timely responses. [0003] The existing automatic identification methods for air targets mainly identify targets through the electromagnetic characteristics, radiation source characteristics, optical imaging characteristics or microwave imaging characteristics of the target perceived by the same or multiple sensors. The main methods are divided into three categories. Aiming at ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
CPCG06V10/40G06F18/2411
Inventor 李珠峰朱珊珊胡瑞娟唐慧丰李勇黄晓辉余文涛席耀一王博刘剑
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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