Deep learning-based airport scene moving target identification method combined with ADS-B (Automatic Dependent Surveillance-Broadcast) information

A technology of ADS-B and moving targets, applied in neural learning methods, character and pattern recognition, computer components, etc., can solve problems such as algorithm display results are not intuitive enough, information redundancy, and the aircraft is stationary on the apron, etc., to achieve effective The effect of scene monitoring scheme and improvement of detection accuracy

Pending Publication Date: 2022-07-29
YANGTZE DELTA REGION INST (QUZHOU) UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

However, in the specific scene of airport scene surveillance, most of the planes are often stationary on the apron, and only a small number of planes are in motion.
Among them, we are only interested in moving targets, and the target detection algorithm will detect all the targets in the screen, which will not only cause redundant information, but also the display results of the algorithm are not intuitive enough

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  • Deep learning-based airport scene moving target identification method combined with ADS-B (Automatic Dependent Surveillance-Broadcast) information
  • Deep learning-based airport scene moving target identification method combined with ADS-B (Automatic Dependent Surveillance-Broadcast) information
  • Deep learning-based airport scene moving target identification method combined with ADS-B (Automatic Dependent Surveillance-Broadcast) information

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Embodiment Construction

[0034] The specific embodiments of the present invention are described below to facilitate those skilled in the art to understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes Such changes are obvious within the spirit and scope of the present invention as defined and determined by the appended claims, and all inventions and creations utilizing the inventive concept are within the scope of protection.

[0035] A deep learning-based airport scene moving target recognition method combined with ADS-B information, such as figure 1 shown, including the following steps:

[0036]S1. Decode the ADS-B information, and use the three-dimensional data returned by the aircraft and the position of the camera to correspond the ADS-B data to the two-dimensional image;

[0037] S2, label the scene surveillance video sequences in the airport scene surveil...

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Abstract

The invention discloses an ADS-B (Automatic Dependent Surveillance-Broadcast) information-combined deep learning-based airport scene moving target identification method, which combines the idea of change detection motion and static judgment and feature extraction, classification and regression modules in target detection, and improves a time histogram-based background modeling method in a change detection algorithm at the same time. A more accurate background image is obtained; and the existing ADS-B technology of the aircraft is adopted to carry out auxiliary training, so that the feature extraction capability is enhanced, and the detection result is improved. And ideas and advantages of a change detection algorithm and a target detection algorithm are integrated.

Description

technical field [0001] The invention relates to the field of airport target recognition, in particular to a deep learning-based airport scene moving target recognition method combined with ADS-B information. Background technique [0002] In recent years, the global civil aviation passenger capacity has continued to increase, the airport structure has become increasingly complex, and the airport scene has become more and more crowded. It has gradually become more difficult for administrators to visually monitor moving targets on the ground in the field, and the safety hazards of manual command and management have become more and more obvious. In order to meet the needs of automated surface surveillance, a surveillance system covering the entire airport surface area is applied to modern airport surface surveillance through multiple cameras. Compared with other sensors, computer vision technology has unique advantages because the way of disseminating information in video is mor...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/40G06V20/52G06V10/774G06V10/764G06V10/82G06V10/25G06V10/28G06K9/62G06N3/04G06N3/08G06T7/246
CPCG06N3/084G06T7/246G06T2207/10016G06T2207/20081G06T2207/20084G06N3/045G06F18/24G06F18/214
Inventor 张翔张志卓杨瑞菁蒋岚洁李宜航
Owner YANGTZE DELTA REGION INST (QUZHOU) UNIV OF ELECTRONIC SCI & TECH OF CHINA
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