Airport low-slow small target prevention and control method based on photoelectric image automatic identification

Abstract

The invention discloses an airport low-slow small target prevention and control method based on photoelectric image automatic identification. The method comprises the following steps of obtaining a plurality of images of the low-slow small targets from a network, and carrying out the on-site actual measurement on, and collecting the plurality of images of the low-slow small targets; performing thefeature extraction on each image, classifying the target types corresponding to the images according to the extracted image features, and obtaining a low-slow small target classifier; preprocessing the to-be-prevented and controlled target image, extracting the image features, and then inputting the features into the classifier to obtain the type of the to-be-prevented and controlled target; anddetermining the position of the to-be-prevented and controlled target, and driving the corresponding prevention and control equipment to work in combination with the type of the to-be-prevented and controlled target. According to the method, the multiple prevention and control strategies of the airport area are achieved by classifying different targets, the optimal combination of different low-slow-speed small prevention and control devices is achieved, the influence of the low-slow small targets on the airspace of the airport is greatly reduced, the defects of a traditional manual monitoringairspace and the limitation of a single control strategy are overcome, and the prevention and control efficiency and precision of the low-slow small targets are improved.

Description

Technical field [0001] The invention belongs to the technical field of intelligent, low, slow and small target prevention and control, in particular to an airport low, slow and small target prevention and control method based on automatic photoelectric image recognition. Background technique [0002] "Low, slow, small" targets refer to aircraft and floating objects that have low-altitude, ultra-low-altitude flight, slow speed, small size, and difficulty in detection. Mainly include light and ultralight aircraft, light helicopters, gliders, delta wings, powered delta wings, powered parachutes, paragliders, hot air balloons, airships, unmanned aerial vehicles, aviation models, aerospace models, floating balloons, tethered balloons, etc. These objects are low-cost, simple to control, convenient to carry, easy to obtain, and have a sudden lift-off, difficult to find and handle, and are easily used as tools for carrying explosives, dropping biochemical agents, and disseminating leafle...

AI Technical Summary

Problems solved by technology

However, due to the small radar reflection area of ​​low, slow and small targets and birds, and the Doppler effect caused by the slow flight speed is not obvious, it is easy to cause target misjudgment

In addition, optical detection is mainly composed of infrared automatic search technology, image processing technology and high-precision turntable control technology, but there are disadvantages such as slow image acquisition and processing speed, low scanning efficiency for large airspace, and inability to accurately calculate the target position.

The existing low-slow and small-bird detection is becoming more and more mature, including the American Merlin radar system, the Canadian Goshawk radar system, the Beijing Zhongke Robin radar system, and the Wuhan leading general aviation airport bird detection radar system, etc. Some of them have already achieved detection and repelling Linkage, but did not propose classified prevention and control strategies and methods

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