Detection system and detection method for low-altitude slow small targets

Abstract

The invention provides a detection system and detection method for low-altitude slow small targets. The detection method includes the following steps that: electromagnetic waves are emitted through adetection radar, electromagnetic waves reflected by a target are received, and the point trace and flight trace information of the target is obtained; unmanned aerial vehicle frequency band electromagnetic signals are received through spectrum detection, signal electromagnetic feature information is extracted, and is compared with unmanned aerial vehicle remote control and telemetry signal electromagnetic features in a database, whether the signals are unmanned aerial vehicle signals is judged, unmanned aerial vehicle direction finding information is obtained; the visible light video and infrared video information of the target is obtained through photoelectric detection; broadcast signals emitted from an onboard type ADS-B system are monitored in real time, the point trace and flight trace information and identity information of the cooperative unmanned aerial vehicle target are obtained; all the above information is integrated, so that the comprehensive information including point and flight trace, category, cooperative / non-cooperative identity information and tracking video information of the target can be obtained. Compared with the prior art, the detection system and detectionmethod can realize three-dimensional positioning, speed measurement, category identification and point trace generation of a low-altitude unmanned aerial vehicle target, a monitor the cooperative target in real time so as to obtain a low-altitude flight real-time trend.

Description

technical field [0001] The invention relates to a low-altitude slow-speed small target detection system and a detection method thereof, and relates to the field of air traffic control low-altitude target detection. Background technique [0002] In recent years, civilian small and micro UAVs have developed rapidly, and the number of UAVs has increased geometrically, but the management of UAVs has lagged behind seriously. The phenomenon of "black flying" and "random flying" of drones is becoming more and more serious, and drones pose a new threat to the flight safety of civil aviation and military aviation. [0003] In December 2013, a drone flew randomly at the Capital Airport, threatening flight safety and causing multiple flight delays. In July 2014, an Airbus A320 in London narrowly missed a drone and nearly caused disaster. In May 2017, drones were spotted several times at Sichuan Shuangliu Airport and its waterways, causing many planes to make forced landings at nearby...

AI Technical Summary

Problems solved by technology

[0003] In December 2013, a drone flew randomly at the Capital Airport, threatening flight safety and causing multiple flight delays

July 2014: Airbus A320 narrowly misses drone in London, narrowly causing disaster

In May 2017, drones were found on the Shuangliu Airport and the waterway in Sichuan Province many times, causing many planes to make forced landings at nearby airports, resulting in multiple flight delays and losses of tens of millions of yuan

[0005] At present, the detection, identification and monitoring methods for small and micro UAV targets are single, and it is difficult to achieve rapid three-dimensional positioning of UAV targets, classification and identification of targets, and effective surveillance of cooperative UAVs, and it is difficult to meet the requirements of all-weather and all-weather work

Ning Huansheng and others proposed a mobile radar bird detection device [Ning Huansheng; Chen Weishi; Liu Wenming; Song Jianmin. Mobile radar bird detection device], which can only realize two-dimensional detection of targets, but cannot realize target classification and recognition

Shan Zhen et al. proposed an anti-UAV system based on UAV remote control telemetry signal monitoring and direction-finding cross-location [Shan Zhen; Zhou Ping; Jin Lingzhi. Anti-UAV passive detection and direction-finding positioning system], the system The detection range is small, the positioning accuracy is poor, and the identity information of the drone cannot be obtained

Cai Mao and others proposed an anti-UAV detection system including radar and photoelectricity [Cai Mao; Yang Qin. Anti-UAV detection system], the system is difficult to achieve target recognition when the visual conditions are not good, and cannot detect Collaborative target for monitoring

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