A UAV detection method based on the periodicity of UAV downlink signals

Abstract

The invention discloses an unmanned aerial vehicle detection method based on the periodicity of a downlink signal of an unmanned aerial vehicle. The method comprises the steps of firstly collecting adownlink communication radio frequency signal between the unmanned aerial vehicle and a remote controller; filtering the downlink radio frequency signal, firstly filtering the signal of a non-unmannedaerial vehicle downlink frequency band, conducting low-pass filtering, and according to whether the amplitude of the filtered signal exceeds a threshold value, obtaining the time when the unmanned aerial vehicle transmits the radio frequency signal, thereby extracting the standard period and the standard signal empty ratio of the unmanned aerial vehicle transmitting the radio frequency signal; finally collecting the radio frequency signal in the environment, and performing filtering processing to determine whether the period of the filtered radio frequency signal and the signal empty ratio match the standard period and the standard signal empty ratio, thereby achieving the detection of the unmanned aerial vehicle periodically transmitting the downlink signal. The method has a great application value.

Description

technical field [0001] The invention belongs to the field of unmanned aerial vehicle detection, and relates to an unmanned aerial vehicle detection method based on the periodicity of the downlink signal of the unmanned aerial vehicle. Background technique [0002] In recent years, the UAV market has developed rapidly, and the number of UAVs has shown a blowout growth; at the same time, incidents of "black flying" and "indiscriminate flying" of UAVs have emerged in an endless stream, which has brought serious threats to public safety and personal privacy. Therefore, the supervision and defense of drones has become the focus of research in academic and industrial circles in various countries. [0003] At present, the detection methods used for drones mainly include radar, audio, video and radio frequency. Since the illegal flight of UAVs often occurs in complex terrain such as buildings, near prisons, etc., it is almost impossible to use radar to identify UAVs with various ec...

AI Technical Summary

Problems solved by technology

Since the illegal flight of UAVs often occurs in complex terrain such as buildings, near prisons, etc., it is almost impossible to use radar to identify UAVs with various echoes.

Using sound to detect drones is easy to cause false detection, because the sound characteristics of drones are easily confused with other types of sounds, such as cicadas, electric fans, etc.

Video detection UAVs are also easily affected by the surrounding environment, and it is difficult to be detected if they are blocked by leaves, etc.

The content based on radio frequency detection is very small, and the current papers are also carried out around the changes in the strength of the WiFi signal between the drone and the remote control. Communication between drones no longer uses WiFi technology, so it is almost impossible to detect such drones using existing WiFi methods

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