CN-121982579-A - Unmanned aerial vehicle detection method and equipment

CN121982579ACN 121982579 ACN121982579 ACN 121982579ACN-121982579-A

Abstract

The invention relates to the technical field of unmanned aerial vehicle detection and provides an unmanned aerial vehicle detection method and equipment, wherein the method comprises the steps of scanning a frequency band, scanning an unmanned aerial vehicle image transmission signal, and screening out frequency points suspected to have image signals according to the intensity of a received signal; the method comprises the steps of video receiving, sequentially performing frequency matching on AV signals corresponding to the screened frequency points, switching one path of AV signals each time through a video signal switch, outputting the AV signals to the rear end, performing signal processing, converting the AV signals into digital video signals through a video encoder, outputting the digital video signals to an image processing module, performing image recognition, judging whether the video signals belong to real and effective image information after a pixel matrix is extracted by the image processing module, determining a target, comprehensively judging whether a certain frequency point belongs to a signal transmitted by unmanned aerial vehicle image transmission by combining the frequency point information identified by a main control unit, and performing joint interference, wherein the image processing module can also link a detection result with interference equipment. The unmanned aerial vehicle detection method improves unmanned aerial vehicle detection efficiency and reduces unmanned aerial vehicle reaction cost.

Inventors

ZHANG WENYUE
CHEN LI
Nie Fanru
MA XIN
Sun Huangshuaian
YANG FAN
DENG WEIDONG

Assignees

北京航天光华电子技术有限公司

Dates

Publication Date: 20260505
Application Date: 20251224

Claims (10)

1. The unmanned aerial vehicle detection method is characterized by comprising the following steps: Scanning a frequency band where an unmanned aerial vehicle image signal currently in a detection range is located, and screening out frequency points with image signals according to the intensity of the received unmanned aerial vehicle image signal; Sequentially receiving the unmanned aerial vehicle image signal corresponding to the screened frequency points in a frequency-to-frequency manner, and switching one frame of unmanned aerial vehicle image signal each time through a video signal switch and outputting the unmanned aerial vehicle image signal to the rear end; The image signal of the unmanned aerial vehicle of a frame output to the back end is converted into a digital video signal; Performing image recognition, extracting a pixel matrix from a digital video signal, judging whether the frame digital video signal belongs to real and effective image information, and executing subsequent processing if the frame digital video signal belongs to the real and effective image information; Judging whether the frequency point corresponding to the current effective image information is in the frequency point screened out by the image signal, if so, the frequency point corresponding to the current effective image information is a transmitting frequency point used by the unmanned aerial vehicle image transmission signal.
2. The method of claim 1, wherein the current effective unmanned aerial vehicle image signal is displayed on a human-computer interaction interface, and meanwhile, a command center is reported, and the combined interference equipment performs interference of corresponding frequency points on the unmanned aerial vehicle according to requirements.
3. The method of claim 1, wherein the frequency band scan comprises: scanning a plurality of unmanned aerial vehicle image transmitted frequency point signals in real time, wherein the frequency point comprises a conventional frequency band and an unconventional frequency band within a range of 1-8 GHz; Outputting different analog voltage values according to the intensity of the image signal, and screening out frequency points with image signals according to the voltage values.
4. The method of claim 1, wherein the video receiving comprises: frequency point alignment is carried out on all frequency points with image signals; sequentially receiving the image signals aligned with the frequency points; and switching the received image signals through a video signal switch so as to switch unmanned aerial vehicle image signals of different frequency points and output the signals to the rear end.
5. The method of claim 1, wherein the digital video signal is an RSTP data stream.
6. The method of claim 5, wherein the image recognition comprises: Outputting a full black reference video stream with a time stamp when no video is input at the rear end, and constructing a real-time data stream through the full black reference video stream and an input RSTP data stream; Performing pixel level analysis on each video stream frame in the real-time data stream, traversing all pixel units in the frame to obtain B, G, R three-channel numerical values of each pixel unit, marking as black pixels when B epsilon [0, 120)% G epsilon [0, 120)% R epsilon [0, 120) is satisfied, calculating the black pixel duty ratio P= (sigma black pixel number)/resolution value, and judging that the current frame is an invalid image when P exceeds a set threshold value theta, otherwise, judging that the current frame is true and effective image information.
7. The method of claim 6, wherein the threshold θ is a value that satisfies: θ=α× (1+log 2 (w×h/10 6 )), where w, h are the compensation coefficients for video resolution, α∈ [0.85,0.95 ].
8. The method of claim 6, wherein the video processing pipeline is constructed based on an OpenCV library, and wherein asynchronous capture of video stream frames stored in a BGR color space in a ring buffer is achieved by VideoCapture classes.
9. Unmanned aerial vehicle detects equipment, its characterized in that includes: The system comprises a main control unit, a video signal switch, a radio frequency signal receiving module, a video signal switch, a video signal processing unit and a video signal processing unit, wherein the main control unit is used for receiving the video signal of the unmanned aerial vehicle; The image processing unit is used for processing each frame of received unmanned aerial vehicle image signal, converting the received unmanned aerial vehicle image signal into a digital video signal, extracting a pixel matrix, judging whether the video signal belongs to real and effective image information or not, and if the video signal belongs to the real and effective image information, transmitting a frequency point of the image information to the main control unit; the main control unit identifies the received frequency point, judges whether the frequency point is in the frequency point range with the image signal sent by the radio frequency signal receiving module, and if so, the frequency point is a transmitting frequency point used by the unmanned aerial vehicle image transmission signal.
10. The device of claim 9, further comprising a man-machine interaction unit, wherein the main control unit sends the unmanned aerial vehicle graph signal corresponding to the identified frequency point to the man-machine interaction unit for display, and meanwhile, the identified frequency point is reported to the command center, and the combined interference device performs interference of the corresponding frequency point to the unmanned aerial vehicle according to the requirement.

Description

Unmanned aerial vehicle detection method and equipment Technical Field The invention relates to the technical field of unmanned aerial vehicle detection, and provides an unmanned aerial vehicle detection method and equipment. Background Unmanned aerial vehicle detection in complex urban environments has been an industry difficulty. Currently, detecting unmanned aerial vehicle flight control signals is a main method for monitoring commercial unmanned aerial vehicles, but under urban complex terrain environments, unmanned aerial vehicle flight control signals are easily shielded by high buildings, and flight control equipment is farthest from a detection system, so that signals are difficult to capture. Compared with the flight control signal, the image transmission signal is generated by the unmanned aerial vehicle, is not easy to be shielded, and has high signal power and easy capture. Therefore, the working range of the unmanned aerial vehicle detection system can be effectively expanded by detecting the image transmission signal. The mainstream commercial unmanned aerial vehicle all uses certain radio frequency band according to international standard or national regulation, but if meet the special person that possesses certain anti-reconnaissance ability, through the repacking, become comparatively cold frequency channel with unmanned aerial vehicle image signal transmission, then the user need adopt the coverage wider, the more advanced equipment of technique detects. Therefore, it is necessary to develop a set of mapping signal detection system with wide frequency band, which covers most of the frequency points between the radio frequency bands of 1 GHz-8 GHz, so as to effectively protect the security of the high-sensitivity area. Disclosure of Invention The unmanned aerial vehicle detection method and equipment provided by the invention have the advantages that the defects of the prior art are overcome, unmanned aerial vehicle signals can be detected rapidly, and potential safety hazards brought to society by unmanned aerial vehicles are effectively reduced. The technical scheme of the invention is that the unmanned aerial vehicle detection method comprises the following steps: Scanning a frequency band where an unmanned aerial vehicle image signal currently in a detection range is located, and screening out frequency points with image signals according to the intensity of the received unmanned aerial vehicle image signal; Sequentially receiving the unmanned aerial vehicle image signal corresponding to the screened frequency points in a frequency-to-frequency manner, and switching one frame of unmanned aerial vehicle image signal each time through a video signal switch and outputting the unmanned aerial vehicle image signal to the rear end; The image signal of the unmanned aerial vehicle of a frame output to the back end is converted into a digital video signal; Performing image recognition, extracting a pixel matrix from a digital video signal, judging whether the frame digital video signal belongs to real and effective image information, and executing subsequent processing if the frame digital video signal belongs to the real and effective image information; Judging whether the frequency point corresponding to the current effective image information is in the frequency point screened out by the image signal, if so, the frequency point corresponding to the current effective image information is a transmitting frequency point used by the unmanned aerial vehicle image transmission signal. Preferably, the current effective unmanned aerial vehicle image signal is displayed on a man-machine interaction interface, and meanwhile, a command center is reported, and the combined interference equipment performs interference of corresponding frequency points on the unmanned aerial vehicle according to requirements. Preferably, the frequency band scanning includes: scanning a plurality of unmanned aerial vehicle image transmitted frequency point signals in real time, wherein the frequency point comprises a conventional frequency band and an unconventional frequency band within a range of 1-8 GHz; Outputting different analog voltage values according to the intensity of the image signal, and screening out frequency points with image signals according to the voltage values. Preferably, the video receiving includes: frequency point alignment is carried out on all frequency points with image signals; sequentially receiving the image signals aligned with the frequency points; and switching the received image signals through a video signal switch so as to switch unmanned aerial vehicle image signals of different frequency points and output the signals to the rear end. Preferably, the digital video signal is an RSTP data stream. Preferably, the image recognition includes: Outputting a full black reference video stream with a time stamp when no video is input at the rear end, and constructing a real-time data stream throu