Unmanned aerial vehicle detection system based on spectral analysis

Abstract

The invention provides an unmanned aerial vehicle detection system based on spectral analysis, and the system comprises a signal capturing module and a data processing module, and the signal capturing module is used for converting a received radio frequency signal of a target unmanned aerial vehicle into a baseband signal; and the processing module is used for generating a signal grayscale image according to the baseband signal sent by the signal capturing module, and determining the unmanned aerial vehicle model of the target unmanned aerial vehicle based on the signal grayscale image. The signal capturing module which is simple in structure and convenient to arrange is used for detecting unmanned aerial vehicle signals, and meanwhile equipment cost is low.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a drone detection system based on spectrum analysis. Background Art

[0002] With the development of technology, a large number of commercial small drones have appeared in the sky over cities. They can carry cameras or other sensors for filming and monitoring. Especially when drones enter private territory or sensitive areas, they may collect information or data without permission.

[0003] Current drone detection methods such as continuous wave Doppler radar, software radio spectrum detection and sonar detection equipment are not only too expensive, but also inconvenient to set up and use. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a drone detection system based on spectrum analysis, which detects drone signals through a signal capture module with a simple structure and convenient arrangement, while the equipment cost is low.

[0005] In a first aspect, the present invention provides a UAV detection system based on spectrum analysis, the system comprising a signal capture module and a data processing module, the signal capture module being used to convert a received radio frequency signal of a target UAV into a baseband signal; the processing module being used to generate a signal grayscale image based on the baseband signal sent by the signal capture module, and determining the UAV model of the target UAV based on the signal grayscale image.

[0006] In an optional embodiment, the signal capture module includes an acquisition unit, a dual-branch filtering unit, a mixing unit, a single-branch filtering unit and a detection unit connected in sequence, the acquisition unit includes an antenna for receiving the radio frequency signal of the drone; the dual-branch filtering unit is used to filter the radio frequency signal; the mixing unit is used to mix the filtered radio frequency signal with the oscillation signal to generate an intermediate frequency signal; the single-branch filtering unit is used to filter the intermediate frequency signal; the detection unit is used to detect the baseband signal from the filtered intermediate frequency signal.

[0007] In an optional embodiment, the dual-branch filtering unit includes a first filtering branch and a second filtering branch, wherein the output end of the antenna is connected to the static contact of the first single-pole double-throw switch, and the first moving contact of the first single-pole double-throw switch, the input end of the first frequency band bandpass filter, the output end of the first frequency band bandpass filter, the input end of the first low-noise amplifier, the output end of the first low-noise amplifier, and the first moving contact of the second single-pole double-throw switch are connected in sequence to form a first filtering branch; the second moving contact of the first single-pole double-throw switch, the input end of the second frequency band bandpass filter, the output end of the second frequency band bandpass filter, the input end of the second low-noise amplifier, the output end of the second low-noise amplifier, and the second moving contact of the second single-pole double-throw switch are connected in sequence to form a second filtering branch;

[0008] The processing module is also used to generate a switch signal according to a preset frequency, control the first single-pole double-throw switch and the second single-pole double-throw switch to switch the connection relationship between the static contact and the moving contact, so that the first filter branch or the second filter branch is connected.

[0009] In an optional embodiment, the mixing unit includes a local oscillator and a down-mixer, the local oscillator is used to output an oscillation signal to a first input terminal of the down-mixer; the second input terminal of the down-mixer is connected to a static contact of a second single-pole double-throw switch to obtain a filtered RF signal, the down-mixer mixes the filtered RF signal with the oscillation signal, and outputs an intermediate frequency signal through an output terminal.

[0010] In an optional implementation, the single-branch filtering unit includes an intermediate frequency bandpass filter, an intermediate frequency amplifier, and a narrowband crystal filter connected in sequence; and the detection unit includes a detector.

[0011] In an optional implementation manner, the processing module acquires a baseband signal at a preset frequency, and for each acquired baseband signal, converts the baseband signal into character data;

[0012] Based on the character data received within a preset time length, a signal grayscale image is converted and generated; from the signal grayscale image, the time characteristics corresponding to the drone signal are identified to determine the signal characteristic image; based on the similarity between the signal characteristic image and the sample characteristic image, the target sample characteristic image is determined; the drone model associated with the target sample characteristic image is determined as the drone model of the target drone.

[0013] In an optional embodiment, a storage module is also included, which includes sample feature images and drone models stored in association.

[0014] In an optional embodiment, the processing module is further used to determine the transmission bandwidth of the target UAV based on the size of the signal characteristic image.

[0015] In an optional embodiment, the processing module is further used to determine the signal strength value of the target drone based on the pixel value of the signal feature image.

[0016] In an optional implementation, the processing module is further used to determine the direction of the target UAV based on the magnitude of the signal strength value of the target UAV and the direction of the antenna.

[0017] The present application provides a spectrum analysis-based drone detection system, which includes a signal capture module and a data processing module. The signal capture module is used to output a sampled baseband signal based on the received radio frequency signal of the target drone; the processing module is used to generate a signal grayscale image based on the baseband signal sent by the signal capture module, and determine the drone model of the target drone based on the signal grayscale image. The signal capture module is composed of discrete devices, which are low-cost, small in size and easy to carry. Combined with the software algorithm in the processing module, the information of the invading drone can be determined. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 A structural diagram of a UAV detection system based on spectrum analysis provided in an embodiment of the present application;

[0020] Figure 2 A structural diagram of a signal acquisition module provided in an embodiment of the present application;

[0021] Figure 3 A flowchart of a software algorithm provided in an embodiment of the present application;

[0022] Figure 4 A schematic diagram of a signal grayscale image provided in an embodiment of the present application;

[0023] Figure 5 A schematic diagram of a signal characteristic image provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The technical solution of the present application is applicable to the detection of drones in closed parks.

[0025] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0026] Figure 1A structural diagram of a UAV detection system based on spectrum analysis provided in an embodiment of the present application. The system includes a signal capture module and a data processing module.

[0027] The signal capture module here is a mobile device or non-mobile device composed of discrete devices, which is used to convert the received RF signal of the target drone into a baseband signal. It can be deployed in the park or carried by security personnel.

[0028] The processing module mainly includes an MCU and a software algorithm, which is used to generate a signal grayscale image from the baseband signal sent by the signal capture module, and determine the drone model of the target drone based on the signal grayscale image.

[0029] The drone detection system may further include a display module, which may be a display screen for displaying detected drone information, such as drone model, distance, etc.

[0030] like Figure 2 As shown, Figure 2 A structural diagram of a signal acquisition module provided in an embodiment of the present application. In one embodiment of the present application, the signal acquisition module includes a collection unit, a dual-branch filtering unit, a mixing unit, a single-branch filtering unit and a detection unit connected in sequence.

[0031] The acquisition unit includes an antenna for receiving the radio frequency signal of the drone. The antenna here can be a common antenna or a directional antenna.

[0032] The dual-branch filter unit is used to filter the radio frequency signal. The dual-branch filter unit includes a first filter branch and a second filter branch, wherein the output end of the antenna is connected to the static contact of the first single-pole double-throw switch, the first moving contact of the first single-pole double-throw switch, the input end of the first frequency band bandpass filter, the output end of the first frequency band bandpass filter, the input end of the first low-noise amplifier, the output end of the first low-noise amplifier, and the first moving contact of the second single-pole double-throw switch are connected in sequence to form the first filter branch; the second moving contact of the first single-pole double-throw switch, the input end of the second frequency band bandpass filter, the output end of the second frequency band bandpass filter, the input end of the second low-noise amplifier, the output end of the second low-noise amplifier, and the second moving contact of the second single-pole double-throw switch are connected in sequence to form the second filter branch.

[0033] The processing module is also used to generate a switch signal according to a preset frequency, control the first single-pole double-throw switch and the second single-pole double-throw switch to switch the connection relationship between the static contact and the moving contact, so that the first filter branch or the second filter branch is connected.

[0034] In a specific embodiment, the model of the single-pole double-throw switch can be FM8625H, the first frequency band pass filter is a 5.8G band pass filter (SLFB18-5R500G-01TF), and the second frequency band pass filter is a 2.4G band pass filter (SLFB21-2R50G-09TF), which are used to filter out unnecessary interference and stray signals outside the passband. The model of the first low noise amplifier is BGU7258, and the model of the second low noise amplifier is SKY65405-21. The model of the local oscillator is ADF4350, and the model of the down mixer is ADL5801. The model of the intermediate frequency band pass filter is TA1171A, the model of the intermediate frequency amplifier is BFP740, the model of the narrowband crystal filter is NM7050SA, and the model of the detector is AD8310.

[0035] The single-pole double-throw switch is controlled by the MCU so that the 2.4G filter branch and the 5.8G filter branch are switched alternately at a rate of 0.5ms.

[0036] The frequency mixing unit is used to mix the filtered RF signal with the oscillation signal to generate an intermediate frequency signal. The frequency mixing unit includes a local oscillator and a down-mixer, wherein the local oscillator is used to output the oscillation signal to the first input end of the down-mixer; the second input end of the down-mixer is connected to the static contact of the second single-pole double-throw switch to obtain the filtered RF signal, and the down-mixer mixes the filtered RF signal with the oscillation signal and outputs the intermediate frequency signal through the output end.

[0037] The local oscillator here provides a variable frequency sinusoidal oscillation signal, and the frequency of the down-mixer output signal is equal to the difference between the frequency of the antenna input signal and the local oscillator signal.

[0038] The single-branch filtering unit is used to filter the intermediate frequency signal. The single-branch filtering unit includes an intermediate frequency bandpass filter, an intermediate frequency amplifier, and a narrowband crystal filter which are connected in sequence.

[0039] The IF bandpass filter provides a 125MHz passband with a center frequency of 100MHz, and filters out signals greater than 162.5MHz and less than 37.5MHz. The IF amplifier amplifies the weak signal output by the IF bandpass filter. The narrowband crystal filter is a crystal filter with a center frequency of 100MHz and a passband bandwidth less than or equal to 4Khz, and has extremely high out-of-band suppression capability.

[0040] The detection unit is used to detect the baseband signal from the filtered intermediate frequency signal. The detection unit includes a detector. The detector can convert the input RF energy into a voltage output according to a certain ratio.

[0041] like Figure 3 As shown, Figure 3A flowchart of a software algorithm provided for an embodiment of the present application. The processing module acquires a baseband signal at a preset frequency, and converts the baseband signal into character data for each baseband signal acquired. Based on the character data received within a preset time length, a signal grayscale image is converted and generated. From the signal grayscale image, the time characteristics corresponding to the drone signal are identified to determine the signal feature image. Based on the similarity between the signal feature image and the sample feature image, a target sample feature image is determined. The drone model associated with the target sample feature image is determined as the drone model of the target drone.

[0042] In a specific embodiment, the baseband signal output by the signal capture module every 0.5 ms is converted into 16-bit data after passing through the ADC of the MCU and stored in the buffer array.

[0043] The RF signal input by the drone is transmitted to the down-mixer on the board after low-noise amplification. The down-mixer also receives the sine wave signal of 5625MHz~5750MHz, 1ms timing and 1MHz frequency interval emitted by the local oscillator.

[0044] For example, at time 0, the local oscillator is controlled by the program to transmit a 5625MHz signal, at time 1ms, the local oscillator is controlled by the program to transmit a 5626MHz signal, at time 2ms, the local oscillator is controlled by the program to transmit a 5627MHz signal, at time 3ms, the local oscillator is controlled by the program to transmit a 5628MHz signal, and so on, all the way to 5750MHz, and then return to 5625Mhz and start again.

[0045] At 50ms, suppose there is a drone nearby that happens to continuously transmit video stream signals at 5775MHz with a 20MHz frequency bandwidth, that is, the real-time transmission frequency covers 5775MHz to 5795MHz. At this time, the down-mixer can output a strong RF signal of (5775-5675) = 100MHz. After this RF signal passes through a 100MHz crystal filter and is input into the detector, it can also output a higher level baseband signal. This baseband signal is converted into 16-bit data after passing through the ADC of the MCU and stored in the buffer array. By analogy, at 51ms, the buffer array can also store 16-bit data that can reflect the strength of the drone's transmission signal at the corresponding moment.

[0046] Until 71ms, because it has exceeded the drone's transmission frequency range, the buffer array begins to store weaker environmental noise signals. It returns to 0ms and starts the next round of the same sweep frequency reception cycle. After 80 cycles, the data of the entire buffer array is converted into a signal grayscale image as shown below: Figure 4 As shown in the figure, the vertical axis of the signal grayscale image is the bandwidth of the frequency sweep, 0MHz corresponds to 0ms, and the horizontal axis is time, a total of 1000ms.

[0047] Then, the target recognition algorithm is used to identify and crop the signal feature image from the signal grayscale image. Figure 5 It should be noted that the signal characteristic image only includes the main band part, but does not include the out-of-band stray ghost part.

[0048] Since the digital image signal transmitted by the drone is in the form of data packets, each packet has a fixed transmission time and time interval. Different types of image transmission systems have their own time characteristics, so it is possible to determine whether it is a certain type of drone by comparing the collected stripes, and it can be distinguished from other interference signals, such as WiFi and Bluetooth signals.

[0049] Therefore, the detection information of the present application may also include a storage module, which includes associated stored sample feature images and drone models. The sample feature images here are generated in advance by processing radio frequency signals of different drones.

[0050] The data array corresponding to the signal feature image is moved along the ordinate and correlation calculation is performed with the data array corresponding to the same ordinate of the sample feature image. When the correlation is maximum and greater than a preset threshold, the model of the target drone can be determined.

[0051] The present application provides a drone detection system based on spectrum analysis, in which the signal capture module is composed of discrete devices, has low cost, is small in size and is easy to carry. Combined with the software algorithm in the processing module, the information of the invading drone can be determined.

[0052] In one embodiment of the present application, the processing module is further used to determine the transmission bandwidth of the target drone based on the size of the signal characteristic image, and to determine the signal strength value of the target drone based on the pixel value of the signal characteristic image, and to determine the direction of the target drone based on the size of the signal strength value of the target drone and the direction of the antenna.

[0053] The transmitting frequency of the drone is the ordinate + the starting frequency of the local oscillator, the transmitting bandwidth is the width of the stripe on the ordinate, and the signal strength is the cumulative sum of all elements of the collected stripe image data array. When ranging is required, this can be used as a basis to estimate the distance between the drone and the antenna. When direction finding is required, a directional antenna can be used. When the antenna points to the location with the maximum signal strength, it is the direction of the drone. And the determined drone information can be displayed to the user.

[0054] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0055] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0056] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0057] It should be noted that if the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM) random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0058] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0059] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A UAV detection system based on spectrum analysis, characterized in that: The system includes a signal acquisition module and a data processing module. The signal capture module is used to convert the received RF signal of the target drone into a baseband signal output; The processing module is used to generate a signal grayscale image from the baseband signal sent by the signal capture module, and determine the drone model of the target drone based on the signal grayscale image.

2. The system according to claim 1, characterized in that The signal acquisition module includes a collection unit, a dual-branch filtering unit, a mixing unit, a single-branch filtering unit and a detection unit connected in sequence. The acquisition unit includes an antenna for receiving a radio frequency signal from the drone; The dual-branch filtering unit is used to filter the radio frequency signal; The frequency mixing unit is used to mix the filtered radio frequency signal with the oscillation signal to generate an intermediate frequency signal; The single-branch filtering unit is used to filter the intermediate frequency signal; The detection unit is used to detect the baseband signal from the filtered intermediate frequency signal.

3. The system according to claim 2, characterized in that The dual-branch filtering unit comprises a first filtering branch and a second filtering branch; The output end of the antenna is connected to the static contact of the first single-pole double-throw switch. The first moving contact of the first single-pole double-throw switch, the input end of the first frequency band pass filter, the output end of the first frequency band pass filter, the input end of the first low noise amplifier, the output end of the first low noise amplifier, and the first moving contact of the second single-pole double-throw switch are connected in sequence to form a first filtering branch; The second moving contact of the first single-pole double-throw switch, the input end of the second frequency band band-pass filter, the output end of the second frequency band band-pass filter, the input end of the second low-noise amplifier, the output end of the second low-noise amplifier, and the second moving contact of the second single-pole double-throw switch are connected in sequence to form a second filtering branch; The processing module is also used to generate a switch signal according to a preset frequency, and control the first single-pole double-throw switch and the second single-pole double-throw switch to switch the connection relationship between the static contact and the moving contact, so that the first filter branch or the second filter branch is connected.

4. The system according to claim 3, characterized in that The frequency mixing unit comprises a local oscillator and a down mixer, The local oscillator is used to output an oscillation signal to a first input terminal of the down-mixer; The second input end of the down-mixer is connected to the static contact of the second single-pole double-throw switch to obtain the filtered radio frequency signal. The down-mixer mixes the filtered radio frequency signal with the oscillation signal and outputs the intermediate frequency signal through the output end.

5. The system according to claim 4, characterized in that The single-branch filtering unit comprises an intermediate frequency bandpass filter, an intermediate frequency amplifier, and a narrowband crystal filter connected in sequence; The detection unit includes a detector.

6. The system according to claim 1, characterized in that The processing module acquires the baseband signal according to the preset frequency, and converts the baseband signal into character data for each acquired baseband signal; Based on the character data received within a preset time length, convert and generate a signal grayscale image; From the signal grayscale image, identifying the time feature corresponding to the drone signal to determine a signal feature image; Determining a target sample feature image based on the similarity between the signal feature image and the sample feature image; The drone model associated with the target sample feature image is determined as the drone model of the target drone.

7. The system according to claim 6, characterized in that It also includes a storage module, which includes associated stored sample feature images and drone models.

8. The system according to claim 6, characterized in that The processing module is also used to determine the transmission bandwidth of the target UAV based on the size of the signal characteristic image.

9. The system according to claim 6, characterized in that The processing module is also used to determine the signal strength value of the target drone based on the pixel value of the signal feature image.

10. The system according to claim 9, characterized in that The processing module is also used to determine the direction of the target UAV based on the signal strength value of the target UAV and the direction of the antenna.

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