Unmanned aerial vehicle intelligent countering system, method, equipment and medium

Abstract

The invention discloses an unmanned aerial vehicle intelligent countering system, method and device and a medium, and relates to the technical field of unmanned aerial vehicles, and the system comprises a detection and identification module, a positioning and direction finding module, a signal interference module and a path guiding module which are in communication connection in pairs; the detection identification module is used for determining whether the unmanned aerial vehicle exists in the target area; the positioning direction finding module is used for determining the real-time position of the unmanned aerial vehicle; the signal interference module is used for interfering a communication link between the unmanned aerial vehicle and the corresponding controller and a positioning signal of the unmanned aerial vehicle based on the real-time position; the path guiding module is used for transmitting an induction signal to the unmanned aerial vehicle based on the real-time position and generating a dynamic induction path, and the dynamic induction path is used for guiding the unmanned aerial vehicle to leave the target area under the condition that the unmanned aerial vehicle receives the induction signal. The invention aims to solve the technical problems of low fault tolerance and poor adaptability in the induction process in the existing unmanned aerial vehicle countering method.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) technology, and in particular to an intelligent UAV countermeasure system, method, device and medium. Background Technology

[0002] In response to the reconnaissance, sabotage and attack activities of drones in target areas, existing technologies often employ countermeasures such as navigation deception. This method simulates and transmits false satellite navigation signals to mislead the drone's flight control system, causing it to deviate from the preset flight path, thereby achieving non-contact countermeasures.

[0003] However, such decoy systems lack accurate real-time positioning and continuous tracking of the target drone's location, making it difficult to dynamically generate an induction trajectory that matches the real airspace conditions. This results in low fault tolerance and poor adaptability in the induction process, low overall countermeasure efficiency, and difficulty in dealing with highly dynamic drone targets. Summary of the Invention

[0004] The main purpose of this application is to provide an intelligent countermeasure system, method, device and medium for unmanned aerial vehicles (UAVs), aiming to solve the technical problems of low fault tolerance and poor adaptability in the induction process of existing UAV countermeasure methods.

[0005] To achieve the above objectives, this application provides an intelligent countermeasure system for unmanned aerial vehicles (UAVs), comprising: a detection and identification module, a positioning and direction finding module, a signal jamming module, and a path guidance module, all connected in pairs; the detection and identification module is used to determine whether a UAV exists in a target area; the positioning and direction finding module is used to determine the real-time position of the UAV; the signal jamming module is used to jam the communication link between the UAV and its corresponding controller and the UAV's positioning signal based on the real-time position; the path guidance module is used to transmit an inducement signal to the UAV based on the real-time position and generate a dynamic inducement path, wherein the dynamic inducement path is used to guide the UAV away from the target area when the UAV receives the inducement signal.

[0006] Optionally, the detection and identification module is further configured to identify the model of the drone when the drone is present in the target area; the positioning and direction finding module is further configured to receive the model of the drone and calibrate the real-time position of the drone based on the model.

[0007] Optionally, the positioning and direction finding module is also used to determine the position of the drone pilot; the system also includes a pilot processing module, which is used to process the drone pilot based on the position of the drone pilot.

[0008] Optionally, the detection and identification module includes a spectrum sensing unit and an identity recognition unit; the spectrum sensing unit is used to identify the radio frequency signals of drones in the target area, and determine whether there are drones in the target area based on the drone radio frequency signals; the identity recognition unit has a built-in drone model library, and the identity recognition unit is used to identify the model of the drone based on the drone model library, wherein the drone model library contains several drone models.

[0009] Optionally, the signal jamming module includes a digital baseband unit and an analog radio frequency unit; the digital baseband unit is used to generate an interference signal based on the real-time location; the analog radio frequency unit is connected to the digital baseband unit, and the analog radio frequency unit is used to convert the interference signal to the target frequency band, and use the converted interference signal to interfere with the communication link between the UAV and the corresponding controller and the positioning signal of the UAV.

[0010] Optionally, the path guidance module includes an induction signal generation unit and an induction path generation unit; the induction signal generation unit is used to generate an induction signal based on the real-time location, and the induction signal has the same signal structure as the positioning signal of the UAV; the induction path generation unit is used to generate a dynamic induction path based on the real-time location.

[0011] Optionally, the induced path generation unit is configured with a GPS positioning algorithm; the induced path generation unit is also used to simulate a positioning process using the GPS positioning algorithm, and the simulated positioning process is used to update the dynamic induced path of the UAV.

[0012] Furthermore, to achieve the above objectives, this application also provides an intelligent countermeasure method for unmanned aerial vehicles (UAVs), which applies the above system and includes: determining whether a UAV exists in a target area; determining the real-time location of the UAV; interfering with the communication link between the UAV and its corresponding controller and the UAV's positioning signal based on the real-time location; transmitting an induction signal to the UAV based on the real-time location and generating a dynamic induction path, wherein the dynamic induction path is used to guide the UAV away from the target area when the UAV receives the induction signal.

[0013] This application also provides a drone intelligent countermeasure device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the above-described drone intelligent countermeasure method.

[0014] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described intelligent countermeasures method against unmanned aerial vehicles.

[0015] This application proposes an intelligent countermeasure system, method, device, and medium for unmanned aerial vehicles (UAVs). First, a detection and identification module monitors the target area in real time, enabling rapid and accurate determination of UAV intrusion and providing basic information for subsequent countermeasures. Second, a positioning and direction-finding module determines the UAV's real-time position, and a signal jamming module, based on the real-time position information, interferes with the communication link between the UAV and the controller, as well as the positioning signal, cutting off the UAV's normal communication with the outside world and rendering it unable to control commands and locate itself. Finally, a path guidance module generates an induction signal with the same structure as the UAV's original positioning signal, guiding it to leave the target area along a dynamic induction path. This effectively solves the problems of low fault tolerance and poor adaptability in the induction process of existing technologies. Attached Figure Description

[0016] Figure 1 This is a structural block diagram of the intelligent anti-drone system provided in the embodiments of this application; Figure 2 This is a schematic diagram of the GPS positioning principle provided in an embodiment of this application; Figure 3 This is a schematic diagram of satellite positioning relay navigation deception provided in an embodiment of this application; Figure 4 A flowchart of the intelligent countermeasure method for unmanned aerial vehicles provided in the embodiments of this application; Figure 5 This is a schematic diagram of the structure of the intelligent countermeasure device for unmanned aerial vehicles provided in an embodiment of this application.

[0017] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0018] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0019] In response to the reconnaissance, sabotage and attack activities of drones in target areas, existing technologies often employ countermeasures such as navigation deception. This method simulates and transmits false satellite navigation signals to mislead the drone's flight control system, causing it to deviate from the preset flight path, thereby achieving non-contact countermeasures.

[0020] However, such decoy systems lack accurate real-time positioning and continuous tracking of the target drone's location, making it difficult to dynamically generate an induction trajectory that matches the real airspace conditions. This results in low fault tolerance and poor adaptability in the induction process, low overall countermeasure efficiency, and difficulty in dealing with highly dynamic drone targets.

[0021] To address the aforementioned issues, this application provides an intelligent countermeasure system, method, device, and medium for unmanned aerial vehicles (UAVs). The solution described in this application is detailed below.

[0022] Figure 1 The present application provides a structural block diagram of an intelligent anti-drone system 100, which may include: a detection and identification module 110, a positioning and direction finding module 120, a signal jamming module 130, and a path guidance module 140 connected in pairs; the detection and identification module 110 is used to determine whether there is an unmanned aerial vehicle (UAV) in the target area; the positioning and direction finding module 120 is used to determine the real-time position of the UAV; the signal jamming module 130 is used to jam the communication link between the UAV and the corresponding controller and the UAV's positioning signal based on the real-time position; the path guidance module 140 is used to transmit an inducement signal to the UAV based on the real-time position and generate a dynamic inducement path, wherein the dynamic inducement path is used to guide the UAV to leave the target area when the UAV receives the inducement signal.

[0023] It should be noted that the UAV's data link includes core components such as a radio frequency transceiver, a modem module, and an antenna. The communication stability of the data link determines whether the UAV can fly safely in the target area. In this embodiment, the signal jamming module 130 can interfere with the UAV's data link, preventing the UAV from transmitting effective information with the remote control device and interfering with the remote control device's control of the UAV.

[0024] It is understood that the interference mentioned in this embodiment refers to communication interference with data links. Communication interference is a general term for electronic attack actions aimed at disrupting or interfering with the information (image or data) transmission process of local communication systems. In particular, a communication interference system can disrupt the radio communication process by emitting a specific form of electromagnetic signal associated with the communication signal, thereby causing communication paralysis.

[0025] In the specific implementation process, the detection and identification module 110 can scan the frequency band from 300MHz to 6GHz in the target area using spectrum sensing technology to determine whether there is a drone signal in the target area. If there is a drone signal, the module will compare the signal characteristics of the drone signal with the built-in artificial intelligence classification algorithm and drone model library (including hundreds of models such as DJI, Autel, Dahua, and EHang) to determine the specific model of the drone.

[0026] The positioning and direction finding module 120 is connected to the detection and identification module 110 and receives the UAV signal output by the detection and identification module 110 to determine the UAV's real-time position. Specifically, the positioning and direction finding module 120 uses two or more detection devices and employs a cross-positioning algorithm (when two devices are deployed) or a TDOA (Time Difference of Arrival) positioning algorithm (when three or more devices are deployed) to accurately determine the UAV's real-time position and simultaneously calculate the position of the UAV pilot (i.e., the UAV remote controller operator).

[0027] The signal jamming module 130 connects the detection and identification module 110 and the positioning and direction finding module 120. Based on the real-time position of the UAV provided by the positioning and direction finding module 120, the signal jamming module 130 can precisely jam the communication link between the UAV and its corresponding controller, as well as the UAV's positioning signal. Specifically, the signal jamming module 130 includes a digital baseband unit and an analog radio frequency unit. The digital baseband unit can detect and synchronize UAV signals and generate jamming signals based on the UAV's real-time position. The analog radio frequency unit can convert the jamming signal to the target frequency band and finally transmit it through an antenna to jam the communication link (uplink) between the UAV and its corresponding controller, as well as the UAV's positioning signal.

[0028] The path guidance module 140 is connected to the signal jamming module 130. The path guidance module 140 can generate and transmit an inducement signal, i.e., a false navigation signal, based on the real-time position of the UAV. In addition, the path guidance module 140 can also calculate the forwarding delay of the inducement signal, causing the UAV navigation system to calculate an incorrect self-position, thereby generating a dynamic inducement path to guide the UAV to a preset safe area.

[0029] In one embodiment, the detection and identification module 110 can identify the model information of the UAV, which is transmitted in real time to the positioning and direction finding module 120 and the signal jamming module 130. The positioning and direction finding module 120 can use the model information to determine the communication frequency band and frequency hopping mode of the UAV model, thereby calibrating the scanning parameters and improving the positioning speed and positioning accuracy.

[0030] Specifically, the detection and identification module 110 includes a spectrum sensing unit and an identity recognition unit. The spectrum sensing unit is equipped with a wideband radio frequency receiver and can identify the radio frequency signals of drones in the target area. The identity recognition unit is equipped with a high-performance embedded DSP as the core processor, which contains a drone model library. It can use artificial intelligence classification algorithms to compare and match signal features to obtain the specific model of the drone.

[0031] In one embodiment, the location information of the drone pilot calculated by the positioning and direction-finding module 120 is uploaded to the system terminal. The system may also include a pilot processing module, which can allocate resources and process the pilot based on the location information. It is understood that the pilot processing module can be a software logic module or it can be linked with physical security forces.

[0032] In one embodiment, the signal interference module 130 is configured with a first signal generator and a power amplifier. The first signal generator and the power amplifier can generate various forms of interference waveforms according to interference guidance parameters, thus obtaining an interference signal. It should be noted that the first signal generator is a DSP+FPGA architecture, capable of generating baseband signals of arbitrary waveforms, such as linearly swept signals. The power amplifier then amplifies this baseband signal to form the interference signal. It can be understood that the power amplifier can amplify a low-power baseband signal to obtain an interference signal that meets the interference requirements.

[0033] In another embodiment, the signal jamming module 130 may include a digital baseband unit and an analog radio frequency unit. The digital baseband unit may adopt a DSP+FPGA architecture. The DSP is the core and can communicate with the host computer for signal detection of the UAV remote control link. The FPGA can be used for high-speed signal processing, that is, to generate jamming signals in real time in conjunction with the DSP.

[0034] It should be noted that the interference signals generated by the digital baseband unit can have various signal patterns, including but not limited to linear sweep signals and AWGN (additive white Gaussian noise) signals.

[0035] The analog radio frequency unit is divided into a receiving path and a transmitting path. The receiving path includes S-band downconversion (processing 2-4GHz signals) and C-band downconversion (processing 4-8GHz signals), and consists of filters, low-noise amplifiers (LNAs), mixers, local oscillator modules, and controllable digital attenuators, which can downconvert radio frequency signals to 375MHz analog intermediate frequency signals for output. The transmitting path consists of an upconversion module and a power amplifier, which can upconvert interference signals output by the digital baseband unit to the target frequency band and amplify them.

[0036] It is understandable that the analog radio frequency unit can convert the interference signal generated by the digital baseband unit to the target frequency band, thus obtaining the final interference signal. This final interference signal can then be used to interfere with the communication link between the UAV and the corresponding controller, as well as the UAV's positioning signal.

[0037] In one embodiment, the path guidance module 140 includes an inducement signal generation unit and an inducement path generation unit. The path guidance module 140 is configured with a second signal generator. The second signal generator has the same internal structure as the first signal generator. The inducement signal generation unit can generate an inducement signal based on GPS spoofing.

[0038] GPS spoofing refers to an attacker actively transmitting false navigation signals that resemble genuine GPS signals, causing the drone to mistakenly believe the false navigation signals originate from real satellites, thereby calculating incorrect position, speed, or time. It is understood that this embodiment generates a misleading signal based on GPS spoofing, which can cause the drone's receiving terminal to generate incorrect positioning information.

[0039] Specifically, the induced signal generation unit has a built-in GPS receiver. After receiving visible satellite signals, the GPS receiver analyzes them to obtain the signal transmission time. Simultaneously, the GPS receiver obtains the signal reception time using its own clock. Subtracting the two times and multiplying by the speed of light yields the distance between the GPS receiver and the satellite. Furthermore, the GPS receiver can obtain the satellite's motion parameters by analyzing the GPS signal, thus obtaining the satellite's coordinates. Precise positioning can then be achieved through calculation.

[0040] Please see Figure 2 , Figure 2 This diagram illustrates the principle of GPS positioning. In a geocentric coordinate system, the GPS receiver coordinates are (x, y, z), and the coordinates of satellite Si obtained by the GPS receiver are (x, y, z). Si ,y Si ,z Si ), i=1, 2, 3…, the pseudoranges measured by the GPS receiver are ρi, i=1, 2, 3, where the pseudoranges can be calculated using the following formula (1): (1) by Figure 2 Taking the reception of signals from three satellites as an example, formula (1) can be: (2) Based on formula (2), the specific values ​​of x, y, and z can be solved, thereby obtaining the coordinates of the GPS receiver and realizing GPS positioning.

[0041] It should be noted that in practical scenarios, since the GPS receiver clock and the satellite clock cannot be perfectly synchronized, this embodiment introduces a new unknown quantity in formula (1): receiver clock difference t. u Therefore, formula (1) is modified to: (3) Where c represents the speed of light in a vacuum, and in this embodiment, c equals 3 × 10⁻⁶. 8 m / s.

[0042] Based on formula (3), the current coordinates (x, y, z) of the GPS receiver and the receiver clock error t can be obtained using the least squares method. u This enables GPS positioning.

[0043] It should be noted that GPS positioning is achieved by solving multiple pseudorange positioning equations. In transponder spoofing, the spoofing device delays and amplifies the received real signal, thereby changing the pseudorange value entering the GPS receiver loop and affecting the positioning result.

[0044] Please see Figure 3 , Figure 3 This diagram illustrates a satellite positioning and relay-based navigation deception method, assuming that the relay delay corresponding to satellite Si is... The corresponding GPS receiver (i.e. Figure 3 The pseudorange values ​​of each satellite calculated by the target receiver B) upon receiving the induced signal are: (4) At this point, if the target receiver B needs to be located at the deceiving target point C, only adjustment is needed. , making This allows one to achieve the purpose of deception.

[0045] Furthermore, the induced path generation unit is equipped with a GPS positioning algorithm, which can achieve precise deception by dynamically generating a virtual trajectory that smoothly extends from the current location of the drone to a safe area.

[0046] Specifically, the induced path generation unit continuously generates a sequence of path points at a high refresh rate (e.g., once per second). For each new path point, the induced path generation unit calculates the forwarding delay required for all satellite signals in real time, and the second signal generator synchronously adjusts the deception signals of each channel, causing the pseudorange value received by the UAV to change dynamically.

[0047] Here, each channel refers to the signal transmission link of different GPS satellites. When the system generates the induced path, it calculates the required forwarding delay for each visible satellite at each path point. The second signal generator then synchronously adjusts the transmission timing and phase of the corresponding satellite signals on each channel. Dynamic change refers to the synchronous and continuous minute adjustment of the pseudorange values ​​of all channels according to a preset trajectory, so that the position coordinates calculated by the UAV receiver produce the illusion of smooth position drift, rather than a sudden position jump.

[0048] It is understood that the dynamic guidance path obtained in this embodiment can match the phenomenon of the UAV moving at a constant speed along the preset path as simulated by UAV navigation, effectively simulating the continuous motion trajectory in real flight, thereby effectively avoiding the triggering of the protection mechanism of the UAV flight control system (such as triggering the UAV to hover) due to sudden changes in positioning information, and ensuring that the guidance process is stable and covert.

[0049] Those skilled in the art should understand that the division of the various modules in the embodiments is merely a division of logical functions. In actual applications, they can be fully or partially integrated into one or more actual carriers. These modules can be implemented entirely in software through processing unit calls, entirely in hardware, or a combination of software and hardware.

[0050] The intelligent countermeasure system for unmanned aerial vehicles (UAVs) proposed in this application firstly uses a detection and identification module 110 to monitor the target area in real time, which can quickly and accurately determine whether there is an UAV intrusion, providing basic information for subsequent countermeasures. Secondly, the positioning and direction finding module 120 determines the real-time position of the UAV, and the signal jamming module 130 interferes with the communication link between the UAV and the controller and the positioning signal based on the real-time position information, cutting off the normal communication between the UAV and the outside world, causing it to lose control commands and positioning capabilities. Finally, the path guidance module 140 generates an induction signal with the same structure as the original positioning signal of the UAV, guiding it to leave the target area along a dynamic induction path, effectively solving the problems of low fault tolerance and poor adaptability in the induction process in the prior art.

[0051] Figure 4 A flowchart of an embodiment of the intelligent countermeasure method for unmanned aerial vehicles provided in this application is shown below. Figure 4 As shown, the method may include: S21. Determine whether there are drones in the target area; S22. Determine the real-time location of the drone; S23. Based on real-time location interference, the communication link between the UAV and the corresponding controller and the UAV's positioning signal are interfered with; S24. Based on the real-time location, transmit an induction signal to the UAV and generate a dynamic induction path, wherein the dynamic induction path is used to guide the UAV away from the target area when the UAV receives the induction signal.

[0052] It should be noted that each step in the intelligent countermeasure method for unmanned aerial vehicles in this embodiment corresponds one-to-one with each module in the intelligent countermeasure system for unmanned aerial vehicles in the aforementioned embodiment. Therefore, the specific implementation of this embodiment can refer to the implementation of the intelligent countermeasure system for unmanned aerial vehicles in the aforementioned embodiment, and will not be repeated here.

[0053] In one embodiment, the UAV intelligent countermeasure method in this embodiment can be applied to a handheld reconnaissance and strike integrated device. The handheld reconnaissance and strike integrated device is a portable design, equipped with a foldable display and control screen, and integrates detection, identification, positioning and directional jamming functions. It is suitable for scenarios such as individual soldier patrol and temporary deployment.

[0054] In another embodiment, the intelligent drone countermeasure method can also be applied to a vehicle-mounted drone defense system. This system is highly integrated into the vehicle platform and features real-time calibration capabilities, allowing for dynamic calibration of the vehicle's heading while in motion to ensure accurate positioning and jamming targeting. The system supports detection and handling of surrounding drones at speeds up to 140 km / h, making it suitable for mobile security scenarios.

[0055] Based on the above embodiments, Figure 5 This is a schematic diagram of the structure of an intelligent countermeasure device for unmanned aerial vehicles according to one embodiment of this application, as shown below. Figure 5 As shown, the intelligent countermeasure device for unmanned aerial vehicles (UAVs) may include a processor 310, a communication interface 320, a memory 330, and a communication bus 340. The processor 310, communication interface 320, and memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute the aforementioned intelligent countermeasure method for UAVs. This method includes: determining whether a UAV exists in the target area; determining the real-time position of the UAV; jamming the communication link between the UAV and its corresponding controller and the UAV's positioning signal based on the real-time position; and transmitting a guidance signal to the UAV based on the real-time position and generating a dynamic guidance path, wherein the dynamic guidance path is used to guide the UAV away from the target area when the UAV receives the guidance signal.

[0056] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0057] Based on the above embodiments, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a drone intelligent countermeasure method provided by the above methods. The method includes: determining whether a drone exists in a target area; determining the real-time position of the drone; interfering with the communication link between the drone and its corresponding controller and the drone's positioning signal based on the real-time position; transmitting an induction signal to the drone based on the real-time position and generating a dynamic induction path, wherein the dynamic induction path is used to guide the drone away from the target area when the drone receives the induction signal.

[0058] Based on the above embodiments, in another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program is implemented to perform a drone intelligent countermeasure method provided in the above embodiments. The method includes: determining whether a drone exists in a target area; determining the real-time position of the drone; interfering with the communication link between the drone and its corresponding controller and the drone's positioning signal based on the real-time position; transmitting an induction signal to the drone based on the real-time position and generating a dynamic induction path, wherein the dynamic induction path is used to guide the drone away from the target area when the drone receives the induction signal.

[0059] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A smart countermeasure system for unmanned aerial vehicles (UAVs), characterized in that, The system includes: a detection and identification module, a positioning and direction finding module, a signal jamming module, and a path guidance module that are connected in pairs for communication; The detection and identification module is used to determine whether a drone exists in the target area; The positioning and direction finding module is used to determine the real-time position of the UAV; The signal jamming module is used to interfere with the communication link between the UAV and the corresponding controller, as well as the UAV's positioning signal, based on the real-time location. The path guidance module is used to transmit a guidance signal to the UAV based on the real-time location and generate a dynamic guidance path, wherein the dynamic guidance path is used to guide the UAV to leave the target area when the UAV receives the guidance signal.

2. The system according to claim 1, characterized in that, The detection and identification module is also used to identify the model of the drone when the drone is present in the target area; The positioning and direction finding module is also used to receive the model of the UAV and calibrate the real-time position of the UAV based on the model.

3. The system according to claim 1, characterized in that, The positioning and orientation-finding module is also used to determine the location of the drone pilot; The system also includes a pilot processing module, which is used to process the drone pilot based on the drone pilot's position.

4. The system according to claim 2, characterized in that, The detection and identification module includes a spectrum sensing unit and an identity recognition unit; The spectrum sensing unit is used to identify the radio frequency signals of drones in the target area, and to determine whether there are drones in the target area based on the drone radio frequency signals; The identification unit has a built-in drone model database. The identification unit is used to identify the model of the drone based on the drone model database, wherein the drone model database contains several drone models.

5. The system according to claim 1, characterized in that, The signal interference module includes a digital baseband unit and an analog radio frequency unit; The digital baseband unit is used to generate interference signals based on the real-time location; The analog radio frequency unit is connected to the digital baseband unit. The analog radio frequency unit is used to convert the interference signal to the target frequency band and use the converted interference signal to interfere with the communication link between the UAV and the corresponding controller, as well as the positioning signal of the UAV.

6. The system according to claim 5, characterized in that, The path guidance module includes an induction signal generation unit and an induction path generation unit; The inducement signal generation unit is used to generate an inducement signal based on the real-time position, and the inducement signal has the same signal structure as the positioning signal of the UAV. The guidance path generation unit is used to generate a dynamic guidance path based on the real-time location.

7. The system according to claim 6, characterized in that, The induced path generation unit is configured with a GPS positioning algorithm; The induced path generation unit is also used to simulate the positioning process using the GPS positioning algorithm, and the simulated positioning process is used to update the dynamic induced path of the UAV.

8. A method for intelligent countermeasures against unmanned aerial vehicles (UAVs), characterized in that, Applied to the system according to any one of claims 1-7, the method comprises: Determine if drones are present in the target area; Determine the real-time location of the drone; The real-time location interference disrupts the communication link between the UAV and its corresponding controller, as well as the UAV's positioning signal. Based on the real-time location, an inducement signal is transmitted to the drone and a dynamic inducement path is generated, wherein the dynamic inducement path is used to guide the drone away from the target area when the drone receives the inducement signal.

9. A smart countermeasure device for unmanned aerial vehicles (UAVs), characterized in that, The device includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the intelligent countermeasure method for unmanned aerial vehicles as described in claim 8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the intelligent countermeasures method for unmanned aerial vehicles as described in claim 8.

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