A method, device and equipment for drone countermeasure

Abstract

The application discloses a method, device and equipment for anti-drone, the method comprising: extracting the radio frequency signal feature information from the detection terminal, if there is no set radio frequency feature information matching the radio frequency feature information in the multiple set radio frequency feature information, the target drone is determined as an illegal drone; the sub-region where the target drone is located is determined as the target sub-region, each sub-region is based on the first human flow density of the correction coefficient and the control region, the original boundary of each original sub-region of the control region is updated to obtain the second human flow density based on the target sub-region and the grid region where the target drone is located, the target anti-drone method is determined, and the target anti-drone method is used to counter the target drone. The method can improve the accuracy of the control region partition, reduce resource waste, illegal drone missed detection, and implement hierarchical countermeasures combined with the human flow density of the target sub-region and the grid region where the target drone is located.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicles (UAVs), and more particularly to a method, apparatus, and equipment for countering UAVs. Background Technology

[0002] With the maturity of the consumer drone industry chain, the annual output of open-source flight control drones and non-standard modified drones has exceeded 10 million units. The chaos of unauthorized low-altitude flights has intensified year by year. Unauthorized flights have caused privacy leaks for tourists in scenic spots, flight delays and diversions at airports, and illegal aerial photography in government and party compound areas have become key pain points for public safety management.

[0003] Existing drone countermeasure systems typically rely on human experience to set zone radii, which can lead to two problems: overly large control zones resulting in wasted resources, and underly small zones allowing unauthorized drones to slip through detection. Furthermore, existing systems use the same countermeasure method for multiple levels of protected zones, which is not applicable to every zone. For example, in densely populated areas such as scenic spots and urban commercial districts, full-band interference can easily block public mobile communications, vehicle Bluetooth, and public WiFi (Wireless Fidelity) civilian communication frequencies, causing widespread radio pollution. In low-traffic scenarios such as border areas and uninhabited wastelands, the controllers lack adaptive strategies for targeted and precise forced landings, and uniform soft-drive methods allow illegal drones to repeatedly intrude into the controlled area. Summary of the Invention

[0004] This application provides a method, apparatus, and equipment for countering unmanned aerial vehicles (UAVs), which improves the accuracy of zoning control areas, reduces resource waste and undetected illegal UAVs, and enables adaptive and differentiated countermeasures within the control area.

[0005] In a first aspect, embodiments of this application provide a method for countering unmanned aerial vehicles (UAVs), including: Radio frequency (RF) signals are subjected to feature extraction to obtain RF feature information. The RF signals are obtained by the detection terminal after performing a spectrum scan on the target UAV. If none of the multiple set radio frequency feature information matches the set radio frequency feature information, then the target drone is determined to be an illegal drone; The sub-region where the target drone is located is determined as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on the correction coefficient and the first population density of the control area. The correction coefficient is determined based on the first population density. Based on the second pedestrian density of the target sub-region and the grid region where the target drone is located, a target countermeasure method is determined, and the target countermeasure method is used to counter the target drone. The control area includes multiple grid regions.

[0006] In this embodiment, the radio frequency (RF) signal obtained by the detection terminal after performing a spectrum scan on the target drone is acquired. RF feature information is extracted from the RF signal. If no matching RF feature information exists, the target drone is determined to be an illegal drone, thereby improving the accuracy of illegal drone identification. Furthermore, this application defines the sub-region where the target drone is located as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on a correction coefficient and the first pedestrian density of the control area. This improves the accuracy of the control area partitioning, reduces resource waste and missed detection of illegal drones, and further improves the accuracy of the determined target sub-region. Moreover, this application determines a target countermeasure method based on the sub-region (target sub-region) where the target drone is located and the second pedestrian density of the grid area where the target drone is located, and uses this method to counter the target drone, thereby achieving adaptive differentiated countermeasures within the control area and reducing the risk of radio accidental injury within the control area.

[0007] In one possible design, before performing feature extraction on the radio frequency signal to obtain radio frequency feature information, the method further includes: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set radial distance, the radial distance of each original sub-region of the controlled area is determined; Each sub-region is determined based on its radial distance and its original boundary.

[0008] In this embodiment, a correction coefficient is determined based on the first pedestrian density of the controlled area. Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and a set radial distance, the radial distance of each original sub-region of the controlled area is determined. This yields the distance by which the original boundary of each original sub-region needs to be extended outward or contracted inward. Furthermore, based on the radial distance and the original boundary of each original sub-region, each sub-region is determined, thereby improving the accuracy of the controlled area zoning and reducing resource waste and missed detection of illegal drones.

[0009] In one possible design, the set radial distance includes a first radial distance and a second radial distance, and the control area includes a first original sub-region, a second original sub-region, and a third original sub-region. Determining the radial distance of each original sub-region of the control area based on the correction coefficient, a first pedestrian density threshold, the first pedestrian density, and the set radial distance includes: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the first radial distance, the radial distance of the first original sub-region is determined; and based on the second radial distance and the correction coefficient, the radial distance of the third original sub-region is determined. The radial distance of the second original sub-region is determined based on the radial distance of the first original sub-region and the set weight coefficient; The first original sub-region is the region formed by the original boundary of the first original sub-region and the original boundary of the second original sub-region. The second original sub-region is the region formed by the original boundary of the second original sub-region and the original boundary of the third original sub-region. The third original sub-region is a closed region enclosed by the boundary of the third original sub-region.

[0010] In one possible design, determining each sub-region based on the radial distance and the original boundaries of each original sub-region includes: Using the original boundary of the third original sub-region as a reference, the radial distance of the third original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the third original sub-region to obtain the first target boundary, and the third sub-region is determined based on the first target boundary. Using the original boundary of the second original sub-region as a reference, extend or contract the radial distance of the second original sub-region outward or inward along the normal direction of the original boundary of the second original sub-region to obtain the second target boundary, and determine the second sub-region based on the first target boundary and the second target boundary; Using the original boundary of the first original sub-region as a reference, the radial distance of the first original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the first original sub-region to obtain the third target boundary, and the first sub-region is determined based on the second target boundary and the third target boundary.

[0011] In this embodiment, for each original sub-region, based on the original boundary of the original sub-region, the radial distance of the original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the original sub-region to obtain the target boundary. Based on each target boundary, each sub-region is determined, realizing millisecond-level adaptive scaling of each sub-region of the control area. Furthermore, it adapts to irregular scenic spots, winding borders and other irregular protective boundaries, supports instantaneous full-domain refresh of hand-drawn temporary control boundaries, reduces the time required for temporary deployment, lowers the false positive and false negative rate of target sub-regions of illegal drones, and improves the identification accuracy of illegal drones.

[0012] In one possible design, the method for determining the target countermeasure based on the second pedestrian density of the target sub-region and the grid region where the target drone is located includes: The second pedestrian density is compared with the second pedestrian density threshold to obtain the comparison result; Based on the target sub-region and the comparison results, the target countermeasure method is determined.

[0013] In this embodiment, based on the relationship between the target sub-region and the second pedestrian density and the second pedestrian density threshold, the corresponding target countermeasure method is determined, thereby realizing scene-adaptive differentiated countermeasure, i.e., hierarchical countermeasure.

[0014] In one possible design, determining the target countermeasure method based on the target sub-region and the comparison result includes: If the target sub-region is a first sub-region or a second sub-region, a first control command is sent to the countermeasure terminal so that the countermeasure terminal prohibits the transmission of radio frequency countermeasure signals and forced landing signals based on the first control command, and transmits a voice drive-away signal. If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is greater than or equal to the second pedestrian density threshold, then a second control command is sent to the countermeasure terminal to make the countermeasure terminal prohibit the transmission of radio frequency countermeasure signals and forced landing signals based on the second control command, and transmit a voice drive-away signal; If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is less than the second pedestrian density threshold, then a third control command is sent to the countermeasure terminal so that the countermeasure terminal transmits a radio frequency countermeasure signal and a forced landing signal based on the third control command.

[0015] In this embodiment, when the target sub-region is a first sub-region or a second sub-region, a first control command is sent to the countermeasure terminal to prevent the countermeasure terminal from transmitting radio frequency countermeasure signals and forced landing signals, and to transmit a voice warning signal, thereby reducing ineffective high-power countermeasure actions. Furthermore, when the target sub-region is a third sub-region and the second pedestrian density is greater than or equal to a second pedestrian density threshold, a second control command is sent to the countermeasure terminal to prevent the countermeasure terminal from transmitting radio frequency countermeasure signals and forced landing signals, and to transmit a voice warning signal, thereby avoiding interference with the normal communication of tourists' mobile phones, walkie-talkies, and other devices, and reducing the probability of accidental radio-related injuries in densely populated areas. Moreover, when the target sub-region is a third sub-region and the second pedestrian density is less than a second pedestrian density threshold, a third control command is sent to the countermeasure terminal to prevent the countermeasure terminal from transmitting radio frequency countermeasure signals and forced landing signals, thereby achieving countermeasure processing against the target drone.

[0016] In one possible design, after determining that the target drone is an illegal drone, the process further includes: Based on the target sub-region and the established correspondence, a target alarm method is determined, and an alarm is issued using the target alarm method. The established correspondence is the correspondence between each sub-region and each alarm method.

[0017] In this embodiment of the application, a target alarm method is determined based on the target sub-region and the established correspondence, that is, different target sub-regions correspond to different levels of alarm methods, thereby improving the efficiency of relevant personnel in handling each alarm.

[0018] In one possible design, the method for determining target alarms based on the target sub-region and the established correspondence includes: If the target sub-region is the first sub-region, then the first warning sound will be used to sound an alarm, the first alarm pop-up window will be displayed, and relevant personnel within the first notification range will be notified through the set communication method. If the target sub-region is the second sub-region, then a second warning sound is used to sound an alarm, a second alarm pop-up window is displayed, relevant personnel within the second notification range are notified through a set communication method, and the flight trajectory of the target drone is determined and displayed based on the historical and current location information of the target drone. If the target sub-region is the third sub-region, then a third alarm sound will be used to sound an alarm, a third alarm pop-up window will be displayed, and relevant personnel within the third notification range will be notified through the set communication method. The frequency of the first warning sound is lower than that of the second warning sound, and the frequency of the second warning sound is lower than that of the third warning sound; the colors of the first alarm pop-up, the second alarm pop-up, and the third alarm pop-up are different; the range of the first notification is smaller than that of the second notification, and the range of the second notification is smaller than that of the third notification.

[0019] In this embodiment, the three-level sub-regions correspond to different frequencies of warning sounds, different notification ranges of relevant personnel, and different colored alarm pop-ups, thereby significantly improving the speed at which relevant personnel can identify threat levels, enhancing the efficiency of handling high-risk scenarios, and greatly reducing the number of invalid false alarms.

[0020] In one possible design, determining the sub-region where the target drone is located as the target sub-region includes: A ray is determined with the position information of the target UAV as the endpoint and a set direction is defined, wherein the set direction is the direction from the center of the third sub-region to the target UAV. Determine the number of intersections between the boundaries of each sub-region and the ray; The sub-regions that intersect the ray an odd number of times are designated as the target sub-regions.

[0021] Secondly, embodiments of this application provide a drone countermeasure device, comprising: The extraction module is used to extract features from the radio frequency signal to obtain radio frequency feature information. The radio frequency signal is obtained by the detection terminal after performing a spectrum scan on the target UAV. The first determining module is used to determine that the target drone is an illegal drone if there is no set radio frequency feature information that matches the radio frequency feature information among the multiple set radio frequency feature information. The second determining module is used to determine the sub-region where the target drone is located as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on the correction coefficient and the first population density of the control area. The correction coefficient is determined based on the first population density. The countermeasure module is used to determine the target countermeasure method based on the second population density of the target sub-region and the grid region where the target drone is located, and to countermeasure the target drone using the target countermeasure method. The control area includes multiple grid regions.

[0022] Thirdly, this application provides an electronic device, comprising: Memory, used to store program instructions; A processor is configured to invoke program instructions stored in the memory and execute the steps of the method described in any one of the first aspects according to the obtained program instructions.

[0023] Fourthly, this application provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the method described in any one of the first aspects.

[0024] Fifthly, this application provides a computer program product comprising: computer program code, which, when run on a computer, causes the computer to perform the method described in any one of the first aspects.

[0025] The technical effects of aspects two through five and any one of their designs can be found in the technical effects of the corresponding designs in aspect one, and will not be repeated here. Attached Figure Description

[0026] Figure 1 This is a schematic diagram illustrating an application scenario provided in the embodiments of this application; Figure 2 A flowchart illustrating a method for countering unmanned aerial vehicles (UAVs) provided in this application embodiment; Figure 3 A flowchart illustrating a method for determining sub-regions provided in this application embodiment; Figure 4 A schematic diagram of a control area provided in an embodiment of this application; Figure 5 A detailed flowchart of a drone countermeasure method provided in this application embodiment; Figure 6 A flowchart illustrating a method for determining the radial distance of each original sub-region of a controlled area, provided in an embodiment of this application; Figure 7 A detailed flowchart illustrating a method for determining sub-regions provided in an embodiment of this application; Figure 8 A schematic diagram illustrating the radial distances of the original sub-regions provided in the embodiments of this application; Figure 9 A schematic diagram of each sub-region provided in the embodiments of this application; Figure 10 A flowchart illustrating a method for determining a target sub-region provided in an embodiment of this application; Figure 11 This is a schematic diagram illustrating the determination of a target sub-region, provided in an embodiment of this application. Figure 12 This is a schematic diagram illustrating another method for determining a target sub-region, as provided in an embodiment of this application. Figure 13 This is a schematic diagram illustrating the determination of a target sub-region, provided in an embodiment of this application. Figure 14 A flowchart illustrating a method for determining a target countermeasure is provided in an embodiment of this application; Figure 15 A schematic diagram of a drone alarm provided in an embodiment of this application; Figure 16 This is a schematic diagram of the structure of a drone countermeasure device provided in an embodiment of this application; Figure 17 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0028] The terms "first" and "second" in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the term "comprising" and any variations thereof are intended to cover non-exclusive protection. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. The term "multiple" in this application can mean at least two, for example, two, three, or more, and the embodiments of this application do not impose limitations.

[0029] The data collection, dissemination, and use in this application all comply with relevant national laws and regulations.

[0030] Before introducing the drone countermeasure method provided in the embodiments of this application, the technical background of the embodiments of this application will be described in detail for ease of understanding.

[0031] With the maturation of the consumer drone industry chain, the annual production of open-source flight control drones and non-standard modified drones has exceeded ten million units. The problem of unauthorized low-altitude flights has intensified year by year. Unauthorized drones entering scenic areas leading to privacy breaches, causing flight delays and diversions at airports, and illegally filming classified information in government and party compound areas have become key public safety management challenges. Unauthorized flights refer to drone operations within controlled areas that violate relevant regulations and fail to meet any of the legal requirements for real-name registration, flight reporting, airspace access, or qualification control. Controlled areas generally include: all airspace above 120 meters true altitude, airport clear zones, classified areas of government / military institutions, chemical plants, temporary controlled airspace for large-scale events, and restricted airspace along national borders. Existing domestic drone countermeasure systems generally suffer from structural technical shortcomings in four core areas: airspace configuration, alarm control, countermeasure decision-making, and data storage. These shortcomings are detailed below: First, the control area zoning mechanism is rigid and lacks multi-parameter adaptive diameter change capability.

[0032] The boundaries of all control zones (layers / sub-regions) in the existing drone countermeasure system's control area are fixed using factory-pre-entered static GIS (Geographic Information System) coordinates. The radial distance of the three-level control layers is a fixed constant within the hardware firmware, lacking a standardized data interaction interface for external sensor data linkage correction. When switching from routine control scenarios to situations with a surge in crowds, such as large music festivals or temporary emergency security, maintenance personnel need to manually modify vector coordinates segment by segment using GIS map software and manually iteratively verify the boundaries of each control zone. Reconfiguring the boundaries of each control zone takes 2-6 hours, which cannot meet the practical requirement of rapid deployment within 5 minutes for temporary control. Furthermore, the existing drone countermeasure system lacks a dual-input parameterized layer iterative calculation mathematical model based on site attribute coefficients and real-time crowd density. It relies entirely on human experience to set the zone radius, which easily leads to the dual defects of overly large control areas resulting in resource waste and underly small zones leading to missed detection of unauthorized drone flights. Although some existing drone countermeasure systems have set up multi-level zones, the zone boundaries are only defined by the straight-line distance of the detection and are not vector-bound to the actual geographical boundaries of the protected targets, making them unsuitable for irregular protection scenarios such as scenic spots and winding borders.

[0033] Secondly, the alarm triggering logic is driven by a single threshold and has a hierarchical and differentiated output architecture without layer binding.

[0034] Existing drone countermeasure systems typically employ a single-channel fixed audio source and a hardware architecture for mass SMS messaging across the entire address book. These systems rely solely on the straight-line distance between the target drone and the center point of the controlled area as the sole criterion for alarm triggering, failing to establish a mapping data table between the spatial attributes of the controlled area and the alarm output modalities. Regardless of whether the target drone intrudes into a high-risk red no-fly zone or a low-risk yellow warning buffer zone, existing drone countermeasure systems output identical audible and visual alarms, with all maintenance and security personnel simultaneously receiving the same alarm SMS. Client pop-ups lack priority differentiation and background color-coded hierarchical indicators. High-risk unauthorized flights and low-altitude, compliant flights trigger the same alarms, causing alarm fatigue among security personnel, delays in handling high-risk incidents, and an average of more than 10 invalid false alarms per day, severely disrupting daily security maintenance work.

[0035] Thirdly, the countermeasures rely on a single basis for starting and stopping, and lack a hardware-based interlocking control mechanism that constrains the flow of people.

[0036] Current drone countermeasure systems rely solely on the target's straight-line distance as the condition for activating and deactivating high-power radio frequency output. Once the distance is reached, the full-band radio frequency power amplifier power supply circuit is activated, resulting in indiscriminate omnidirectional transmission of 2.4GHz / 5.8GHz high-power white noise signals. In densely populated areas such as scenic spots and urban commercial districts, this full-band interference can easily block public mobile communications, vehicle Bluetooth, and public WiFi frequencies, causing widespread radio pollution and violating relevant regulations. In low-traffic scenarios such as border areas and uninhabited wastelands, the lack of adaptive strategies for targeted and precise forced landings means that unauthorized drones repeatedly intrude into controlled areas. Existing drone countermeasure systems only restrict the activation and deactivation logic at the software level, without adding hardware-level electronic interlocking switches to the radio frequency power amplifier power supply circuit. This makes the software parameters susceptible to tampering and ineffective, failing to prevent the use of high-power electromagnetic interference in densely populated areas from the underlying hardware level.

[0037] Fourthly, business data is stored in a discrete manner, and there is no hardware encryption integrated judicial evidence collection architecture.

[0038] Existing drone countermeasure systems store raw spectrum data, alarm logs, countermeasure commands, and drone trajectories in multiple local hard drives in separate modules. The database lacks a unified structured index and is not equipped with a hardware-level SHA256 (Secure HashAlgorithm 256) encryption chip. Log fields can be manually modified or deleted by the backend administrator. When the public security department investigates illegal drone flights, maintenance personnel need to manually split multi-source data and manually organize evidence materials, with an average evidence collection period of 3 to 5 working days. The legality of the evidence cannot be accepted by the judiciary, and many illegal drone flight cases cannot be subject to administrative penalties due to the cumbersome evidence collection process, resulting in a broken control loop.

[0039] To address the aforementioned issues, this application proposes a method, apparatus, and equipment for countering unmanned aerial vehicles (UAVs), which improves the accuracy of zoning control areas, reduces resource waste and undetected illegal UAVs, and enables adaptive and differentiated countermeasures within the control area.

[0040] First refer to Figure 1This is a schematic diagram illustrating an application scenario of an embodiment of this application, including a target drone 11, a server 12, a detection terminal 13, and a countermeasure terminal 14. The detection terminal 13 and the server 12 communicate via a network, which can be a local area network (LAN), a wide area network (WAN), etc. The countermeasure terminal 14 and the server 12 also communicate via a network, which can be a LAN, a WAN, etc. The server 12 can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, and big data and artificial intelligence platforms. The detection terminal 13 can be some or all of a fixed detection terminal, a vehicle-mounted detection terminal, and a portable detection terminal. All detection terminals 13 are interconnected based on the LoRa Mesh (a self-organizing network communication protocol based on LoRa (a low-power local area network wireless standard) technology) self-organizing network protocol. Countermeasure terminal 14 can be some or all of a fixed countermeasure terminal, a vehicle-mounted countermeasure terminal, and a portable countermeasure terminal. Countermeasure terminal 14 is used to counter illegal drones. A detection terminal 13 and a countermeasure terminal 14 can be integrated into a single terminal.

[0041] In this embodiment of the application, as an optional implementation, the detection terminal 13 performs a spectrum scan on the target drone 11 to obtain a radio frequency signal, and sends the radio frequency signal to the server 12. The server 12 extracts features from the radio frequency signal to obtain radio frequency feature information. If there is no set radio frequency feature information that matches the radio frequency feature information among the multiple set radio frequency feature information, then the target drone is determined to be an illegal drone. The sub-region where the target drone is located is determined as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on the correction coefficient and the first pedestrian density of the control area. The correction coefficient is determined based on the first pedestrian density. Based on the target sub-region and the second pedestrian density of the grid area where the target drone is located, a target countermeasure method is determined, and the target countermeasure method is used to counter the target drone. The control area includes multiple grid areas.

[0042] The following is for reference. Figure 2 The flowchart shown illustrates a method for countering unmanned aerial vehicles (UAVs), and explains the technical solution provided in the embodiments of this application: Step 201: Extract features from the radio frequency signal to obtain radio frequency feature information.

[0043] The radio frequency signal is obtained by the detection terminal after performing a spectrum scan on the target drone. There can be one or multiple detection terminals.

[0044] In this embodiment of the application, after extracting features from the radio frequency signal to obtain radio frequency feature information, the method further includes: if there is a set radio frequency feature information that matches the radio frequency feature information among the multiple set radio frequency feature information, then the target drone is determined to be a legitimate drone.

[0045] Step 202: If there is no matching radio frequency feature among the multiple set radio frequency feature information, then the target drone is determined to be an illegal drone.

[0046] The multiple preset radio frequency (RF) characteristic information can be set according to the actual situation, or it can be determined in advance using the RF signal obtained after the detection terminal performs a spectrum scan on the legitimate drone. Each preset RF characteristic information can be determined by the following method: acquiring the RF signal obtained after the detection terminal performs a spectrum scan on the legitimate drone, and extracting features from the acquired RF signal to obtain the preset RF characteristic information.

[0047] Regardless of whether it's a factory-made consumer drone or a homemade / modified racing drone, any drone that lacks registration, approval, violates airspace regulations, exceeds altitude limits, or has its firmware hacked to evade control, and thus intrudes into a controlled area, will be deemed an illegal drone.

[0048] Step 203: Determine the sub-region where the target drone is located as the target sub-region.

[0049] In this embodiment of the application, determining the sub-region where the target drone is located as the target sub-region includes: determining the sub-region where the target drone is located as the target sub-region based on the location information of the target drone and the boundaries that constitute each sub-region.

[0050] Each sub-region is obtained by updating the original boundaries of the original sub-regions of the controlled area based on a correction coefficient and the first pedestrian density of the controlled area. The correction coefficient is determined based on the first pedestrian density. The controlled area includes multiple original sub-regions; for example, the controlled area includes three original sub-regions: the first original sub-region, the second original sub-region, and the third original sub-region. This application updates the original boundaries of the three original sub-regions of the controlled area based on the correction coefficient and the first pedestrian density of the controlled area, resulting in three sub-regions: the first sub-region, the second sub-region, and the third sub-region.

[0051] In this embodiment, the correction coefficient is determined by the following method: determining the correction coefficient corresponding to the population density range to which the first population density belongs. This application can set multiple population density ranges according to actual conditions, setting a correction coefficient for each population density range. Furthermore, the higher the population density, the smaller the set correction coefficient. The set correction coefficient can be positive or negative. For example, this application can set 3 population density ranges, with the first population density range being... The first high population density range has a correction factor K1=0; the second population density range is... The first is the medium population density range, with a corresponding correction factor K2 = 0.35; the third population density range is... This refers to the low pedestrian density range, with a corresponding correction factor K3 = 0.8. If the first person density Within the second range of pedestrian density, the correction factor is set at 0.35.

[0052] In this embodiment, to determine the first pedestrian density of the controlled area, the controlled area is divided into multiple grid areas. Based on the pedestrian density of each grid area, the first pedestrian density of the controlled area is determined. This application can divide the controlled area into grid areas according to actual conditions; the areas of any two grid areas can be the same or different.

[0053] The first pedestrian density in the controlled area in this application can be either the instantaneous pedestrian density or the average pedestrian density over a set period. When the first pedestrian density in the controlled area is the instantaneous pedestrian density, this application can determine the first pedestrian density in the controlled area using the following method: obtain the pedestrian density JSON (JavaScript Object Notation) time-series data of each grid area in the controlled area according to a set period; perform outlier removal and third-order mean filtering preprocessing on the pedestrian density JSON time-series data of each grid area to obtain the pedestrian density data of each grid area; calculate the mean of the pedestrian density data of each grid area to obtain the first pedestrian density of the controlled area.

[0054] The set period can be configured according to actual conditions; for example, the set period can be 1 minute. JSON is an open standard lightweight data interchange format. JavaScript, or JS for short, is a lightweight, interpreted, dynamically typed scripting language. The specific process of outlier removal and third-order mean filtering preprocessing for pedestrian density JSON time-series data in this application is existing technology and will not be described in detail here.

[0055] This application obtains raw data from three types of passenger flow terminals located in the controlled area. The three types of passenger flow terminals are an infrared passenger flow counter, a video AI (Artificial Intelligence) human figure recognition and statistics gateway, and a park access control collection device. The raw data is standardized to obtain JSON time-series data of passenger flow density. The JSON time-series data of passenger flow density includes information such as sampling time, grid area number, real-time number of people in the area, short-term average passenger flow, and area passenger flow density threshold.

[0056] In this embodiment of the application, the average value of the pedestrian density data of each grid area is calculated to obtain the first pedestrian density of the controlled area, including: determining the first sum of the pedestrian density data of each grid area; and taking the ratio of the first sum to the number of grid areas as the first pedestrian density of the controlled area.

[0057] When the first pedestrian density in the controlled area is the average pedestrian density over a set duration, this application can determine the first pedestrian density in the controlled area using the following method: obtain the pedestrian density JSON time-series data for a set duration for each grid area in the controlled area; perform outlier removal and third-order mean filtering preprocessing on the pedestrian density JSON time-series data for a set duration for each grid area to obtain the pedestrian density data for a set duration for each grid area; for each grid area, obtain the pedestrian density data for that grid area based on the pedestrian density data for a set duration and the set duration; calculate the mean of the pedestrian density data for each grid area to obtain the first pedestrian density in the controlled area.

[0058] The duration can be set according to the actual situation. For example, the duration can be 1 minute, 5 minutes, or 10 minutes.

[0059] In this embodiment, the process of obtaining pedestrian density data for a grid area based on pedestrian density data for a set duration and the set duration includes: determining a second sum of pedestrian density data for the set duration in the grid area; and using the ratio of the second sum to the set duration as the pedestrian density data for the grid area. In this embodiment, the process of calculating the average of pedestrian density data for each grid area to obtain a first pedestrian density for the controlled area includes: determining a third sum of pedestrian density data for each grid area; and using the ratio of the third sum to the number of grid areas as the first pedestrian density for the controlled area.

[0060] Step 204: Based on the second pedestrian density of the target sub-region and the grid region where the target UAV is located, determine the target countermeasure method and use the target countermeasure method to counter the target UAV.

[0061] In this application, the second pedestrian density in the grid area where the target drone is located can be the instantaneous pedestrian density of the grid area where the target drone is located; or it can be the average pedestrian density of the grid area where the target drone is located over a set period of time. If the first pedestrian density is the instantaneous pedestrian density, then the second pedestrian density is also the instantaneous pedestrian density of the grid area where the target drone is located; if the first pedestrian density is the average pedestrian density over a set period of time, then the second pedestrian density is also the average pedestrian density of the grid area where the target drone is located over a set period of time.

[0062] When the second pedestrian density in the grid area where the target drone is located is the instantaneous pedestrian density in the grid area where the target drone is located, this application can determine the second pedestrian density using the following method: obtain the pedestrian density JSON time series data of the grid area where the target drone is located according to a set period, and perform outlier removal and third-order mean filtering preprocessing on the pedestrian density JSON time series data of the grid area where the target drone is located to obtain the pedestrian density data of the grid area where the target drone is located.

[0063] When the second pedestrian density in the grid area where the target drone is located is the average pedestrian density in the grid area for a set duration, this application can determine the second pedestrian density in the grid area where the target drone is located using the following method: obtain JSON time-series data of pedestrian density in the grid area where the target drone is located for a set duration; perform outlier removal and third-order mean filtering preprocessing on the JSON time-series data of pedestrian density in the grid area where the target drone is located for a set duration to obtain pedestrian density data of the grid area where the target drone is located for a set duration; and obtain the second pedestrian density in the grid area where the target drone is located based on the pedestrian density data of the grid area where the target drone is located for a set duration and the set duration.

[0064] In this embodiment of the application, the second population density of the grid area where the target drone is located is obtained based on the population density data of the grid area for a set duration and the set duration, including: determining the fourth sum of the population density data of the grid area where the target drone is located for a set duration; and taking the ratio of the fourth sum to the set duration as the second population density of the grid area where the target drone is located.

[0065] In this embodiment, the radio frequency (RF) signal obtained by the detection terminal after performing a spectrum scan on the target drone is acquired. RF feature information is extracted from the RF signal. If no matching RF feature information exists, the target drone is determined to be an illegal drone, thereby improving the accuracy of illegal drone identification. Furthermore, this application defines the sub-region where the target drone is located as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on a correction coefficient and the first pedestrian density of the control area. This improves the accuracy of the control area partitioning, reduces resource waste and missed detection of illegal drones, and further improves the accuracy of the determined target sub-region. Moreover, this application determines a target countermeasure method based on the sub-region (target sub-region) where the target drone is located and the second pedestrian density of the grid area where the target drone is located, and uses this method to counter the target drone, thereby achieving adaptive differentiated countermeasures within the control area and reducing the risk of radio accidental injury within the control area.

[0066] In this embodiment of the application, before extracting radio frequency feature information from the radio frequency signal in step 201, the original boundaries of each original sub-region of the control area are updated based on the correction coefficient and the first pedestrian density of the control area to obtain each sub-region. Figure 3 A flowchart illustrating a method for determining sub-regions provided in this application embodiment is shown below. Figure 3 As shown, it includes at least the following steps 301-302: Step 301: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set radial distance, determine the radial distance of each original sub-region of the control area.

[0067] The set radial distance includes a first radial distance and a second radial distance, which can be set according to the actual situation.

[0068] In this embodiment of the application, the first pedestrian density threshold can be determined using the following formula. : ;Formula (1) Where C is the rated capacity of the controlled area, S is the area of ​​the controlled area, and the rated capacity C can be set according to the actual situation, with the first population density threshold being the [missing information]. The unit is (people / km) 2 (people / square kilometer). When the controlled area is a high-density area (e.g., scenic area) or a medium-density area, the first population density threshold is... This can be the instantaneous maximum carrying capacity of the controlled area; when the controlled area is a low-density area (such as a border or open field), the first population density threshold is... It can take the minimum value.

[0069] Step 302: Determine each sub-region based on the radial distance of each original sub-region and the original boundary of each original sub-region.

[0070] In this embodiment of the application, the control area includes three original sub-regions, namely the first original sub-region, the second original sub-region, and the third original sub-region. The first original sub-region is the area formed by the original boundary of the first original sub-region and the original boundary of the second original sub-region. The second original sub-region is the area formed by the original boundary of the second original sub-region and the original boundary of the third original sub-region. The third original sub-region is a closed area enclosed by the original boundary of the third original sub-region. Figure 4This is a schematic diagram of a control area provided in an embodiment of this application. The control area includes three original sub-regions: a first original sub-region, a second original sub-region, and a third original sub-region. The third original sub-region is a closed area enclosed by its original boundary f1, i.e., a white area. The second original sub-region is the area formed by the original boundary f1 of the third original sub-region and the original boundary f2 of the second original sub-region, i.e., an area with a grid background. The first original sub-region is the area formed by the original boundary f2 of the second original sub-region and the original boundary f3 of the first original sub-region, i.e., a gray area.

[0071] The following will provide a detailed explanation of the specific steps involved in the drone countermeasures methods described above, such as... Figure 5 As shown: Step 501: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density of the controlled area, and the set radial distance, determine the radial distance of each original sub-area of ​​the controlled area.

[0072] Step 502: Determine each sub-region based on the radial distance of each original sub-region and the original boundary of each original sub-region.

[0073] Step 503: Extract features from the radio frequency signal to obtain radio frequency feature information.

[0074] Step 504: Determine whether there is any set radio frequency feature information that matches the radio frequency feature information among the multiple set radio frequency feature information. If yes, proceed to step 505; otherwise, proceed to step 506.

[0075] Step 505: Determine that the target drone is a legitimate drone.

[0076] Step 506: Determine that the target drone is an illegal drone.

[0077] In this embodiment, a similarity algorithm is used to calculate the similarity between radio frequency feature information and each set radio frequency feature information. If there is a set radio frequency feature information with a similarity exceeding a similarity threshold, the target drone is determined to be a legitimate drone; if there is no set radio frequency feature information with a similarity exceeding the similarity threshold, the target drone is determined to be an illegitimate drone. The similarity threshold can be set according to actual conditions, and the similarity algorithm can be cosine similarity, Euclidean distance, or other algorithms.

[0078] This application pre-sets a drone radio frequency feature information fingerprint database, which includes multiple set radio frequency feature information. Each set radio frequency feature information is obtained by extracting features from the radio frequency information obtained by the detection terminal after performing a spectrum scan on a legitimate drone (i.e., a drone in the whitelist).

[0079] Step 507: Determine the sub-region where the target drone is located as the target sub-region.

[0080] Step 508: Based on the second pedestrian density of the target sub-region and the grid region where the target UAV is located, determine the target countermeasure method and use the target countermeasure method to counter the target UAV.

[0081] In this embodiment, the radial distance of each original sub-region of the control area is determined based on a correction coefficient, a first pedestrian density threshold, a first pedestrian density in the control area, and a set radial distance. The control area includes a first original sub-region, a second original sub-region, and a third original sub-region, and the set radial distance includes the first radial distance and the second radial distance. Figure 6 A flowchart illustrating a method for determining the radial distance of each original sub-region of a controlled area, as provided in this application embodiment, is shown below. Figure 6 As shown, step 501 above includes at least the following steps 601-603: Step 601: Determine the radial distance of the first original sub-region based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the first radial distance.

[0082] In this embodiment, the radial distance of the first original sub-region can be determined using the following formula. ;Formula (2) in, This is the first radial distance, which can be set according to the actual situation. For correction factor, The highest population density. This is the first threshold for pedestrian density.

[0083] Step 602: Determine the radial distance of the third original sub-region based on the second radial distance and the correction coefficient.

[0084] In this embodiment of the application, determining the radial distance of the third original sub-region based on the second radial distance and the correction coefficient includes: using the product of the second radial distance and the correction coefficient as the radial distance of the third original sub-region. The execution order of steps 601 and 602 can be either step 601 first, followed by step 602, or step 602 first, followed by step 601.

[0085] In this embodiment of the application, the radial distance of the third original sub-region can be determined by the following formula. : ;Formula (3) in, This is the second radial distance, which can be set according to the actual situation. This is a correction factor.

[0086] Step 603: Determine the radial distance of the second original sub-region based on the radial distance of the first original sub-region and the set weight coefficient.

[0087] The weighting coefficient can be set according to the actual situation; for example, the weighting coefficient can be set to 0.6.

[0088] In this embodiment of the application, determining the radial distance of the second original sub-region based on the radial distance of the first original sub-region and the set weight coefficient includes: taking the product of the radial distance of the first original sub-region and the set weight coefficient as the radial distance of the second original sub-region.

[0089] In this embodiment, the radial distance of the second original sub-region can be determined using the following formula. : ;Formula (4) in, The radial distance of the first original sub-region. The weighting coefficient can be set to 0.6.

[0090] In this embodiment of the application, the radial distance of the second original sub-region can also be determined by the following method: the radial distance of the second original sub-region is determined based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, the first radial distance, and the set weight coefficient.

[0091] In this embodiment, the radial distance of the second original sub-region can be determined using the following formula. : ;Formula (5) in, The first radial distance, For correction factor, The highest population density. The first threshold for pedestrian density. To set the weighting coefficients.

[0092] In the case of using the above formula (5) to determine the radial distance of the second original sub-region, the steps of determining the radial distance of the three sub-regions can be performed in parallel or in sequence, without any restriction.

[0093] In this embodiment, each sub-region is determined based on the radial distance of each original sub-region and the original boundary of each original sub-region. Figure 7 A detailed flowchart of a method for determining sub-regions provided in this application embodiment is shown below. Figure 7 As shown, step 502 above includes at least the following steps 701-703: Step 701: Using the original boundary of the third original sub-region as a reference, extend or contract the radial distance of the third original sub-region outward or inward along the normal direction of the original boundary of the third original sub-region to obtain the first target boundary, and determine the third sub-region based on the first target boundary.

[0094] The original boundary of the third original sub-region is pre-defined and is a WGS84 (World Geodetic System 1984, geocentric coordinate system) geographic vector closed boundary. WGS-84 is a conventional Earth coordinate system with the Earth's center of mass as the origin, the Z-axis pointing to the reference polar direction defined by the International Earth Rotation and Reference Systems Service (IERS), the X-axis pointing to the intersection of the reference meridian and the equator, and the Y-axis forming a right-handed coordinate system. In this embodiment, determining the third sub-region based on the first target boundary includes: taking the closed region enclosed by the first target boundary as the third sub-region.

[0095] In this embodiment, when the radial distance of the third original sub-region is positive, the original boundary of the third original sub-region is used as a reference, and the radial distance of the third original sub-region is extended outward along the normal direction of the original boundary of the third original sub-region to obtain the first target boundary. When the radial distance of the third original sub-region is negative, the original boundary of the third original sub-region is used as a reference, and the radial distance of the third original sub-region is contracted inward along the normal direction of the original boundary of the third original sub-region to obtain the first target boundary.

[0096] For example, Figure 8 A schematic diagram of the radial distances of the original sub-regions provided in the embodiments of this application is shown below. Figure 8 As shown, the original boundary of the third original sub-region is f1, and the radial distance of the third original sub-region is h1. Taking the original boundary f1 of the third original sub-region as the reference, the radial distance h1 of the third original sub-region is extended outward along the normal direction of the original boundary f1 to obtain the first target boundary. . Figure 9 This is a schematic diagram of each sub-region provided in the embodiments of this application, such as... Figure 9 As shown, after obtaining the first target boundary Then, based on the first target boundary Determine the third sub-region, that is, determine the boundary of the first target. The enclosed region is the third subregion; therefore, the third subregion is... Figure 9 The white area in the middle.

[0097] Step 702: Using the original boundary of the second original sub-region as a reference, extend or contract the radial distance of the second original sub-region outward or inward along the normal direction of the original boundary of the second original sub-region to obtain the second target boundary, and determine the second sub-region based on the first target boundary and the second target boundary.

[0098] The original boundary of the second original sub-region is pre-defined and is a WGS84 geographic vector closed boundary.

[0099] In this embodiment, when the radial distance of the second original sub-region is positive, the original boundary of the second original sub-region is used as a reference, and the radial distance of the second original sub-region is extended outward along the normal direction of the original boundary of the second original sub-region to obtain the second target boundary. When the radial distance of the second original sub-region is negative, the original boundary of the second original sub-region is used as a reference, and the radial distance of the second original sub-region is contracted inward along the normal direction of the original boundary of the second original sub-region to obtain the second target boundary.

[0100] For example, such as Figure 8 As shown, the original boundary of the second original sub-region is f2, and the radial distance of the second original sub-region is h2. Taking the original boundary f2 of the second original sub-region as the reference, the radial distance h2 of the second original sub-region is extended outward along the normal direction of the original boundary f2 to obtain the second target boundary. After obtaining the second target boundary Then, based on the first target boundary Second target boundary Determine the second sub-region, that is, the second sub-region is Figure 9 The background in the image is a grid area.

[0101] Step 703: Using the original boundary of the first original sub-region as a reference, extend or contract the radial distance of the first original sub-region outward or inward along the normal direction of the original boundary of the first original sub-region to obtain the third target boundary, and determine the first sub-region based on the second target boundary and the third target boundary.

[0102] The original boundary of the first original sub-region is pre-defined and is a closed boundary of the WGS84 geographic vector. The third sub-region is usually marked in red and is commonly referred to as the red area (red zone), or countermeasure execution zone, which is a closed area enclosed by the first target boundary. The second sub-region is usually marked in blue and is commonly referred to as the blue area (blue zone), or middle buffer zone, which is the area formed by the first target boundary and the second target boundary. The first sub-region is usually marked in yellow and is commonly referred to as the yellow area (yellow zone), or outer buffer zone, which is the area formed by the second target boundary and the third target boundary. Based on the radial distance and original boundary of each original sub-region, this application generates a multi-layer closed vector polygon GIS layer of yellow, blue, and red after determining each sub-region. The multi-layer vector layers are stored independently and overlaid on the electronic map in real time. Hand-drawn temporary boundaries will simultaneously generate new layered vector circles.

[0103] In this embodiment, when the radial distance of the first original sub-region is positive, the original boundary of the first original sub-region is used as a reference, and the radial distance of the first original sub-region is extended outward along the normal direction of the original boundary of the first original sub-region to obtain the third target boundary. When the radial distance of the first original sub-region is negative, the original boundary of the first original sub-region is used as a reference, and the radial distance of the first original sub-region is contracted inward along the normal direction of the original boundary of the first original sub-region to obtain the third target boundary.

[0104] In this application's embodiments, there are cases where the original boundaries of all original sub-regions extend outwards, cases where the original boundaries of all original sub-regions contract inwards, and cases where the original boundaries of some original sub-regions extend outwards while the original boundaries of others contract inwards. This application takes the case where the original boundaries of all original sub-regions extend outwards as an example.

[0105] For example, such as Figure 8 As shown, the original boundary of the first original sub-region is f3, and the radial distance of the first original sub-region is h3. Taking the original boundary f3 of the first original sub-region as the reference, the radial distance h3 of the first original sub-region is extended outward along the normal direction of the original boundary f3 to obtain the third target boundary. After obtaining the third target boundary Subsequently, based on the second target boundary and the third target boundary The first sub-region is determined, that is, the first sub-region is Figure 9 The gray area in the text.

[0106] In this embodiment of the application, step 503 above, which involves extracting features from the radio frequency (RF) signal to obtain RF feature information, includes: acquiring the RF signal obtained after at least one detection terminal performs a spectrum scan on the target UAV; and extracting features from the RF signal using a predefined feature extraction method to obtain RF feature information. The RF feature information is typically a RF feature vector.

[0107] In this embodiment of the application, acquiring the radio frequency signal obtained after at least one detection terminal performs a spectrum scan on the target drone includes: acquiring the radio frequency signal of a predetermined first duration obtained after at least one detection terminal performs a spectrum scan on the target drone. The first duration can be set according to actual conditions.

[0108] The detection terminals typically fall into three categories: fixed detection terminals, vehicle-mounted detection terminals, and portable detection terminals. All three types of terminals utilize an SDR (Software Defined Radio) receiver architecture, covering the universal communication frequency band for all UAVs from 433MHz (megacycle) to 6GHz (gigahertz) (2.4GHz for remote control, 5.8GHz for image transmission, 900MHz for industrial remote control, and GNSS (Global Navigation Satellite System) navigation band). SDR is a radio broadcast communication technology based on a software-defined wireless communication protocol rather than hardwired implementation.

[0109] Fixed detection terminals are typically deployed at airports and government compound perimeters, integrating 77GHz millimeter-wave radar and wideband spectrum acquisition chips, with a detection radius of 8km, and a built-in fingerprint database of RF signature information from over 200 mainstream drones. Vehicle-mounted detection terminals are typically mounted on security patrol vehicles, integrating infrared optoelectronic gimbals and superheterodyne RF receiver modules, with a detection radius of 5km, supporting mobile, full-area patrols. Portable detection terminals are typically used at scenic area gates and for temporary event security, handheld deployments, integrating narrowband RF receiver circuitry, with a 12-hour battery life and a detection radius of 3km. These three types of detection terminals are interconnected based on the LoRa Mesh self-organizing network protocol. When any single detection terminal loses power, adjacent detection terminals automatically increase their RF receiving gain by 3-6dB, thus filling airspace blind spots and eliminating single-point detection dead zones. LoRa is a low-power local area network wireless standard. Its name comes from Long Range Radio. Its biggest feature is that it can transmit over a longer distance than other wireless methods under the same power consumption conditions, achieving a balance between low power consumption and long distance. The communication distance can be 3-5 times that of traditional wireless radio frequency technology.

[0110] The feature extraction method can be set according to the actual situation. For example, the feature extraction method can be the short-time energy detection method, the zero-crossing detection method, etc. Radio frequency feature information includes some or all of the time domain feature information and the frequency domain feature information.

[0111] In this embodiment, the short-time energy detection method is used to extract features from the radio frequency (RF) signal, obtaining time-domain feature information from the RF feature information. Specifically, the RF pulse sequence of the RF signal is extracted according to a fixed sliding time window, the sum of squares of the signal amplitude within the fixed sliding time window is calculated, and time-domain feature information such as pulse duration, pulse interval, signal start-stop period, and peak amplitude is extracted. The duration corresponding to the fixed sliding time window can be set according to actual conditions.

[0112] In this embodiment, zero-crossing detection is used to extract features from the radio frequency (RF) signal, obtaining time-domain features from the RF feature information. Specifically, based on the RF signal, the number of times the signal waveform crosses the zero level per unit time is counted to distinguish between the UAV remote control signal and environmental noise, and time-domain features such as signal duty cycle and pulse repetition period are extracted.

[0113] In this embodiment, the time-frequency conversion can be performed using Fast Fourier Transform (FFT). Specifically, the time-domain radio frequency signal is converted into a spectrum curve through FFT operation; frequency domain information such as center operating frequency, signal bandwidth, sideband distribution, harmonic components, and spectral roll-off slope are extracted from the spectrum curve; the frequency domain information is normalized to eliminate signal strength differences caused by distance, forming standardized frequency domain feature information, i.e., frequency domain feature vector.

[0114] In this embodiment of the application, the target sub-region is determined based on the number of intersections between a ray, determined by a set direction with the target UAV's position information as the endpoint, and the boundaries constituting each sub-region. Figure 10 A flowchart of a method for determining a target sub-region provided in an embodiment of this application is shown below. Figure 10 As shown, step 507 above includes at least the following steps 101-103: Step 101: Determine a ray in a set direction using the target UAV's position information as the endpoint.

[0115] The direction is defined as the direction from the center of the third sub-region to the target UAV. The target UAV's position information is determined using a multi-station direction finding cross-location algorithm. Specifically, based on the known WGS84 positions of multiple detection terminals that detected the target UAV, triangulation is performed using the incident angle of each radio frequency signal to determine the target UAV's position information, which includes the target UAV's WGS84 longitude and latitude coordinates.

[0116] Step 102: Determine the number of intersections between the boundaries of each sub-region and the ray.

[0117] The controlled area includes a first sub-region, a second sub-region, and a third sub-region. This application can determine the number of intersections between the boundary of the third sub-region and the ray by determining the number of intersections between the first target boundary and the ray. This application can determine the number of intersections between the boundary of the second sub-region and the ray by determining the number of intersections between the first target boundary, the second target boundary, and the ray. This application can determine the number of intersections between the boundary of the first sub-region and the ray by determining the number of intersections between the second target boundary, the third target boundary, and the ray.

[0118] Step 103: The sub-regions that intersect with the ray an odd number of times are designated as the target sub-regions.

[0119] In this embodiment, it is first determined whether the number of intersections between the boundary of the first sub-region and the ray is odd. If yes, the first sub-region is taken as the target sub-region, that is, the target drone is currently in the first sub-region. If not, it is determined whether the number of intersections between the boundary of the second sub-region and the ray is odd. If yes, the second sub-region is taken as the target sub-region, that is, the target drone is currently in the second sub-region. If not, it is determined whether the number of intersections between the boundary of the third sub-region and the ray is odd. If yes, the third sub-region is taken as the target sub-region, that is, the target drone is currently in the third sub-region. If not, it is determined that the target drone is not in the controlled area.

[0120] For example, Figure 11 This is a schematic diagram illustrating the determination of a target sub-region provided in an embodiment of this application, such as... Figure 11As shown, the control area includes a first sub-region, a second sub-region, and a third sub-region. The third sub-region is a closed area enclosed by the first target boundary f1. The second sub-region is composed of the first target boundary f1 and the second target boundary f2. The first sub-region is composed of the second target boundary f2 and the third target boundary f3. A ray a is defined with the current position W of the target UAV as the endpoint and the direction from the center O of the third sub-region to the target UAV. The number of intersections between the boundary of the first sub-region and ray a is determined to be 2, meaning that both the second target boundary f2 and the third target boundary f3 intersect ray a. Since the number of intersections between the boundary of the first sub-region and ray a is not odd, the number of intersections between the boundary of the second sub-region and ray a is determined to be 2, meaning that both the first target boundary f1 and the second target boundary f2 intersect ray a. Since the number of intersections between the boundary of the second sub-region and ray a is not odd, the number of intersections between the boundary of the third sub-region and ray a is determined to be 1, meaning that the first target boundary f1 intersects ray a. Since the number of intersections between the boundary of the third sub-region and ray a is odd, the third sub-region is taken as the target sub-region, meaning that the target UAV is currently in the third sub-region.

[0121] Figure 12 This is a schematic diagram of another method for determining a target sub-region, as provided in an embodiment of this application. Figure 12 As shown, the control area includes a first sub-region, a second sub-region, and a third sub-region. The third sub-region is a closed area enclosed by the first target boundary f1. The second sub-region is formed by the first target boundary f1 and the second target boundary f2. The first sub-region is formed by the second target boundary f2 and the third target boundary f3. A ray a is defined with the current position W of the target UAV as the endpoint, pointing from the center O of the third sub-region towards the target UAV. The number of intersections between the boundary constituting the first sub-region and ray a is determined to be 2, meaning both the second target boundary f2 and the third target boundary f3 intersect ray a. Since the number of intersections between the boundary constituting the first sub-region and ray a is not odd, the number of intersections between the boundary constituting the second sub-region and ray a is determined to be 1, meaning the second target boundary f2 intersects ray a, while the first target boundary f1 does not intersect ray a. Since the number of intersections between the boundary constituting the second sub-region and ray a is odd, the second sub-region is designated as the target sub-region, meaning the target UAV is currently located in the second sub-region.

[0122] Figure 13 This is a schematic diagram illustrating the determination of a target sub-region provided in an embodiment of this application, such as... Figure 13As shown, the control area includes a first sub-region, a second sub-region, and a third sub-region. The third sub-region is a closed area enclosed by the first target boundary f1. The second sub-region is formed by the first target boundary f1 and the second target boundary f2. The first sub-region is formed by the second target boundary f2 and the third target boundary f3. A ray a is drawn from the current position W of the target UAV to the direction from the center O of the third sub-region towards the target UAV. The number of intersections between the boundary constituting the first sub-region and ray a is determined to be 1, meaning the third target boundary f3 intersects with ray a, while the second target boundary f2 does not intersect with ray a. Since the number of intersections between the boundary constituting the first sub-region and ray a is odd, the first sub-region is designated as the target sub-region; that is, the target UAV is currently located in the first sub-region.

[0123] In this embodiment of the application, the target countermeasure method is determined based on the second pedestrian density of the target sub-region and the grid region where the target drone is located. Figure 14 A flowchart of a target countermeasure method provided in this application embodiment is shown below. Figure 14 As shown, step 508 above includes at least the following steps 141-142: Step 141: Compare the second pedestrian density with the second pedestrian density threshold to obtain the comparison result.

[0124] In this embodiment of the application, the second pedestrian density threshold can be determined using the following formula. : ;Formula (6) in, Given the rated capacity of the i-th grid area within the controlled area, and the target drone being located in the i-th grid area, m is the total number of grid areas in the controlled area. The settings can be adjusted according to the actual situation, where S is the area of ​​the i-th grid region of the control area, and the second population density threshold is... The unit is (people / km) 2 When the controlled area is a high-density area (such as a scenic spot) or a medium-density area, the second population density threshold is applied. This can be the instantaneous maximum carrying capacity of the i-th grid region; when the controlled area is a low-population-density area (e.g., border or open field), the second population density threshold is... It can take the minimum value.

[0125] Step 142: Based on the target sub-region and the comparison results, determine the target countermeasure method.

[0126] The target sub-region can be the identification information of the sub-region where the target drone is located. Each sub-region corresponds to a unique identification information, which is used to uniquely identify the sub-region. The identification information of each sub-region can consist of multiple characters. For example, the first sub-region in the control area is 001, the second sub-region is 002, and the third sub-region is 003.

[0127] In this embodiment of the application, based on the target sub-region and the comparison results, the target countermeasure method is determined to have the following three cases: In the first case, if the target sub-region is the first sub-region or the second sub-region, a first control command is sent to the countermeasure terminal so that the countermeasure terminal is prohibited from transmitting radio frequency countermeasure signals and forced landing signals based on the first control command, and transmits a voice drive-away signal.

[0128] Countermeasure terminals typically fall into three categories: fixed countermeasure terminals, vehicle-mounted countermeasure terminals, and portable countermeasure terminals. All three types of countermeasure terminals integrate a directional narrowband RF power amplifier module, a BeiDou / GPS (Global Positioning System) navigation decoy signal source, and a segmented power supply circuit. Furthermore, a controllable MOS (Metal-Oxide-Semiconductor) electronic interlock switch is connected in series in the main power supply circuit of the high-power amplifier. The MOS electronic interlock switch is controlled by the level signal of the main control relay. After receiving the first control command, the countermeasure terminal disconnects the MOS electronic interlock switch based on the low-level signal of the first control command to prevent the transmission of RF countermeasure signals and forced landing signals, and transmits a voice warning signal based on the first control command.

[0129] In the second scenario, if the target sub-region is the third sub-region and the comparison result indicates that the second pedestrian density is greater than or equal to the second pedestrian density threshold, then a second control command is sent to the countermeasure terminal to prevent the countermeasure terminal from transmitting radio frequency countermeasure signals and forced landing signals based on the second control command, and to transmit a voice drive-away signal.

[0130] Upon receiving the second control command, the countermeasure terminal disconnects the MOS electronic lockout switch based on the low-level signal of the second control command to prohibit the transmission of radio frequency countermeasure signals and forced landing signals, and transmits a voice drive-away signal based on the second control command.

[0131] In the third case, if the target sub-region is the third sub-region and the comparison result indicates that the second pedestrian density is less than the second pedestrian density threshold, then a third control command is sent to the countermeasure terminal so that the countermeasure terminal can transmit radio frequency countermeasure signals and forced landing signals based on the third control command.

[0132] Upon receiving the third control command, the countermeasure terminal closes the MOS electronic latching switch based on the high-level signal of the third control command to transmit radio frequency countermeasure signals and forced landing signals.

[0133] In this embodiment, after determining that the target drone is an illegal drone, a target alarm method is determined based on the target sub-region and a set correspondence, and an alarm is issued using the target alarm method. The set correspondence is the correspondence between each sub-region and each alarm method. The determination of the target alarm method based on the target sub-region and the set correspondence includes the following three cases: In the first scenario, if the target sub-area is the first sub-area, the first warning sound will be used to trigger an alarm, the first alarm pop-up window will be displayed, and relevant personnel within the first notification range will be notified through the set communication method.

[0134] The first warning sound can be low-frequency white noise, with a frequency of 200-500Hz. The communication method can be set according to actual needs, such as SMS or telephone. The relevant personnel within the first notification range can be set according to actual needs, such as maintenance personnel. Furthermore, when the target sub-region is the first sub-region, a first alarm pop-up window can appear on the current display interface. This first alarm pop-up window can be yellow (#FFFF00) or other colors, but the color of the alarm pop-up window will differ depending on the sub-region. The alarm pop-up window includes information such as the drone identifier, alarm trigger timestamp, drone location, target sub-region, current grid pedestrian density, alarm sound source type, SMS recipient, pop-up level, radio frequency information, and whether countermeasures have been triggered. Each drone corresponds to a unique drone identifier, which can consist of multiple characters. The drone identifier can be a drone UUID (Universally Unique Identifier).

[0135] In the second scenario, if the target sub-area is the second sub-area, the second warning sound will be used to trigger an alarm, and a second alarm pop-up window will be displayed. The relevant personnel within the second notification range will be notified through the set communication method. Based on the target drone's historical location information and current location information, the flight trajectory of the target drone will be determined and displayed.

[0136] The second warning tone can be a mid-frequency warning tone, with a frequency of 1-2 kHz. The communication method can be set according to actual needs, such as SMS or telephone. The first notification range is smaller than the second notification range. The relevant personnel within the second notification range can be set according to actual needs, such as maintenance personnel and security personnel. Furthermore, when the target sub-area is the second sub-area, a second alarm pop-up window can appear on the current display interface. The color of the second alarm pop-up window is different from the first alarm pop-up window; the second alarm pop-up window can be blue (#0066FF) or another color. Each sub-area corresponds to a different alarm pop-up window color, and the color of the alarm pop-up window corresponds to a pop-up level.

[0137] In the third scenario, if the target sub-area is the third sub-area, then the third warning sound will be used to trigger an alarm, a third alarm pop-up will be displayed, and relevant personnel within the third notification range will be notified through the set communication method.

[0138] The first warning tone has a lower frequency than the second, and the second has a lower frequency than the third. The third warning tone can be a high-frequency tone, with a frequency of 3-5 kHz. The communication method can be set according to actual needs, such as SMS or telephone. The first notification range is smaller than the second, and the second is smaller than the third. The relevant personnel within the third notification range can be set according to actual needs, such as maintenance personnel, security personnel, and local police personnel. Furthermore, when the target sub-area is the third sub-area, a third alarm pop-up window can appear on the current display interface. The colors of the first, second, and third alarm pop-ups are different; the third alarm pop-up window can be red (#FF0000) or another color. If the first alarm pop-up corresponding to the first sub-region is yellow, the second alarm pop-up corresponding to the second sub-region is blue, and the third alarm pop-up corresponding to the third sub-region is red, then the red third alarm pop-up has a higher priority than the blue second alarm pop-up, and the blue second alarm pop-up has a higher priority than the yellow first alarm pop-up. The higher the alarm pop-up's priority, the higher its processing priority.

[0139] For example, Figure 15 This is a schematic diagram of a drone alarm provided in an embodiment of this application, as shown below. Figure 15As shown, the drone is in the third sub-area. It uses the third warning sound to issue an alarm and notifies relevant personnel within the third notification range via SMS, namely maintenance personnel, security personnel, and local public security personnel. Then, a third alarm pop-up window appears on the display interface, which includes information such as drone identification, alarm trigger timestamp, drone location, and target sub-area.

[0140] This application provides a drone countermeasure device. The drone countermeasure device adopts a five-layer hardware topology architecture consisting of a main control hub layer, a heterogeneous detection layer, a hierarchical alarm layer, a hierarchical countermeasure execution layer, and an encrypted storage layer. It is electrically interconnected by five functional modules: a main control server unit, a multi-form Mesh self-organizing network detection unit, a hierarchical multimodal audible and visual alarm unit, a hierarchical controllable interlocking countermeasure execution unit, and a hardware encrypted evidence storage unit. The units are interconnected through three communication protocols: Ethernet TCP (Transmission Control Protocol) / IP (Internet Protocol), RS485 (Recommended Standard 485) industrial bus, and LoRa wireless to achieve multi-source data interaction. All hardware selections comply with T / AOPA 0067-2024 (Industry Technical Standard for Handheld Drone Countermeasure Equipment).

[0141] The main control server unit is configured with an industrial-grade x86 (Intel Architecture 8086) main control motherboard, equipped with an ARM Cortex-A53 main control chip (a processor based on the Reduced Instruction Set Computer (RISC) architecture) and an FPGA (Field Programmable Gate Array) floating-point coprocessor. It features 8GB of industrial-grade DDR4 (Double Data Rate 4 Synchronous Dynamic Random Access Memory) memory, dual gigabit Ethernet ports, four RS485 (a serial communication standard) isolated serial ports, and multiple relay-level output pins. Peripherals include third-party passenger flow terminals (infrared passenger flow counters, video AI passenger flow statistics gateways), a 4G (4th Generation Mobile Communication Technology) SMS modem, and a host computer management platform server. The x86 architecture refers to the computer language instruction set executed by a microprocessor, representing a common set of computer instructions.

[0142] The main control server unit is embedded with four software engines: a dynamic variable path layer algorithm engine, a hierarchical alarm four-dimensional mapping engine, a pedestrian flow data standardization and analysis engine, and a two-factor counter-locking decision engine.

[0143] The dynamic variable diameter concentric circle algorithm engine internally stores correction coefficients corresponding to each pedestrian density range. For example, the correction coefficient K1=0 for the first pedestrian density range (high pedestrian density range), the correction coefficient K2=0.35 for the second pedestrian density range (medium pedestrian density range), and the correction coefficient K3=0.8 for the third pedestrian density range (low pedestrian density range). The dynamic variable diameter concentric circle algorithm engine receives the first pedestrian density of the controlled area and determines the corresponding correction coefficient based on the pedestrian density range to which the first pedestrian density belongs. Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set first radial distance, the radial distance of the first original sub-region is determined using the above formula (2). Based on the radial distance of the first original sub-region and the set weight coefficient, the radial distance of the second original sub-region is determined using the above formula (4). Based on the set second radial distance and the correction coefficient, the radial distance of the third original sub-region is determined using the above formula (3). The dynamic variable-diameter concentric circle algorithm engine determines each sub-region based on its radial distance and original boundary. Specifically, for each sub-region, using its original boundary as a reference, the engine extends or contracts its radial distance outward or inward along the normal direction of the original boundary to obtain the corresponding target boundary. Each sub-region is then derived from these three target boundaries. The engine supports manual drawing of irregular temporary control boundaries by maintenance personnel through a user interface. The engine synchronously refreshes all-domain partition parameters in real time and distributes fixed / vehicle-mounted / portable detection and countermeasure points based on the generated sub-region boundaries.

[0144] The hierarchical alarm four-dimensional mapping engine has a built-in four-dimensional mapping data table for target sub-regions, audio parameters, SMS routing, and pop-up priority. It pre-loads the audio sampling rate, output frequency range, SMS receiving number grouping, and pop-up RGB (Red / Green / Blue) background color parameters for the first, second, and third sub-regions. After the main control server unit determines the target sub-region (the sub-region where the target drone is located), it automatically retrieves the corresponding parameters and sends them to the alarm hardware.

[0145] The pedestrian flow data standardization and parsing engine is compatible with the private protocols of mainstream pedestrian flow equipment, and standardizes multi-format pedestrian flow density data into a format of people / km² (people / square kilometer), eliminating abnormal jump values ​​from equipment and ensuring the stability of input data for countermeasure decisions.

[0146] The two-factor counter-locking decision engine synchronously collects two parameters: the target sub-region (the sub-region where the target drone is located) and the second pedestrian density of the grid region where the target drone is located. The internal logic gates output high and low levels to control the counter-locking switch of the counter-locking unit. When the target sub-region is the first or second sub-region, a low level is output, disconnecting the MOS electronic lockout switch to cut off the main power supply circuit of the high-power amplifier. When the target sub-region is the third sub-region, and the second pedestrian density is greater than or equal to the second pedestrian density threshold, a low level is output, disconnecting the MOS electronic lockout switch to cut off the main power supply circuit of the high-power amplifier. When the target sub-region is the third sub-region, and the second pedestrian density is less than the second pedestrian density threshold, a high level is output, closing the MOS electronic lockout switch to connect the main power supply circuit of the high-power amplifier.

[0147] This multi-form Mesh self-organizing network detection unit comprises three types of hardware detection terminals, all employing an SDR software-defined radio receiver architecture. The detection frequency band covers the 433MHz–6GHz universal communication band for all UAVs (2.4GHz remote control, 5.8GHz image transmission, 900MHz industrial remote control, and GNSS navigation bands). The three types of detection terminals include fixed, vehicle-mounted, and portable terminals. Fixed detection terminals are deployed at airports and government compound perimeters, integrating a 77GHz millimeter-wave radar and a wideband spectrum acquisition chip, with a detection radius of 8km and a built-in RF fingerprint database of over 200 mainstream UAVs. Vehicle-mounted detection terminals are mounted on security patrol vehicles, integrating an infrared optoelectronic gimbal and a superheterodyne RF receiver module, with a detection radius of 5km, supporting mobile, full-area patrols. Portable detection terminals are handheld deployments for scenic area gates and temporary event security, integrating narrowband RF receiver circuitry, with a 12-hour battery life and a detection radius of 3km. The three types of detection terminals are interconnected based on the LoRa Mesh self-organizing network protocol. When any single device experiences a power failure, adjacent detection terminals automatically increase their radio frequency receiving gain by 3-6 dB to fill in the airspace blind spots and eliminate single-point detection blind zones. After completing radio frequency signal acquisition, the detection terminals package and upload the radio frequency information, target drone model, frequency, latitude and longitude coordinates, and signal strength to the main control server unit through a 5G (5th Generation Mobile Communication Technology) industrial module.

[0148] The hierarchical multimodal audio-visual alarm unit includes hardware such as a multi-frequency domain DSP (Digital Signal Processor) audio decoding chip, a multi-channel 4G SMS modem module, a host computer pop-up driver control board, and a three-color active audio-visual alarm. The DSP chip pre-stores three sets of differentiated sound sources: the first sub-region corresponds to the first warning sound, i.e., low-frequency white noise (200-500Hz); the second sub-region corresponds to the second warning sound, i.e., a mid-frequency warning sound (1-2kHz); and the third sub-region corresponds to the third warning sound, i.e., a dedicated high-frequency alarm sound for unauthorized flights (3-5kHz). The communication method is typically set to SMS. The SMS modem is divided into three whitelists: the first sub-region corresponds to the numbers of relevant personnel within the first notification range, i.e., maintenance personnel numbers; the second sub-region corresponds to the numbers of relevant personnel within the second notification range, i.e., maintenance personnel numbers and security personnel numbers. The code; the numbers of relevant personnel within the third notification scope corresponding to the third sub-region, namely the operation and maintenance personnel number, the security manager number, and the local public security personnel number (local public security emergency contact number); the color of the first pop-up window corresponding to the first sub-region is yellow (#FFFF00), the color of the second pop-up window corresponding to the second sub-region is blue (#0066FF), and the color of the third pop-up window corresponding to the third sub-region is red (#FF0000). After the main control server unit determines the sub-region where the target drone is located as the target sub-region and issues the target sub-region, the hardware synchronously switches the audio source, SMS sending group, and pop-up window background color. When the target drone flies continuously across sub-regions, the target sub-region is refreshed in real time, and the alarm parameters change step by step in milliseconds.

[0149] The graded controllable interlocking countermeasure execution unit includes three types of countermeasure terminals: fixed countermeasure terminals, vehicle-mounted countermeasure terminals, and portable countermeasure terminals. Each countermeasure terminal integrates a directional narrowband RF power amplifier module, a Beidou / GPS navigation decoy signal source, a segmented power supply circuit, and a high-power amplifier main power supply circuit connected in series with a controllable MOS electronic interlocking switch. When the MOS electronic interlocking switch is on, the high-power RF power amplifier is powered on, and the countermeasure terminal can output directional RF interference (RF countermeasure signal) and navigation decoy signal (forced landing signal). When the MOS electronic interlocking switch is off, it directly cuts off the high-power amplifier main power supply circuit, completely shutting down high-power RF transmission, retaining only a low-power voice warning alarm, and eliminating active electromagnetic interference output. The MOS electronic interlocking switch is controlled by the main control relay level signal, which is a high / low level control command issued by the main control server unit. The main control server unit makes a decision based on the target sub-area and the second pedestrian density, and outputs the corresponding voltage level signal to the relay inside the countermeasure unit. If the main control server unit outputs a high-level signal, the relay will engage, driving the MOS electronic interlock switch to close, thus powering the power amplifier and connecting the main power supply circuit of the high-power amplifier, allowing high-power RF countermeasure output, i.e., transmitting RF countermeasure signals and navigation decoy signals (forced landing signals); if the main control server unit outputs a low-level signal, the relay will disengage, and the MOS electronic interlock switch will simultaneously disengage, cutting off the power amplifier power supply and the main power supply circuit of the high-power amplifier, forcibly shutting down the transmission of high-power RF countermeasure signals and navigation decoy signals (forced landing signals); the voltage level signal is a hardware-level control command, which is not subject to tampering by upper-level software programs, ensuring compliance with spectrum management in dense scenarios.

[0150] Specifically, when the main control server unit determines that the target sub-region is the first or second sub-region, it sends a first control command to the countermeasure terminal of the hierarchical controllable interlocking countermeasure execution unit. Upon receiving the low-level signal in the first control command, the countermeasure terminal disconnects the relay, and the MOS electronic interlocking switch simultaneously disconnects, cutting off the power amplifier's power supply and the main power supply circuit of the high-power amplifier. It also shuts down the transmission of the high-power RF countermeasure signal and the navigation deception signal (forced landing signal), retaining only a 1W low-frequency voice drive-away signal output and storing an alarm log. The alarm log includes information such as the drone's UUID, alarm trigger timestamp, target latitude and longitude, target sub-region, current grid population density, alarm sound source type, SMS recipient, pop-up level, RF signal, and whether countermeasure interlocking was triggered. Therefore, when the target sub-region is the first or second sub-region, the main control server unit continuously outputs a low-level signal, and the MOS electronic interlocking switch simultaneously disconnects the high-power RF amplifier's power supply circuit. Under hardware interlocking conditions, the software cannot independently activate the high-power RF amplifier's transmission path.

[0151] The main control server unit determines that the target sub-region is the third sub-region and that the second pedestrian density is greater than or equal to the second pedestrian density threshold. Then, it sends a second control command to the countermeasure terminal of the hierarchical controllable interlocking countermeasure execution unit. The countermeasure terminal receives the low-level signal in the second control command, the relay is disconnected, the MOS electronic interlocking switch is disconnected synchronously, the power amplifier power supply is cut off, the main power supply circuit of the high-power power amplifier is cut off, the high-power radio frequency countermeasure signal transmission and the navigation deception signal (forced landing signal) transmission are turned off, and only the 1W low-frequency voice drive-away signal output is retained.

[0152] The main control server unit determines that the target sub-region is the third sub-region, and that the second pedestrian density is less than the second pedestrian density threshold. Then, it sends a third control command to the countermeasure terminal of the hierarchical controllable interlocking countermeasure execution unit. Upon receiving the high-level signal in the third control command, the countermeasure terminal activates the relay, closes the MOS electronic interlocking switch, and powers the power amplifier, activating the main power supply circuit of the high-power amplifier. This allows for high-power radio frequency countermeasure output, namely, the transmission of radio frequency countermeasure signals and navigation deception signals (forced landing signals). Specifically, when the target sub-region is determined to be the third sub-region and the second pedestrian density is less than the second pedestrian density threshold, the relay on the high-level drive board of the countermeasure terminal is activated, the MOS electronic interlock switch is turned on, the main circuit of the high-power RF amplifier is powered on, and the 15dB gain directional antenna is used to align with the coordinates of the target drone. The narrowband RF module of the countermeasure terminal outputs the corresponding frequency band signal to accurately suppress the remote control and image transmission communication links of the target drone. At the same time, the Beidou / GPS navigation deception module of the countermeasure terminal is activated to send a fake satellite positioning signal to the target drone. The target drone's flight control detects the abnormal positioning and automatically triggers the protection program to make an emergency landing.

[0153] The fixed countermeasure terminal receives instructions from the main control server unit to remotely initiate directional radio frequency output. These instructions can be third-party control instructions, including some or all of the target identification basic parameters, directional antenna control parameters, radio frequency suppression channel parameters, navigation deception control parameters, and hardware-level control level instructions. Target identification basic parameters include the unique UUID of this black flight incident, the drone model code, the target's real-time WGS84 latitude and longitude, and the target sub-region. Directional antenna control parameters include the antenna's horizontal / tilt angle and the directional antenna 15dB gain activation instruction, enabling the antenna to be aligned with the drone's location for narrowband directional transmission. Radio frequency suppression channel parameters include the enabled narrowband interference frequency bands (5.8GHz, 2.4GHz, 900MHz channels for drone remote control / image transmission), the radio frequency output power level, and the continuous transmission duration threshold. Navigation deception control parameters include the BeiDou / GPS fake positioning signal switch and false coordinate offset parameters, used to simultaneously issue forced landing deception instructions. The hardware-level control level command is a high-level output command, which drives the internal MOS electronic interlock switch of the countermeasure terminal to conduct, supplying power to the high-power RF amplifier circuit and allowing RF signal transmission. This command can also be a first control command or a second control command, which includes some or all of the target recognition basic parameters, voice disengagement commands, navigation deception control parameters, and the hardware-level control level command. A low-level hardware-level control level command drives the internal MOS electronic interlock switch of the countermeasure terminal to disengage, preventing power supply to the high-power RF amplifier circuit and prohibiting RF countermeasure signal transmission. The navigation deception control parameters prohibit the issuance of forced landing deception commands.

[0154] The portable countermeasure terminal receives SMS messages and platform instructions from the main control server unit, prompting on-site security personnel to rush to the target location and verbally drive the drone away. The platform instructions are digital data packets sent from the control platform to the portable / vehicle-mounted terminal, containing information such as the unauthorized flight incident number, drone coordinates, alarm level, and countermeasures such as driving away or forcing a landing. The vehicle-mounted countermeasure terminal, relying on the target coordinates transmitted back from the platform, moves to the controlled airspace for on-site handling.

[0155] The hardware-encrypted forensic storage unit is equipped with an industrial-grade SSD (Solid State Drive) and an independent hardware SHA256 encryption security chip, rather than software encryption. For illegal drones, the drone countermeasure system automatically collects the following structured raw data: drone model code, full-time 3D flight trajectory coordinates, raw radio frequency sampling spectrum frames, alarm messages at all levels, countermeasure hardware control level records, and pilot positioning latitude and longitude. The full-time 3D flight trajectory coordinates are the continuous collection of each set of longitude, latitude, and altitude points from the moment the drone is first detected until the signal disappears / current moment; that is, a complete set of spatial coordinates recorded uninterruptedly from the first detection of the drone to the moment the signal disappears / current moment. The raw radio frequency sampling spectrum frames are the radio frequency signals continuously collected from the moment the drone is first detected until the signal disappears. Alarm messages include event UUID, alarm timestamp, target sub-region, drone coordinates, crowd density value, alarm sound source type, SMS push recipient, pop-up warning level, and the radio frequency band that triggered the alarm. The countermeasure hardware control level record includes information such as the high and low levels of each decision output, output time, judgment conditions, MOS electronic latching switch on / off status, and RF power amplifier power supply start / stop records from the initial detection of the drone to the signal disappearance / current moment. The drone operator's location latitude and longitude includes the WGS84 latitude and longitude of the ground remote controller operator from the initial detection of the drone to the signal disappearance / current moment, calculated by a multi-detection terminal direction finding and intersection algorithm.

[0156] For each piece of structured raw data generated, the drone countermeasure system uses a hardware encryption chip to perform a hash operation on the raw data in real time using the SHA256 algorithm to generate a 256-bit irreversible hash checksum. The raw data and the hash checksum are paired and written to an SSD solid-state storage sector, ensuring that the raw data cannot be tampered with by any background operation after storage. The drone countermeasure system uses the unique UUID of each unauthorized drone flight incident as an index to automatically aggregate the entire data chain and generate PDF (Portable Document Format) judicial files. A USB (Universal Serial Bus) encrypted export interface is reserved, and the files can only be retrieved by authorized law enforcement keys.

[0157] For legitimate drones, the drone countermeasure system only records information such as device number, whitelist ID, flight time, flight trajectory, and signal spectrum snapshot in a lightweight manner. It does not generate alarms, countermeasure level records, or package administrative law enforcement files. It only performs daily passage archiving and does not perform the SHA256 mandatory solidification evidence preservation process.

[0158] The following examples illustrate the aforementioned methods for countering drones: Example 1: The controlled area is a park with high pedestrian traffic. The WGS84 boundary coordinates of the park are entered to obtain the original boundaries of each original sub-region within the controlled area. The pre-entered correspondence between pedestrian density ranges and correction coefficients is as follows: correction coefficient K1=0 for the first pedestrian density range (high pedestrian density range), K2=0.35 for the second pedestrian density range (medium pedestrian density range), and K3=0.8 for the third pedestrian density range (low pedestrian density range). The current pedestrian density of the controlled area is obtained, and the pedestrian density range to which the first pedestrian density belongs is determined as the first pedestrian density range. The correction coefficient K1 is set to 0. Based on the correction coefficient K1, the first pedestrian density threshold, the first pedestrian density, and the set radial distance, the radial distance of the first original sub-region (yellow zone) is determined to be 1.8km, the radial distance of the second original sub-region (blue zone) is 0.6km, and the radial distance of the third original sub-region (red zone) is 0km. Since the radial distance of the third original sub-region is 0km, the original boundary of the third original sub-region is determined as the first target boundary. Based on the first target boundary, the third sub-region (red zone) is determined, that is, the closed area enclosed by the first target boundary is the third sub-region (red zone). Taking the original boundary of the second original sub-region as the reference, extend outward by 0.6km along the normal direction of the original boundary of the second original sub-region, that is, the radial distance of the second original sub-region, to obtain the second target boundary. Based on the first target boundary and the second target boundary, the second sub-region (blue zone) is determined. Taking the original boundary of the first original sub-region as the reference, extend outward by 1.8km along the normal direction of the original boundary of the first original sub-region, that is, the radial distance of the first original sub-region, to obtain the third target boundary. Based on the second target boundary and the third target boundary, the first sub-region (yellow zone) is determined.

[0159] Twelve portable detection terminals are deployed along a 3km ring road outside the controlled area. These terminals perform spectrum scanning on the target drone to obtain its radio frequency (RF) signal. Feature extraction is then performed on this RF signal to obtain RF characteristic information. Based on this RF characteristic information and multiple pre-defined RF characteristic information, the target drone is identified as an illegal drone. If the sub-area (target sub-area) where the target drone is located is a third sub-area, a third warning sound (a 3-5kHz exclusive black flight alarm sound) is triggered, and an alarm SMS containing the target's latitude and longitude is automatically sent to relevant personnel. A red highlighted pop-up warning window appears on the system interface.

[0160] If the current pedestrian density in the grid area where the target drone is located is 286 people / square kilometer and the threshold for the second pedestrian density is 150 people / square kilometer, then it is determined that the second pedestrian density is greater than the threshold, and the target sub-area is a third sub-area. The main control server unit then sends a second control command to the countermeasure terminal, causing the countermeasure terminal to prohibit the transmission of radio frequency countermeasure signals and forced landing signals, and to transmit a voice warning signal, i.e., forcibly disabling high-power interference, and outputting a manual capture and disposal plan. Relevant personnel, relying on the drone coordinates and pilot GPS positioning transmitted back by the platform, apprehend the operator of the unauthorized drone. The full detection spectrum, alarm messages, and countermeasure lockout level records are encrypted and stored using hardware SHA256, automatically generating an administrative penalty file. The regulatory department then imposes a fine on the party involved based on the file.

[0161] Example 2: The controlled area is a border wilderness area, i.e., a low-population, open scene. The irregular GIS boundary of this controlled area is entered, obtaining the original boundaries of each original sub-region of the controlled area. The pre-entered correspondence between the population density range and the correction coefficient is as follows: the correction coefficient K1=0 for the first population density range (high population density range), K2=0.35 for the second population density range (medium population density range), and K3=0.8 for the third population density range (low population density range). The current population density of the controlled area is obtained, and the population density range to which the first population density belongs is determined to be the third population density range, with the correction coefficient K3=0.8. Based on the correction coefficient K3, the first population density threshold, the first population density, and the set radial distance, the radial distance of the first original sub-region (yellow zone) is determined to be 2.2km, the radial distance of the second original sub-region (blue zone) is 1.2km, and the radial distance of the third original sub-region (red zone) is 0.8km. Using the original boundary of the third original sub-region as a reference, extend outward by 0.8 km along the normal direction of the original boundary of the third original sub-region, which is the radial distance of the third original sub-region, to obtain the first target boundary. Based on the first target boundary, determine the third sub-region (red zone), that is, the closed area enclosed by the first target boundary is the third sub-region (red zone). Using the original boundary of the second original sub-region as a reference, extend outward by 1.2 km along the normal direction of the original boundary of the second original sub-region, which is the radial distance of the second original sub-region, to obtain the second target boundary. Based on the first target boundary and the second target boundary, determine the second sub-region (blue zone). Using the original boundary of the first original sub-region as a reference, extend outward by 2.2 km along the normal direction of the original boundary of the first original sub-region, which is the radial distance of the first original sub-region, to obtain the third target boundary. Based on the second target boundary and the third target boundary, determine the first sub-region (yellow zone).

[0162] Fixed radar detection points and vehicle-mounted mobile countermeasure points are deployed along the boundaries of each sub-region of the controlled area. The detection terminal performs spectrum scanning on the target drone to obtain radio frequency signals. Feature extraction is performed on these radio frequency signals to obtain radio frequency characteristic information. Based on this radio frequency characteristic information and multiple preset radio frequency characteristic information, the target drone is identified as an illegal drone. If the sub-region where the target drone is located (the target sub-region) is the third sub-region, a third warning sound is triggered, and an alarm SMS containing the target's latitude and longitude is automatically sent to relevant personnel. A red highlighted pop-up warning window appears on the system interface.

[0163] If the current pedestrian density in the grid area where the target drone is located is 12 people / square kilometer, and the threshold for the second pedestrian density is 150 people / square kilometer, then it is determined that the second pedestrian density is less than the threshold, and the target sub-area is a third sub-area. In this case, the main control server unit sends a third control command to the countermeasure terminal, causing the countermeasure terminal to transmit radio frequency countermeasure signals and forced landing signals based on the third control command. That is, the fixed countermeasure terminal initiates narrowband navigation deception, inducing the target drone to make an emergency landing within the controlled area. All data is encrypted and archived throughout the entire process, and the case file is retained for record-keeping.

[0164] In this embodiment, the radial distance of each original sub-region of the control area is determined based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density of the control area, and the set radial distance. Based on the radial distance of each original sub-region and the original boundary of each original sub-region, each sub-region is determined, realizing millisecond-level adaptive scaling of each sub-region of the control area. It adapts to irregular scenic spots, winding borders and other irregular protective boundaries, supports instantaneous full-domain refresh of hand-drawn temporary control boundaries, reduces the time required for temporary deployment, significantly reduces the false alarm rate of target sub-regions of illegal drones, and significantly improves the identification accuracy of illegal drones.

[0165] Furthermore, this application constructs a four-dimensional binding data table for target sub-regions, warning sounds, SMS routing, and pop-up priority. The target drone's cross-regional displacement synchronously upgrades all parameters with alarms, and the three-level sub-regions correspond to differentiated warning sounds, tiered SMS recipients, and three-color pop-up backgrounds. Compared to existing technologies that rely on a single sound source and mass SMS messaging to all personnel without any hierarchical mapping logic, making it impossible to differentiate threat levels through alarms, this application significantly improves the speed at which relevant personnel can identify threat levels, enhances the efficiency of handling high-risk scenarios, and greatly reduces the number of false alarms.

[0166] This application adds a MOS electronic interlock switch to the main power supply circuit of the RF power amplifier in the countermeasure terminal. Based on the relationship between the target sub-region and the second pedestrian density and the second pedestrian density threshold, it determines whether to disconnect the MOS electronic interlock switch, i.e., whether to physically cut off the high-power RF power supply. This achieves scenario-adaptive differentiated countermeasures. Compared with existing countermeasure technologies that only control RF start / stop via software and lack hardware interlocking structures, this significantly reduces the probability of radio accidental injury in densely populated areas and reduces ineffective high-power countermeasure actions. Furthermore, in this application, irreversible hash checksums are automatically generated before the entire process business data is written to the industrial SSD. The original data and checksums are bound together and immutable. The system automatically packages standardized judicial files according to the black flight event ID, supporting one-click export from law enforcement terminals, improving evidence collection efficiency.

[0167] Based on the same technical concept, this application provides an exemplary anti-drone device, such as... Figure 16 As shown, the device includes: Extraction module 161 is used to extract features from radio frequency signals to obtain radio frequency feature information. The radio frequency signals are obtained by the detection terminal after performing a spectrum scan on the target UAV. The first determining module 162 is used to determine that the target drone is an illegal drone if there is no set radio frequency feature information that matches the radio frequency feature information among the multiple set radio frequency feature information. The second determining module 163 is used to determine the sub-region where the target drone is located as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on the correction coefficient and the first population density of the control area. The correction coefficient is determined based on the first population density. The countermeasure module 164 is used to determine a target countermeasure method based on the second pedestrian density of the target sub-region and the grid region where the target drone is located, and to countermeasure the target drone using the target countermeasure method. The control area includes multiple grid regions.

[0168] Optionally, before performing feature extraction on the radio frequency signal to obtain radio frequency feature information, the extraction module 161 is further configured to: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set radial distance, the radial distance of each original sub-region of the controlled area is determined; Each sub-region is determined based on its radial distance and its original boundary.

[0169] Optionally, the set radial distance includes a first radial distance and a second radial distance, the controlled area includes a first original sub-region, a second original sub-region, and a third original sub-region, and the extraction module 161 is used for: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the first radial distance, the radial distance of the first original sub-region is determined; and based on the second radial distance and the correction coefficient, the radial distance of the third original sub-region is determined. The radial distance of the second original sub-region is determined based on the radial distance of the first original sub-region and the set weight coefficient; The first original sub-region is the region formed by the original boundary of the first original sub-region and the original boundary of the second original sub-region. The second original sub-region is the region formed by the original boundary of the second original sub-region and the original boundary of the third original sub-region. The third original sub-region is a closed region enclosed by the original boundary of the third original sub-region.

[0170] Optionally, the extraction module 161 is used for: Using the original boundary of the third original sub-region as a reference, the radial distance of the third original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the third original sub-region to obtain the first target boundary, and the third sub-region is determined based on the first target boundary. Using the original boundary of the second original sub-region as a reference, extend or contract the radial distance of the second original sub-region outward or inward along the normal direction of the original boundary of the second original sub-region to obtain the second target boundary, and determine the second sub-region based on the first target boundary and the second target boundary; Using the original boundary of the first original sub-region as a reference, the radial distance of the first original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the first original sub-region to obtain the third target boundary, and the first sub-region is determined based on the second target boundary and the third target boundary.

[0171] Optionally, the countermeasure module 164 is used for: The second pedestrian density is compared with the second pedestrian density threshold to obtain the comparison result; Based on the target sub-region and the comparison results, the target countermeasure method is determined.

[0172] Optionally, the countermeasure module 164 is used for: If the target sub-region is a first sub-region or a second sub-region, a first control command is sent to the countermeasure terminal so that the countermeasure terminal prohibits the transmission of radio frequency countermeasure signals and forced landing signals based on the first control command, and transmits a voice drive-away signal. If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is greater than or equal to the second pedestrian density threshold, then a second control command is sent to the countermeasure terminal to make the countermeasure terminal prohibit the transmission of radio frequency countermeasure signals and forced landing signals based on the second control command, and transmit a voice drive-away signal; If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is less than the second pedestrian density threshold, then a third control command is sent to the countermeasure terminal so that the countermeasure terminal transmits a radio frequency countermeasure signal and a forced landing signal based on the third control command.

[0173] Optionally, after determining that the target drone is an illegal drone, the first determining module 162 is further configured to: Based on the target sub-region and the established correspondence, a target alarm method is determined, and an alarm is issued using the target alarm method. The established correspondence is the correspondence between each sub-region and each alarm method.

[0174] Optionally, the first determining module 162 is used to: If the target sub-region is the first sub-region, then the first warning sound will be used to sound an alarm, the first alarm pop-up window will be displayed, and relevant personnel within the first notification range will be notified through the set communication method. If the target sub-region is the second sub-region, then a second warning sound is used to sound an alarm, a second alarm pop-up window is displayed, relevant personnel within the second notification range are notified through a set communication method, and the flight trajectory of the target drone is determined and displayed based on the historical and current location information of the target drone. If the target sub-region is the third sub-region, then a third alarm sound will be used to sound an alarm, a third alarm pop-up window will be displayed, and relevant personnel within the third notification range will be notified through the set communication method. The frequency of the first warning sound is lower than that of the second warning sound, and the frequency of the second warning sound is lower than that of the third warning sound; the colors of the first alarm pop-up, the second alarm pop-up, and the third alarm pop-up are different; the range of the first notification is smaller than that of the second notification, and the range of the second notification is smaller than that of the third notification.

[0175] Optionally, the second determining module 163 is used to: A ray is determined with the position information of the target UAV as the endpoint and a set direction is defined, wherein the set direction is the direction from the center of the third sub-region to the target UAV. Determine the number of intersections between the boundaries of each sub-region and the ray; The sub-regions that intersect the ray an odd number of times are designated as the target sub-regions.

[0176] Based on the same inventive concept, this application provides an electronic device that can realize the functions of the drone countermeasure device discussed above. Please refer to... Figure 17 The device includes a processor 171 and a memory 172, wherein the memory 172 is used to store program instructions; The processor 171 calls the program instructions stored in the memory and executes the program instructions to perform the following steps: Radio frequency (RF) signals are subjected to feature extraction to obtain RF feature information. The RF signals are obtained by the detection terminal after performing a spectrum scan on the target UAV. If none of the multiple set radio frequency feature information matches the set radio frequency feature information, then the target drone is determined to be an illegal drone; The sub-region where the target drone is located is determined as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on the correction coefficient and the first population density of the control area. The correction coefficient is determined based on the first population density. Based on the second pedestrian density of the target sub-region and the grid region where the target drone is located, a target countermeasure method is determined, and the target countermeasure method is used to counter the target drone. The control area includes multiple grid regions.

[0177] Optionally, before performing feature extraction on the radio frequency signal to obtain radio frequency feature information, the processor 171 is further configured to perform: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set radial distance, the radial distance of each original sub-region of the controlled area is determined; Each sub-region is determined based on its radial distance and its original boundary.

[0178] Optionally, the set radial distance includes a first radial distance and a second radial distance, and the controlled area includes a first original sub-region, a second original sub-region, and a third original sub-region. Determining the radial distance of each original sub-region of the controlled area based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set radial distance includes: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the first radial distance, the radial distance of the first original sub-region is determined; and based on the second radial distance and the correction coefficient, the radial distance of the third original sub-region is determined. The radial distance of the second original sub-region is determined based on the radial distance of the first original sub-region and the set weight coefficient; The first original sub-region is the region formed by the original boundary of the first original sub-region and the original boundary of the second original sub-region. The second original sub-region is the region formed by the original boundary of the second original sub-region and the original boundary of the third original sub-region. The third original sub-region is a closed region enclosed by the original boundary of the third original sub-region.

[0179] Optionally, determining each sub-region based on the radial distance and the original boundary of each original sub-region includes: Using the original boundary of the third original sub-region as a reference, the radial distance of the third original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the third original sub-region to obtain the first target boundary, and the third sub-region is determined based on the first target boundary. Using the original boundary of the second original sub-region as a reference, extend or contract the radial distance of the second original sub-region outward or inward along the normal direction of the original boundary of the second original sub-region to obtain the second target boundary, and determine the second sub-region based on the first target boundary and the second target boundary; Using the original boundary of the first original sub-region as a reference, the radial distance of the first original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the first original sub-region to obtain the third target boundary, and the first sub-region is determined based on the second target boundary and the third target boundary.

[0180] Optionally, the method for determining the target countermeasure based on the second pedestrian density of the target sub-region and the grid region where the target drone is located includes: The second pedestrian density is compared with the second pedestrian density threshold to obtain the comparison result; Based on the target sub-region and the comparison results, the target countermeasure method is determined.

[0181] Optionally, determining the target countermeasure method based on the target sub-region and the comparison result includes: If the target sub-region is a first sub-region or a second sub-region, a first control command is sent to the countermeasure terminal so that the countermeasure terminal prohibits the transmission of radio frequency countermeasure signals and forced landing signals based on the first control command, and transmits a voice drive-away signal. If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is greater than or equal to the second pedestrian density threshold, then a second control command is sent to the countermeasure terminal to make the countermeasure terminal prohibit the transmission of radio frequency countermeasure signals and forced landing signals based on the second control command, and transmit a voice drive-away signal; If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is less than the second pedestrian density threshold, then a third control command is sent to the countermeasure terminal so that the countermeasure terminal transmits a radio frequency countermeasure signal and a forced landing signal based on the third control command.

[0182] Optionally, after determining that the target drone is an illegal drone, the processor 161 is further configured to perform: Based on the target sub-region and the established correspondence, a target alarm method is determined, and an alarm is issued using the target alarm method. The established correspondence is the correspondence between each sub-region and each alarm method.

[0183] Optionally, the method for determining target alarms based on the target sub-region and the established correspondence includes: If the target sub-region is the first sub-region, then the first warning sound will be used to sound an alarm, the first alarm pop-up window will be displayed, and relevant personnel within the first notification range will be notified through the set communication method. If the target sub-region is the second sub-region, then a second warning sound is used to sound an alarm, a second alarm pop-up window is displayed, relevant personnel within the second notification range are notified through a set communication method, and the flight trajectory of the target drone is determined and displayed based on the historical and current location information of the target drone. If the target sub-region is the third sub-region, then a third alarm sound will be used to sound an alarm, a third alarm pop-up window will be displayed, and relevant personnel within the third notification range will be notified through the set communication method. The frequency of the first warning sound is lower than that of the second warning sound, and the frequency of the second warning sound is lower than that of the third warning sound; the colors of the first alarm pop-up, the second alarm pop-up, and the third alarm pop-up are different; the range of the first notification is smaller than that of the second notification, and the range of the second notification is smaller than that of the third notification.

[0184] Optionally, determining the sub-region where the target UAV is located as the target sub-region includes: A ray is determined with the position information of the target UAV as the endpoint and a set direction is defined, wherein the set direction is the direction from the center of the third sub-region to the target UAV. Determine the number of intersections between the boundaries of each sub-region and the ray; The sub-regions that intersect the ray an odd number of times are designated as the target sub-regions.

[0185] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium. The computer program product includes computer program code, which, when executed on a computer, causes the computer to perform any of the drone countermeasure methods discussed above. Since the principle by which the above-described computer-readable storage medium solves the problem is similar to that of the drone countermeasure methods, the implementation of the above-described computer-readable storage medium can be found in the implementation of the methods, and repeated details will not be elaborated further.

[0186] Based on the same inventive concept, this application also provides a computer program product, which includes computer program code. When the computer program code is run on a computer, it causes the computer to execute any of the drone countermeasure methods discussed above. Since the principle of the above-described computer program product in solving the problem is similar to that of the drone countermeasure methods, the implementation of the above-described computer program product can be referred to the implementation of the method, and repeated details will not be repeated.

[0187] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0188] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0189] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0190] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of user-operated steps to be executed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0191] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for countering unmanned aerial vehicles (UAVs), characterized in that, include: Radio frequency (RF) signals are subjected to feature extraction to obtain RF feature information. The RF signals are obtained by the detection terminal after performing a spectrum scan on the target UAV. If none of the multiple set radio frequency feature information matches the set radio frequency feature information, then the target drone is determined to be an illegal drone; The sub-region where the target drone is located is determined as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on the correction coefficient and the first population density of the control area. The correction coefficient is determined based on the first population density. Based on the second pedestrian density of the target sub-region and the grid region where the target drone is located, a target countermeasure method is determined, and the target countermeasure method is used to counter the target drone. The control area includes multiple grid regions.

2. The method as described in claim 1, characterized in that, Before performing feature extraction on the radio frequency signal to obtain radio frequency feature information, the method further includes: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set radial distance, the radial distance of each original sub-region of the controlled area is determined; Each sub-region is determined based on its radial distance and its original boundary.

3. The method as described in claim 2, characterized in that, The set radial distance includes a first radial distance and a second radial distance. The controlled area includes a first original sub-region, a second original sub-region, and a third original sub-region. Determining the radial distance of each original sub-region of the controlled area based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set radial distance includes: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the first radial distance, the radial distance of the first original sub-region is determined; and based on the second radial distance and the correction coefficient, the radial distance of the third original sub-region is determined. The radial distance of the second original sub-region is determined based on the radial distance of the first original sub-region and the set weight coefficient; The first original sub-region is the region formed by the original boundary of the first original sub-region and the original boundary of the second original sub-region. The second original sub-region is the region formed by the original boundary of the second original sub-region and the original boundary of the third original sub-region. The third original sub-region is a closed region enclosed by the original boundary of the third original sub-region.

4. The method as described in claim 3, characterized in that, The determination of each sub-region based on the radial distance and original boundary of each original sub-region includes: Using the original boundary of the third original sub-region as a reference, the radial distance of the third original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the third original sub-region to obtain the first target boundary, and the third sub-region is determined based on the first target boundary. Using the original boundary of the second original sub-region as a reference, extend or contract the radial distance of the second original sub-region outward or inward along the normal direction of the original boundary of the second original sub-region to obtain the second target boundary, and determine the second sub-region based on the first target boundary and the second target boundary; Using the original boundary of the first original sub-region as a reference, the radial distance of the first original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the first original sub-region to obtain the third target boundary, and the first sub-region is determined based on the second target boundary and the third target boundary.

5. The method as described in claim 1, characterized in that, The method for determining the target countermeasure based on the second pedestrian density of the target sub-region and the grid region where the target drone is located includes: The second pedestrian density is compared with the second pedestrian density threshold to obtain the comparison result; Based on the target sub-region and the comparison results, the target countermeasure method is determined.

6. The method as described in claim 5, characterized in that, The method for determining the target countermeasure based on the target sub-region and the comparison result includes: If the target sub-region is a first sub-region or a second sub-region, a first control command is sent to the countermeasure terminal so that the countermeasure terminal prohibits the transmission of radio frequency countermeasure signals and forced landing signals based on the first control command, and transmits a voice drive-away signal. If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is greater than or equal to the second pedestrian density threshold, then a second control command is sent to the countermeasure terminal to make the countermeasure terminal prohibit the transmission of radio frequency countermeasure signals and forced landing signals based on the second control command, and transmit a voice drive-away signal; If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is less than the second pedestrian density threshold, then a third control command is sent to the countermeasure terminal so that the countermeasure terminal transmits a radio frequency countermeasure signal and a forced landing signal based on the third control command.

7. The method as described in claim 1, characterized in that, After determining that the target drone is an illegal drone, the process also includes: Based on the target sub-region and the established correspondence, a target alarm method is determined, and an alarm is issued using the target alarm method. The established correspondence is the correspondence between each sub-region and each alarm method.

8. The method as described in claim 7, characterized in that, The method for determining target alarms based on the target sub-region and the established correspondence includes: If the target sub-region is the first sub-region, then the first warning sound will be used to sound an alarm, the first alarm pop-up window will be displayed, and relevant personnel within the first notification range will be notified through the set communication method. If the target sub-region is the second sub-region, then a second warning sound is used to sound an alarm, a second alarm pop-up window is displayed, relevant personnel within the second notification range are notified through a set communication method, and the flight trajectory of the target drone is determined and displayed based on the historical and current location information of the target drone. If the target sub-region is the third sub-region, then a third alarm sound will be used to sound an alarm, a third alarm pop-up window will be displayed, and relevant personnel within the third notification range will be notified through the set communication method. The frequency of the first warning sound is lower than that of the second warning sound, and the frequency of the second warning sound is lower than that of the third warning sound; the colors of the first alarm pop-up, the second alarm pop-up, and the third alarm pop-up are different; the range of the first notification is smaller than that of the second notification, and the range of the second notification is smaller than that of the third notification.

9. The method as described in claim 1, characterized in that, The step of determining the sub-region where the target drone is located as the target sub-region includes: A ray is determined with the position information of the target UAV as the endpoint and a set direction is defined, wherein the set direction is the direction from the center of the third sub-region to the target UAV. Determine the number of intersections between the boundaries of each sub-region and the ray; The sub-regions that intersect the ray an odd number of times are designated as the target sub-regions.

10. A countermeasure device for unmanned aerial vehicles (UAVs), characterized in that, include: The extraction module is used to extract features from the radio frequency signal to obtain radio frequency feature information. The radio frequency signal is obtained by the detection terminal after performing a spectrum scan on the target UAV. The first determining module is used to determine that the target drone is an illegal drone if there is no set radio frequency feature information that matches the radio frequency feature information among the multiple set radio frequency feature information. The second determining module is used to determine the sub-region where the target drone is located as the target sub-region. Each sub-region is obtained by updating the original boundaries of each original sub-region of the control area based on the correction coefficient and the first population density of the control area. The correction coefficient is determined based on the first population density. The countermeasure module is used to determine the target countermeasure method based on the second population density of the target sub-region and the grid region where the target drone is located, and to countermeasure the target drone using the target countermeasure method. The control area includes multiple grid regions.

11. The apparatus as claimed in claim 10, characterized in that, Before performing feature extraction on the radio frequency signal to obtain radio frequency feature information, the extraction module is also used for: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the set radial distance, the radial distance of each original sub-region of the controlled area is determined; Each sub-region is determined based on its radial distance and its original boundary.

12. The apparatus as claimed in claim 11, characterized in that, The set radial distance includes a first radial distance and a second radial distance; the controlled area includes a first original sub-region, a second original sub-region, and a third original sub-region; the extraction module is used for: Based on the correction coefficient, the first pedestrian density threshold, the first pedestrian density, and the first radial distance, the radial distance of the first original sub-region is determined; and based on the second radial distance and the correction coefficient, the radial distance of the third original sub-region is determined. The radial distance of the second original sub-region is determined based on the radial distance of the first original sub-region and the set weight coefficient; The first original sub-region is the region formed by the original boundary of the first original sub-region and the original boundary of the second original sub-region. The second original sub-region is the region formed by the original boundary of the second original sub-region and the original boundary of the third original sub-region. The third original sub-region is a closed region enclosed by the original boundary of the third original sub-region.

13. The apparatus as claimed in claim 12, characterized in that, The extraction module is used for: Using the original boundary of the third original sub-region as a reference, the radial distance of the third original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the third original sub-region to obtain the first target boundary, and the third sub-region is determined based on the first target boundary. Using the original boundary of the second original sub-region as a reference, extend or contract the radial distance of the second original sub-region outward or inward along the normal direction of the original boundary of the second original sub-region to obtain the second target boundary, and determine the second sub-region based on the first target boundary and the second target boundary; Using the original boundary of the first original sub-region as a reference, the radial distance of the first original sub-region is extended outward or contracted inward along the normal direction of the original boundary of the first original sub-region to obtain the third target boundary, and the first sub-region is determined based on the second target boundary and the third target boundary.

14. The apparatus as claimed in claim 10, characterized in that, The countermeasure module is used for: The second pedestrian density is compared with the second pedestrian density threshold to obtain the comparison result; Based on the target sub-region and the comparison results, the target countermeasure method is determined.

15. The apparatus as claimed in claim 14, characterized in that, The countermeasure module is used for: If the target sub-region is a first sub-region or a second sub-region, a first control command is sent to the countermeasure terminal so that the countermeasure terminal prohibits the transmission of radio frequency countermeasure signals and forced landing signals based on the first control command, and transmits a voice drive-away signal. If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is greater than or equal to the second pedestrian density threshold, then a second control command is sent to the countermeasure terminal to make the countermeasure terminal prohibit the transmission of radio frequency countermeasure signals and forced landing signals based on the second control command, and transmit a voice drive-away signal; If the target sub-region is a third sub-region, and the comparison result indicates that the second pedestrian density is less than the second pedestrian density threshold, then a third control command is sent to the countermeasure terminal so that the countermeasure terminal transmits a radio frequency countermeasure signal and a forced landing signal based on the third control command.

16. The apparatus as claimed in claim 10, characterized in that, After determining that the target drone is an illegal drone, the first determining module is further configured to: Based on the target sub-region and the established correspondence, a target alarm method is determined, and an alarm is issued using the target alarm method. The established correspondence is the correspondence between each sub-region and each alarm method.

17. The apparatus as claimed in claim 16, characterized in that, The first determining module is used for: If the target sub-region is the first sub-region, then the first warning sound will be used to sound an alarm, the first alarm pop-up window will be displayed, and relevant personnel within the first notification range will be notified through the set communication method. If the target sub-region is the second sub-region, then a second warning sound is used to sound an alarm, a second alarm pop-up window is displayed, relevant personnel within the second notification range are notified through a set communication method, and the flight trajectory of the target drone is determined and displayed based on the historical and current location information of the target drone. If the target sub-region is the third sub-region, then a third alarm sound will be used to sound an alarm, a third alarm pop-up window will be displayed, and relevant personnel within the third notification range will be notified through the set communication method. The frequency of the first warning sound is lower than that of the second warning sound, and the frequency of the second warning sound is lower than that of the third warning sound; the colors of the first alarm pop-up, the second alarm pop-up, and the third alarm pop-up are different; the range of the first notification is smaller than that of the second notification, and the range of the second notification is smaller than that of the third notification.

18. The apparatus as claimed in claim 10, characterized in that, The second determining module is used for: A ray is determined with the position information of the target UAV as the endpoint and a set direction is defined, wherein the set direction is the direction from the center of the third sub-region to the target UAV. Determine the number of intersections between the boundaries of each sub-region and the ray; The sub-regions that intersect the ray an odd number of times are designated as the target sub-regions.

19. An electronic device, characterized in that, include: Memory, used to store program instructions; A processor is configured to invoke program instructions stored in the memory and execute the steps of the method according to any one of claims 1-9.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a computer, cause the computer to perform the method as described in any one of claims 1-9.

21. A computer program product, characterized in that, The computer program product includes: computer program code, which, when run on a computer, causes the computer to perform the method described in any one of claims 1-9.

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