A drone countermeasure system and method

Abstract

The application relates to an unmanned aerial vehicle countermeasure system and method, and relates to the field of unmanned aerial vehicle countermeasures. The method comprises the following steps: acquiring initial unmanned aerial vehicle information, and generating initial coordinates of the unmanned aerial vehicle based on the initial unmanned aerial vehicle information; presetting a flight range of the unmanned aerial vehicle based on the initial coordinates, and randomly generating a plurality of prediction coordinates in the flight range of the unmanned aerial vehicle; acquiring unmanned aerial vehicle information of the plurality of prediction coordinates at a second time point, and evaluating each corresponding prediction coordinate based on the unmanned aerial vehicle information of the plurality of prediction coordinates to obtain a plurality of accurate coordinates of the unmanned aerial vehicle, wherein the second time point is later than a first time point; formulating an attack strategy according to the plurality of accurate coordinates of the unmanned aerial vehicle; and sending control signals to a first transmission system, a second transmission system, a third transmission system and a high-pressure water pump based on the attack strategy, so that a remote-controlled water cannon launches water bombs to shoot down the unmanned aerial vehicle. The application improves the anti-interference of unmanned aerial vehicle positioning, thereby improving the striking accuracy of the unmanned aerial vehicle.

Description

Technical Field

[0001] This application relates to the technical field of drone countermeasures, specifically to a drone countermeasure system and method. Background Technology

[0002] With the development of technology, reconnaissance methods are emerging one after another. In particular, the current drone reconnaissance technology, due to its small size, high flexibility and large operating range, has become the preferred method in many scenarios.

[0003] In certain classified territorial areas, drones may intrude intentionally or unintentionally. For example, in military bases or specialized physics laboratories, malicious actors may attempt to steal security information, seriously threatening the lives and property of the people. Currently, the main countermeasure against such drones is to have patrolling soldiers shoot them down with single-shot bullets. However, bullets can only hit a single point, and even continuous fire cannot form an effective strike area, resulting in a low probability of a hit.

[0004] Therefore, there is an urgent need for a drone countermeasure system and method. Summary of the Invention

[0005] To address the issue of low hit rate in drone countermeasures, this application provides a drone countermeasure system and method.

[0006] In a first aspect, this application provides a drone countermeasure system, including: a patrol vehicle body, on which a high-pressure water pump, a water tank and a remote-controlled water cannon are installed;

[0007] A drone information detection device is installed on the patrol vehicle. The drone information detection device is used to detect drone information and send it to the central control module. The drone information includes image information, communication information and sound wave information.

[0008] The central control module is used to locate the coordinates of the UAV based on the UAV information and to formulate the attack strategy of the remote-controlled water cannon to shoot down the UAV. The attack strategy includes the attack direction and the attack mode, and the attack mode is either cluster attack or distributed attack.

[0009] A first transmission system is installed on the patrol vehicle body. The first transmission system is electrically connected to the central control module and is used to control the lateral striking direction of the remote-controlled water cannon according to the striking direction.

[0010] The second transmission system is installed on the patrol vehicle body and is electrically connected to the central control module. It is used to control the longitudinal striking direction of the remote-controlled water cannon according to the striking direction.

[0011] The third transmission system is installed on the muzzle end of the remote-controlled water cannon. The third transmission system is electrically connected to the central control module and is used to switch the attack mode.

[0012] Optionally, the first transmission system includes a rotating disk and a first motor. The transmission shaft of the first motor is equipped with a first gear, and a second gear is installed on one end face of the rotating disk. The first gear meshes with the second gear. A support mechanism is provided on the other end face of the rotating disk to support the remote-controlled water cannon. A through hole is provided at the center of the rotating disk for installing a water guide pipe so that water in the water tank can enter the remote-controlled water cannon.

[0013] The second rotation system includes a second motor, the drive shaft of the second motor is rotatably connected to the support mechanism, and the drive shaft of the second motor is fixedly connected to the tail end of the remote-controlled water cannon.

[0014] The third transmission system includes a third motor, a telescopic net, and a sliding guide rail. The telescopic shaft of the third motor is fixedly connected to the side wall of the telescopic net, and the telescopic net is slidably connected to the sliding guide rail. The telescopic net is set on the muzzle surface of the remote-controlled water cannon and is used to switch the attack strategy.

[0015] Secondly, this application provides a method for countering unmanned aerial vehicles (UAVs), the method being applied to the central control module mentioned in the first aspect, the method comprising:

[0016] Once the drone enters the strike range, initial drone information is acquired, and based on this initial drone information, initial coordinates of the drone are generated. The initial coordinates store the drone's image information, communication information, sound wave information, speed, and acceleration at the first point in time.

[0017] Based on the initial coordinates, the flight range of the UAV is preset, and multiple predicted coordinates are generated within the flight range of the UAV.

[0018] At a second time point, UAV information at multiple predicted coordinates is acquired, and based on the UAV information at multiple predicted coordinates, the accuracy of the multiple predicted coordinates is evaluated to obtain multiple accurate coordinates of the UAV. The second time point is later than the first time point.

[0019] An attack strategy is formulated based on multiple precise coordinates of the drone;

[0020] Based on the attack strategy, control signals are sent to the first transmission system, the second transmission system, the third transmission system, and the high-pressure water pump to enable the remote-controlled water cannon to fire water bullets to shoot down the drone.

[0021] Optionally, the evaluation of each corresponding predicted coordinate based on the UAV information of multiple predicted coordinates to obtain multiple precise coordinates of the UAV specifically includes:

[0022] The UAV information for the predicted coordinates to be evaluated is divided into multiple sub-information, including image information, communication information, acoustic information, velocity, and acceleration. The predicted coordinates to be evaluated are any one of the multiple predicted coordinates.

[0023] Obtain the preset weight values ​​of the predicted coordinates to be evaluated;

[0024] The information quality of the multiple sub-informations is compared with the initial UAV information to obtain the degree of difference of the multiple sub-informations;

[0025] Based on the degree of difference among multiple sub-information, the preset weight value is corrected to obtain the true weight value of the predicted coordinate to be evaluated.

[0026] If the true weight value of the predicted coordinates to be evaluated is greater than the threshold, then the predicted coordinates to be evaluated are determined to be accurate coordinates.

[0027] Optionally, before obtaining the preset weight values ​​of the predicted coordinates to be evaluated, the method further includes:

[0028] Based on the initial drone information or the drone information with the predicted coordinates to be evaluated, determine the identity information of the drone;

[0029] If a judgment result exists, then based on the identity information of the drone, the preset weight value of the predicted coordinates to be evaluated is obtained from the preset drone countermeasure weight library.

[0030] Optionally, the method for correcting the preset weight value based on the difference between multiple sub-information items to obtain the true weight value of the predicted coordinate to be evaluated is as follows:

[0031]

[0032] Where w is the actual weight value, For preset weight values, Let i be the difference degree of the i-th sub-information. Let i be the weight adjustment factor for the i-th sub-information. is the nonlinear adjustment coefficient for the i-th sub-information.

[0033] Optionally, the strike range of the UAV can be determined based on multiple precise coordinates;

[0034] Determine whether the drone's strike distance is less than or equal to a preset distance;

[0035] If the distance is less than or equal to the preset distance, the strike range and strike angle of the distributed strike are determined based on the multiple precise coordinates.

[0036] Optionally, determining whether the strike distance of the drone is less than or equal to a preset distance further includes:

[0037] If the distance is greater than the preset distance, then the spherical area of ​​the drone's activity is determined based on multiple precise coordinates;

[0038] Calculate the relative distances between the multiple precise coordinates and the center coordinates of the spherical region;

[0039] Based on the relative distances corresponding to each of the multiple precise coordinates, the multiple precise coordinates are sorted by attack priority;

[0040] Based on the strike priority of multiple precise coordinates, the order and angle of cluster strikes are determined.

[0041] Thirdly, this application also provides a drone countermeasure device, which is a central control module. The central control module includes a receiving module, a processing module, and an output module, wherein:

[0042] The receiving module is used to acquire initial drone information after the drone enters the strike range, and generate the initial coordinates of the drone based on the initial drone information. The initial coordinates store the drone's image information, communication information, sound wave information, speed and acceleration at the first time point.

[0043] The processing module is configured to: preset the flight range of the UAV based on the initial coordinates; generate multiple predicted coordinates within the flight range of the UAV; at a second time point, acquire UAV information at the multiple predicted coordinates; and, based on the UAV information at the multiple predicted coordinates, evaluate the accuracy of the multiple predicted coordinates to obtain multiple accurate coordinates of the UAV, wherein the second time point is later than the first time point; and formulate an attack strategy based on the multiple accurate coordinates of the UAV.

[0044] The output module is used to send control signals to the first transmission system, the second transmission system, the third transmission system, and the high-pressure water pump based on the attack strategy, so as to enable the remote-controlled water cannon to fire water bullets to shoot down the drone.

[0045] Fourthly, this application provides an electronic device including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of the second aspects.

[0046] Fifthly, this application provides a computer-readable storage medium storing instructions that, when executed, perform the method described in any one of the second aspects.

[0047] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0048] 1. When a drone enters the strike range, the drone information detection device locates and verifies its position by detecting various types of drone information, thereby improving the drone's positioning accuracy. Then, the central control module formulates a strike strategy based on the drone's coordinates. At this time, the strike strategy is executed by the remote-controlled water cannon. The strike strategy includes the strike direction and attack mode. The attack mode is divided into cluster strike and distributed strike. The strike direction is controlled by the first and second transmission systems, and the switching of the attack mode is controlled by the third transmission system. Cluster strike is suitable for long-range precision strikes, while distributed strike is suitable for short-range strikes, thus forming an effective strike surface and improving the success rate of drone strikes.

[0049] 2. Due to the complex and ever-changing real-world environment, drone information detection devices are easily affected by various external environmental interferences when detecting drone information, resulting in inaccurate drone information acquisition. Therefore, when a drone enters the strike range, initial drone information is acquired, and initial drone coordinates are generated based on this information. Since these initial coordinates are inaccurate, multiple predicted coordinates within a certain range are generated based on the initial drone coordinates. Drone information is then acquired at these multiple predicted coordinates. Finally, based on the signal quality of the drone information at these multiple predicted coordinates, the precise drone coordinates are determined. This process achieves drone positioning without requiring precise measurement of drone information, exhibits high adaptability in complex environments, has low computational resource requirements, and can quickly respond to various environmental changes, thereby improving the accuracy and timeliness of subsequent drone strikes.

[0050] 3. The movement patterns of drones are irregular, and drones may also be equipped with countermeasures devices. Therefore, when determining the precise coordinates of a drone, it is necessary to introduce a nonlinear adjustment factor and a weighted adjustment factor. The nonlinear adjustment factor is used to adjust the precise coordinates when the drone's movement patterns change. The weighted adjustment factor is used to adjust the precise coordinates when the drone is equipped with countermeasures devices. Through the adaptive changes of the nonlinear adjustment factor and the weighted adjustment factor, the positioning accuracy of drones equipped with countermeasures devices can be improved. Attached Figure Description

[0051] Figure 1This is a schematic diagram of the structure of a drone countermeasure system provided in an embodiment of this application.

[0052] Figure 2 This is a cross-sectional view of the overall structure of a drone reversing system provided in an embodiment of this application.

[0053] Figure 3 yes Figure 2 Enlarged diagram of point A in the middle.

[0054] Figure 4 yes Figure 1 Enlarged diagram of point B in the middle.

[0055] Figure 5 This is a flowchart illustrating a method for countering unmanned aerial vehicles (UAVs) provided in an embodiment of this application.

[0056] Figure 6 This is a schematic diagram of the structure of a drone countermeasure device provided in an embodiment of this application.

[0057] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0058] Explanation of reference numerals in the attached drawings: 1. Patrol vehicle body; 2. High-pressure water pump; 3. Remote-controlled water cannon; 4. Water tank; 5. Central control module; 6. UAV information detection device; 7. First transmission system; 71. First motor; 72. First gear; 73. Second gear; 74. Rotating disk; 8. Second motor; 9. Third transmission system; 91. Third motor; 92. Telescopic net; 93. Sliding guide rail; 10. Support mechanism; 11. Water pipe; 601. Receiving module; 602. Processing module; 603. Output module; 700. Electronic equipment; 701. Processor; 702. Communication bus; 703. User interface; 704. Network interface; 705. Memory. Detailed Implementation

[0059] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0060] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0061] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0062] With the development of technology, most of the current reconnaissance methods tend to be unmanned and intelligent.

[0063] Countermeasures against drone reconnaissance mainly involve soldiers using bullets to shoot down drones or using electromagnetic interference to affect their trajectory. However, bullets can only attack one point, and even continuous fire cannot form an effective strike area, resulting in a low probability of hitting the target. While electromagnetic interference can form a larger strike area, most drones are currently equipped with anti-electromagnetic devices, resulting in poor interference effects and thus failing to effectively strike drones.

[0064] To address the aforementioned problems, this application provides a drone countermeasure system, such as... Figure 1 As shown, the countermeasure system includes a patrol vehicle 1, on which a high-pressure water pump 2, a water tank 4, and a remote-controlled water cannon 3 are installed. The high-pressure water pump 2 draws water from the water tank 4 to serve as ammunition for the remote-controlled water cannon 3. Multiple remote-controlled water cannons 3 can be deployed to engage multiple drone targets. Before engaging the drones, their location needs to be determined. Therefore, the patrol vehicle 1 is also equipped with a drone information detection device 6 and a central control module 5. The drone information detection device 6 includes various types of detection sensors, including but not limited to optical sensors, electromagnetic sensors, and acoustic sensors. The drone information detection device 6 detects drone information, including image information, communication information, and acoustic information. This information is then sent to the central control module 5 for processing, obtaining the drone's location coordinates and the attack strategy of the remote-controlled water cannon 3. The attack strategy includes the attack direction and attack mode. The attack modes include cluster attacks and distributed attacks. Cluster attacks are suitable for long-range attacks, while distributed attacks are suitable for short-range attacks. Because the water jet is continuous, drones can switch between two attack methods to create a continuous and effective attack surface along their flight path, as well as to achieve precise strikes, thus greatly improving the success rate of drone attacks.

[0065] To avoid blind spots in the remote-controlled water cannon 3, refer to Figure 1 , Figure 2 Combination Figure 3 The direction of attack is controlled by a first transmission system 7 and a second transmission system, both of which are mounted on the patrol vehicle body 1. Both the first and second transmission systems are electrically connected to the central control module 5. Once the central control module 5 determines the direction of attack, it sends control commands to the first and second transmission systems. Specifically, the first transmission system 7 controls the lateral direction of attack of the remote-controlled water cannon 3, and the second transmission system controls the longitudinal direction of attack of the remote-controlled water cannon 3. The first transmission system 7 includes a rotating disk 74 and a first motor 71. A first gear 72 is mounted on the drive shaft of the first motor 71, and a second gear 73 is mounted on one end face of the rotating disk 74. The first gear 72 and the second gear 73 mesh. When the first motor 71 is started, the first gear 72 drives the second gear 73 to rotate, which in turn drives the rotating disk 74 to rotate. A support mechanism 10 is provided on the other end face of the disk to support the remote-controlled water cannon 3. When the disk rotates, the remote-controlled water cannon 3 rotates accordingly, thus achieving lateral impact. Additionally, a through hole is provided at the center of the rotating disk 74 for installing a water guide pipe 11, allowing water from the water tank 4 to enter the remote-controlled water cannon 3 as projectiles. The second transmission system includes a second motor 8, whose drive shaft is rotatably connected to the support mechanism 10. Furthermore, the drive shaft of the second motor 8 is also fixedly connected to the tail end of the remote-controlled water cannon 3. When the second motor 8 is started, its drive shaft drives the remote-controlled water cannon 3 to rotate, thus achieving longitudinal impact.

[0066] Reference Figure 1 , Figure 4 The third transmission system 9 includes a third motor 91, a telescopic net 92, and a sliding guide rail 93. The third transmission system 9 is located at the muzzle. The telescopic rod of the third motor 91 is fixedly connected to the side wall of the telescopic net 92. The telescopic net 92 is slidably connected to the sliding guide rail 93 installed on the muzzle end face. When the third motor 91 is activated, the telescopic rod drives the telescopic net 92 to block the muzzle for distributed strikes; when the telescopic net 92 does not block the muzzle, cluster strikes are achieved, thus facilitating the switching of attack modes. Furthermore, by controlling the power of the high-pressure water pump 2, the range of distributed strikes and the attack distance of cluster strikes can be controlled.

[0067] The aforementioned patrol vehicle drone countermeasure system utilizes the adjustable shape and continuity of the water jet from the remote-controlled water cannon 3 to achieve both long-range precision strikes and short-range distributed strikes, thereby improving the success rate of drone strikes.

[0068] When patrol vehicles are targeting drones, accurate drone location is crucial. However, the actual environment is complex and ever-changing, with various forms of interference present. The drone information detection device 6 struggles to accurately measure drone information, significantly reducing the success rate of drone strikes.

[0069] To address the aforementioned problems, this application provides a method for countering unmanned aerial vehicles (UAVs), such as... Figure 4 As shown, this method is applied to the central control module 5 of the above-mentioned patrol vehicle-UAV countermeasure system, including steps S101 to S105, as follows:

[0070] S101. When the drone enters the strike range, the initial drone information is acquired, and based on the initial drone information, the initial coordinates of the drone are generated. The initial coordinates store the drone's image information, communication information, sound wave information, speed and acceleration at the first time point.

[0071] In the above steps, the strike range refers to the detection range of the UAV information detection device 6. When the patrol vehicle is traveling within the confidential area, the UAV information detection device 6 is always on, thus enabling it to detect UAVs immediately. When a UAV enters the strike range, initial UAV information is acquired. This initial UAV information includes, but is not limited to, image information, communication information, acoustic information, speed, and acceleration. It should be further noted that if UAV information is detected immediately when it first enters the strike range, it is prone to misjudgment. For example, the electromagnetic signals emitted by the UAV may have some similarity to electromagnetic pulses in the environment, but the electromagnetic pulses fed back by the environment will not remain stable indefinitely, while the electromagnetic pulses fed back by the UAV may not be stable indefinitely. Since the magnetic signal is always in a stable state, the first time point is set to the time point after a preset time period has elapsed after the drone enters the strike range. If drone information can be detected continuously within the preset time period, drone information will be acquired for subsequent processing. It is understandable that the drone information acquired initially is inaccurate due to environmental interference, but it can lock the approximate coordinates of the drone. Therefore, the initial coordinates of the drone can be generated based on the initial drone information. Specifically, different information coordinates are generated according to different information types. For example, image information can obtain image coordinates, communication information can obtain communication coordinates, and sound wave information can obtain sound coordinates. Then, the average of multiple different information coordinates is calculated to obtain an initial coordinate.

[0072] S102. Based on the initial coordinates, preset the flight range of the UAV and generate multiple predicted coordinates within the flight range of the UAV.

[0073] In the above steps, the drone's flight range is determined by the speed and acceleration in the initial drone information. Specifically, starting from the drone's initial coordinates, multiple possible destinations of the drone after a preset time period are predicted. Then, based on the extreme relative distances between these multiple possible destinations and the initial coordinates, the drone's flight range is generated. The predicted coordinates can be understood as multiple coordinate points generated within the flight area that the drone is likely to traverse during its engagement with the patrol vehicle, such as the straight-line area between the drone and the patrol vehicle. These predicted coordinate points store multiple different initial information coordinates from the initial coordinate points.

[0074] S103. At the second time point, obtain UAV information at multiple predicted coordinates, and based on the UAV information at the multiple predicted coordinates, perform an accuracy evaluation on the multiple predicted coordinates to obtain multiple accurate coordinates of the UAV. The second time point is later than the first time point.

[0075] In the above steps, the second time point is the time point after a preset time interval from the first time point. At the second time point, UAV information at multiple predicted coordinates is acquired again. This UAV information contains various types of information, but the acquired information may be inaccurate due to the influence of the actual environment. The UAV coordinates generated from this information may also be inaccurate, making it impossible to directly determine the accurate UAV position using the coordinates generated from the UAV information, nor can it be used to verify the predicted coordinates indirectly obtained from the initial information coordinates. Therefore, this application uses a method of correcting the coordinate weight values ​​at the predicted coordinates to locate the accurate position of the UAV. The coordinate weight value can be understood as the accuracy of the UAV's position at the predicted coordinates. During the correction process, the difference between the signal quality of the UAV information at the predicted coordinates and the signal quality of the UAV information at the initial coordinates is used to determine the specific position of the UAV. A smaller difference increases the weight value of the predicted coordinates, while a larger difference decreases the weight value. When the weight value is sufficiently high, the accurate coordinates of the UAV can be determined. This scheme achieves accurate UAV positioning without detecting accurate UAV information and also reduces data processing difficulty by eliminating complex post-processing steps, thus providing a faster response speed. The specific method is as follows:

[0076] After obtaining the UAV information for the predicted coordinates to be evaluated, this information is divided into multiple sub-information. The predicted coordinates to be evaluated are arbitrarily selected from these multiple predicted coordinates for ease of explanation; it is understood that the same operation is performed on the other predicted coordinates. The multiple sub-information includes image information, communication information, acoustic information, velocity, and acceleration at the predicted coordinates to be evaluated at the second time point.

[0077] Then, the preset weight value of the predicted coordinate to be evaluated is obtained. The preset weight value can be understood as the weight value of the initial coordinate. The weight value of the initial coordinate is determined by the information quality of various information types obtained at the first time point. It should be noted that the weight value of the initial coordinate is initially a default value. Then, the initial default value is corrected one by one according to the information quality of each of the various information types. When the information quality of an information type is high, the initial default value is increased, and when the information quality of an information type is low, the initial default value is decreased.

[0078] In one possible implementation, different drone models differ in their operational methods and countermeasures. Therefore, knowing the drone's identity information in advance provides a more accurate basis for predicting its flight patterns, resulting in more precise predictions of the drone's coordinates. Based on this, before obtaining the preset weights for the predicted coordinates to be evaluated, an attempt is made to determine whether the drone's identity information can be identified based on the initial drone information or the drone information of the predicted coordinates. If the drone's identity information cannot be identified, the first default weight value of the predicted coordinates to be evaluated is corrected based on the initial drone information to obtain the preset weight value of the predicted coordinates. The first default weight value is the initial default value of the weight value of the initial coordinates. If the drone's identity information can be identified, the second default weight value of the predicted coordinates to be evaluated can be obtained by matching the drone information from the preset drone countermeasure weight library. The second default weight value reflects the impact of the drone's countermeasures. The difficulty of acquiring human-machine information is significant. For example, if the drone's identity information is known, it can be deduced that the drone possesses countermeasures against electromagnetic signals. Therefore, even if the communication information acquired from the drone is of high quality, it may be judged as interference, thus lowering the default weight value of the predicted coordinates to be evaluated. In other words, the second default weight value is less than the first default weight value. It should be noted that the purpose of setting a preset drone countermeasure weight library is because the strength of drone countermeasures varies, and the impact of this strength on the default weight value needs to be determined through extensive experimentation. Therefore, the preset drone countermeasure weight library stores the relationship between experimentally verified drone models and the second default weight value. Finally, based on the initial drone information, the second default weight value of the predicted coordinates to be evaluated is corrected to obtain the preset weight value of the predicted coordinates, thereby making the prediction of drone coordinates more accurate.

[0079] After obtaining the preset weight values ​​for the predicted coordinates to be evaluated, the information quality of multiple sub-information at the second time point is compared with the information quality of multiple UAV information at the first time point to obtain the degree of difference among the multiple sub-information. Then, based on the degree of difference among the multiple sub-information, the preset weight values ​​are corrected to obtain the true weight values ​​for the predicted coordinates to be evaluated. The correction method can use the following formula:

[0080]

[0081] Where w is the actual weight value, For preset weight values, Let i be the difference degree of the i-th sub-information. Let i be the weight adjustment factor for the i-th sub-information. is the nonlinear adjustment coefficient for the i-th sub-information.

[0082] In the above formula,

[0083]

[0084] This indicates the degree of influence of the difference in sub-information on the preset weight value. However, this influence is not constant and is affected by the actual environment, drone countermeasures, and the detection equipment itself. Therefore, a nonlinear adjustment coefficient and a weight adjustment factor need to be introduced to amplify or reduce this influence, thereby making the final true weight value more accurate. Further explanation follows:

[0085] For weight adjustment factor It is evident that the environment has a significant impact on the accuracy and reliability of detection equipment. For example, optical sensors can provide highly accurate image information in favorable environments, but their reliability may rapidly decline in harsh environments. Therefore, the weight adjustment factor needs to be adjusted based on this difference, either highlighting or weakening the influence of the UAV information acquired by a particular detection device. If a detection device is more accurate in the current environment, a smaller weight adjustment factor can be set to increase the actual weight value; conversely, if a detection device performs poorly in the current environment, a larger weight adjustment factor can be set to decrease the actual weight value.

[0086] For nonlinear adjustment coefficient In real-world environments, the impact of various factors on the UAV information acquired by detection equipment is typically non-linear. For example, weather conditions affect optical sensors; when fog concentration is low, the impact on image information may be small, but when the fog concentration reaches a certain threshold, the image quality deteriorates sharply. Based on this, a non-linear adjustment coefficient can effectively characterize this non-linear relationship. By setting the non-linear adjustment coefficient, the degree of influence of the environment on the difference in sub-information can be adjusted according to the extent of environmental change. For instance, when environmental factors increase the difference in sub-information, increasing the non-linear adjustment coefficient can reduce the true weight value, thereby weakening this impact and concentrating the true weight value more on precise sub-information.

[0087] In summary, by using nonlinear adjustment coefficients and weight adjustment factors, the weights corresponding to each piece of information can be adjusted and allocated more accurately. Accurate weight allocation makes it more reliable to determine the precise location of the UAV, thereby improving the success rate of UAV countermeasures.

[0088] After obtaining the true weight value of the predicted coordinates of the UAV, it is then determined whether the true weight value of the predicted coordinates is greater than a threshold. If it is greater than the threshold, the predicted coordinates can be determined to be accurate coordinates. It should be noted that there may be more than one predicted coordinate with a true weight value greater than the threshold, that is, there are multiple accurate coordinates. However, these accurate coordinates are relatively concentrated, while the water cannon has a certain coverage area during the strike. This coverage area can cover multiple accurate coordinates, thus still enabling effective strikes.

[0089] S104. Develop an attack strategy based on multiple precise coordinates of the drone.

[0090] In the above steps, the attack strategy includes the direction of attack and the attack mode. The attack mode includes distributed attack and cluster attack. Distributed attack can be understood as the water bullets fired by the remote-controlled water cannon 3 forming a water network. The water network has a large attack area, but the attack force is smaller at long distances, making it suitable for close-range attacks. Cluster attack can be understood as the water bullets fired by the remote-controlled water cannon 3 being launched in the form of water jets, thus having a stronger attack force, but the attack area is smaller at long distances, making it suitable for long-range attacks. Based on this, after determining multiple precise coordinates of the drone, the attack distance and attack angle between the patrol vehicle and the drone are calculated. Then, it is determined whether the attack distance is less than or equal to a preset distance. If it is less than the preset distance, it means that the drone is too close to the patrol vehicle. In this case, distributed attack with a large attack range can be used to ensure the success rate of the attack.

[0091] If the strike distance is greater than the preset distance, this is suitable for long-range cluster strikes. However, since the strike area of ​​a cluster strike is small and there are multiple precise coordinates, random strikes may miss the location where the drone is most likely to be, resulting in multiple strikes to hit the target or even no hit at all. To solve this problem, firstly, a spherical area of ​​drone activity is determined based on multiple precise coordinates. This spherical area contains multiple precise coordinates. Then, the relative distances between these precise coordinates and the center coordinates of the spherical area are calculated. Finally, based on the relative distances of each precise coordinate, the strike priority is ranked, allowing the remote-controlled water cannon 3 to perform cluster strikes from high to low priority. This scheme utilizes a probability distribution map within the spherical area to predict that the probability of a drone appearing at the center of the sphere is the highest, and the closer to the center, the higher the probability of the drone appearing. Based on this characteristic, ranking the strike priority of multiple precise coordinates ensures that each strike covers the area where the drone is most likely to appear as much as possible. Furthermore, since the cluster strike of the remote-controlled water cannon 3 is a continuous strike method, adjusting the strike angle can create a larger strike area, thereby improving the success rate.

[0092] S105. Based on the attack strategy, control signals are sent to the first transmission system 7, the second transmission system, the third transmission system 9, and the high-pressure water pump 2 to enable the remote-controlled water cannon 3 to fire water bullets to shoot down the drone.

[0093] In the above steps, based on the attack angle and attack method included in the attack strategy, the first transmission system 7 is controlled to adjust the lateral attack angle, the second transmission system is controlled to adjust the longitudinal attack angle, the third transmission system 9 is controlled to switch the attack mode, and the water supply pressure of the high-pressure water pump 2 is controlled to adapt to the attack force requirements of different attack modes. Finally, the remote-controlled water cannon 3 shoots down the drone according to the attack strategy. Compared with bullets hitting drones, this scheme can form an effective attack surface, thereby improving the success rate of drone attacks.

[0094] Reference Figure 6 This application also provides a drone countermeasure device, which is the central control module 5 in a patrol vehicle drone countermeasure system. The central control module 5 includes a receiving module 601, a processing module 602, and an output module 603503.

[0095] The receiving module 601 is used to acquire initial drone information after the drone enters the strike range, and generate the initial coordinates of the drone based on the initial drone information. The initial coordinates store the drone's image information, communication information, sound wave information, speed and acceleration at the first time point.

[0096] The processing module 602 is used to preset the flight range of the UAV based on the initial coordinates and generate multiple predicted coordinates within the flight range of the UAV; at a second time point, it acquires UAV information at the multiple predicted coordinates and evaluates the accuracy of the multiple predicted coordinates based on the UAV information at the multiple predicted coordinates to obtain multiple accurate coordinates of the UAV. The second time point is later than the first time point; and it formulates an attack strategy based on the multiple accurate coordinates of the UAV.

[0097] Output module 603 is used to send control signals to the first transmission system 7, the second transmission system, the third transmission system 9, and the high-pressure water pump 2 based on the attack strategy, so that the remote-controlled water cannon 3 can fire water bullets to shoot down the drone.

[0098] In one possible implementation, the UAV information based on multiple predicted coordinates is used to evaluate the corresponding predicted coordinates to obtain multiple accurate coordinates of the UAV. Specifically, this includes: dividing the UAV information of the predicted coordinates to be evaluated into multiple sub-information, including image information, communication information, acoustic information, velocity, and acceleration, with the predicted coordinates to be evaluated being any one of the multiple predicted coordinates; obtaining a preset weight value for the predicted coordinates to be evaluated; comparing the information quality of the multiple sub-information with the initial UAV information to obtain the degree of difference of the multiple sub-information; correcting the preset weight value based on the degree of difference of the multiple sub-information to obtain the true weight value of the predicted coordinates to be evaluated; and determining the predicted coordinates to be evaluated as accurate coordinates if the true weight value of the predicted coordinates to be evaluated is greater than a threshold.

[0099] In one possible implementation, before obtaining the preset weight value of the predicted coordinates to be evaluated, the method further includes: determining the identity information of the drone based on the initial drone information or the drone information of the predicted coordinates to be evaluated; if there is a determination result, then matching the preset weight value of the predicted coordinates to be evaluated from the preset drone countermeasure weight library based on the drone's identity information.

[0100] In one possible implementation, the preset weight value is corrected based on the difference between multiple sub-information values ​​to obtain the true weight value of the predicted coordinates to be evaluated. The specific method is as follows:

[0101]

[0102] Where w is the actual weight value, For preset weight values, Let i be the difference degree of the i-th sub-information. Let i be the weight adjustment factor for the i-th sub-information. is the nonlinear adjustment coefficient for the i-th sub-information.

[0103] In one possible implementation, the strike distance of the UAV is determined based on multiple precise coordinates; it is then determined whether the strike distance of the UAV is less than or equal to a preset distance; if it is less than or equal to the preset distance, the strike range and strike angle of the distributed strike are determined based on the multiple precise coordinates.

[0104] In one possible implementation, determining whether the strike distance of the UAV is less than or equal to a preset distance further includes: if it is greater than the preset distance, determining the spherical area of ​​the UAV's activity based on multiple precise coordinates; calculating the relative distance between the multiple precise coordinates and the center coordinates of the spherical area; ranking the multiple precise coordinates according to their respective relative distances; and determining the order of cluster strikes and the strike angle based on the strike priority of the multiple precise coordinates.

[0105] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0106] This application also discloses an electronic device 700. (See reference...) Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic device 700 disclosed in an embodiment of this application. The electronic device 700 may include: at least one processor 701, at least one network interface 704, a user interface 703, a memory 705, and at least one communication bus 702.

[0107] The communication bus 702 is used to enable communication between these components.

[0108] The user interface 703 may include a display screen and a camera. Optionally, the user interface 703 may also include a standard wired interface and a wireless interface.

[0109] The network interface 704 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0110] The processor 701 may include one or more processing cores. The processor 701 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 705, and by calling data stored in memory 705. Optionally, the processor 701 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 701 may integrate one or more of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor 701.

[0111] The memory 705 may include random access memory (RAM) or read-only memory. Optionally, the memory 705 may include a non-transitory computer-readable storage medium. The memory 705 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 705 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch functionality, sound playback functionality, image playback functionality, etc.), instructions for implementing the various method embodiments described above, etc.; the data storage area may store data involved in the various method embodiments described above, etc. Optionally, the memory 705 may also be at least one storage device located remotely from the aforementioned processor 701. (Refer to...) Figure 7 The memory 705, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface 703 module, and an application program for a method of countering unmanned aerial vehicles.

[0112] exist Figure 7In the illustrated electronic device 700, the user interface 703 is mainly used to provide an input interface for the user and acquire user input data; while the processor 701 can be used to call an application program stored in the memory 705 for a drone countermeasure method. When executed by one or more processors 701, the electronic device 700 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0113] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0114] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0115] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0116] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0117] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device 705. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage device 705 and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage device 705 includes various media capable of storing program code, such as a USB flash drive, external hard drive, magnetic disk, or optical disk.

[0118] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0119] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A drone countermeasure system, characterized in that, include: The patrol vehicle body (1) is equipped with a high-pressure water pump (2), a water tank (4) and a remote-controlled water cannon (3). The drone information detection device (6) is installed on the patrol vehicle body (1). The drone information detection device (6) is used to detect drone information and send it to the central control module (5). The drone information includes image information, communication information and sound wave information. The central control module (5) is used to locate the coordinates of the UAV based on the UAV information and to formulate the attack strategy of the remote-controlled water cannon (3) to shoot down the UAV. The attack strategy includes the attack direction and the attack mode. The attack mode is either cluster attack or distributed attack. The first transmission system (7) is installed on the patrol vehicle body (1). The first transmission system (7) is electrically connected to the central control module (5) and is used to control the lateral striking direction of the remote-controlled water cannon (3) according to the striking direction. The second transmission system is installed on the patrol vehicle body (1). The second transmission system is electrically connected to the central control module (5) and is used to control the longitudinal striking direction of the remote-controlled water cannon (3) according to the striking direction. The third transmission system (9) is installed on the muzzle end of the remote-controlled water cannon (3). The third transmission system (9) is electrically connected to the central control module (5) and is used to switch the attack mode. The third transmission system (9) includes a third motor (91), a telescopic net (92) and a sliding guide rail (93). The telescopic shaft of the third motor (91) is fixedly connected to the side wall of the telescopic net (92). The telescopic net (92) is slidably connected in the sliding guide rail (93). The telescopic net (92) is set on the muzzle surface of the remote-controlled water cannon (3) and is used to switch the attack mode.

2. The countermeasure system according to claim 1, characterized in that, The first transmission system (7) includes a rotating disk (74) and a first motor (71). The transmission shaft of the first motor (71) is equipped with a first gear (72). A second gear (73) is installed on one end face of the rotating disk (74). The first gear (72) meshes with the second gear (73). A support mechanism (10) is provided on the other end face of the rotating disk (74) for supporting the remote-controlled water cannon (3). A through hole is provided at the center of the rotating disk (74). The through hole is used to install a water guide pipe (11) so that water in the water tank (4) can enter the remote-controlled water cannon (3). The second transmission system includes a second motor (8), the transmission shaft of the second motor (8) is rotatably connected to the support mechanism (10), and the transmission shaft of the second motor (8) is fixedly connected to the tail end of the remote-controlled water cannon (3).

3. A method for countering unmanned aerial vehicles (UAVs), characterized in that, Based on the central control module (5) of the UAV countermeasure system according to claim 1, the method includes: Once the drone enters the strike range, initial drone information is acquired, and based on this initial drone information, initial coordinates of the drone are generated. The initial coordinates store the drone's image information, communication information, sound wave information, speed, and acceleration at the first point in time. Based on the initial coordinates, the flight range of the UAV is preset, and multiple predicted coordinates are generated within the flight range of the UAV. At a second time point, UAV information at multiple predicted coordinates is acquired, and based on the UAV information at multiple predicted coordinates, the accuracy of the multiple predicted coordinates is evaluated to obtain multiple accurate coordinates of the UAV. The second time point is later than the first time point. An attack strategy is formulated based on multiple precise coordinates of the drone; Based on the attack strategy, control signals are sent to the first transmission system (7), the second transmission system, the third transmission system (9) and the high-pressure water pump (2) to enable the remote-controlled water cannon (3) to fire water bullets to shoot down the drone.

4. The method according to claim 3, characterized in that, The step of evaluating the accuracy of multiple predicted coordinates based on UAV information at multiple predicted coordinates to obtain multiple accurate coordinates of the UAV specifically includes: The UAV information for the predicted coordinates to be evaluated is divided into multiple sub-information, including image information, communication information, acoustic information, velocity, and acceleration. The predicted coordinates to be evaluated are any one of the multiple predicted coordinates. Obtain the preset weight values ​​of the predicted coordinates to be evaluated; The information quality of the multiple sub-informations is compared with the initial UAV information to obtain the degree of difference of the multiple sub-informations; Based on the degree of difference among multiple sub-information, the preset weight value is corrected to obtain the true weight value of the predicted coordinate to be evaluated. If the true weight value of the predicted coordinates to be evaluated is greater than the threshold, then the predicted coordinates to be evaluated are determined to be accurate coordinates.

5. The method according to claim 4, characterized in that, Before obtaining the preset weight values ​​of the predicted coordinates to be evaluated, the method further includes: Based on the initial drone information or the drone information with the predicted coordinates to be evaluated, determine the identity information of the drone; If no judgment result exists, the first default weight value of the predicted coordinates to be evaluated is corrected based on the initial UAV information to obtain the preset weight value of the predicted coordinates to be evaluated. If a judgment result exists, then based on the identity information of the drone, a second default weight value for the predicted coordinates to be evaluated is obtained from the preset drone countermeasure weight library. The second default weight value of the predicted coordinates to be evaluated is corrected based on the initial UAV information to obtain the preset weight value of the predicted coordinates to be evaluated.

6. The method according to claim 4, characterized in that, The step of correcting the preset weight value based on the difference between multiple sub-information items to obtain the true weight value of the predicted coordinate to be evaluated is as follows: ； Where w is the actual weight value, For preset weight values, Let i be the difference degree of the i-th sub-information. Let i be the weight adjustment factor for the i-th sub-information. is the nonlinear adjustment coefficient for the i-th sub-information.

7. The method according to claim 3, characterized in that, The step of formulating an attack strategy based on multiple precise coordinates of the drone specifically includes: The strike range of the UAV is determined based on multiple precise coordinates. Determine whether the drone's strike distance is less than or equal to a preset distance; If the distance is less than or equal to the preset distance, the strike range and strike angle of the distributed strike are determined based on the multiple precise coordinates.

8. The method according to claim 7, characterized in that, The step of determining whether the strike distance of the drone is less than or equal to a preset distance further includes: If the distance is greater than the preset distance, then the spherical area of ​​the drone's activity is determined based on multiple precise coordinates; Calculate the relative distances between the multiple precise coordinates and the center coordinates of the spherical region; Based on the relative distances corresponding to each of the multiple precise coordinates, the multiple precise coordinates are sorted by attack priority; Based on the strike priority of multiple precise coordinates, the order and angle of cluster strikes are determined.

9. A countermeasure device for unmanned aerial vehicles (UAVs), characterized in that, Based on the central control module (5) of the UAV countermeasure method according to claim 3, the central control module (5) includes a receiving module (601), a processing module (602), and an output module (603), wherein: The receiving module (601) is used to acquire initial drone information after the drone enters the strike range, and generate the initial coordinates of the drone based on the initial drone information. The initial coordinates store the drone's image information, communication information, sound wave information, speed and acceleration at the first time point. The processing module (602) is used to preset the flight range of the UAV based on the initial coordinates, and generate multiple predicted coordinates within the flight range of the UAV; at a second time point, acquire UAV information at the multiple predicted coordinates, and perform an accuracy evaluation on the multiple predicted coordinates based on the UAV information at the multiple predicted coordinates to obtain multiple accurate coordinates of the UAV, wherein the second time point is later than the first time point; and formulate an attack strategy based on the multiple accurate coordinates of the UAV. The output module (603) is used to send control signals to the first transmission system (7), the second transmission system, the third transmission system (9) and the high-pressure water pump (2) based on the attack strategy, so that the remote-controlled water cannon (3) can fire water bullets to shoot down the drone.

10. An electronic device (700), characterized in that, The device includes a processor (701), a memory (705), a user interface (703), and a network interface (704), wherein the memory (705) is used to store instructions, the user interface (703) and the network interface (704) are used to communicate with other devices, and the processor (701) is used to execute the instructions stored in the memory (705) to cause the electronic device (700) to perform the method as described in any one of claims 3 to 8.

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