An intelligent UAV interception system based on image communication

Abstract

The present invention discloses an intelligent interception system for unmanned aerial vehicles based on image communication, belonging to the field of intelligent control technology. It includes: a target UAV recognition module, which is used to obtain the original image data of the target UAV through a monitoring device, perform threat recognition on the original image data, copy the original image data when a threat is confirmed, and perform UAV image recognition and contour extraction on the two copied images respectively to obtain a UAV image and an environment image; an intelligent interception module, which is used to, after receiving the UAV image and the environment image, perform environment recognition on the environment image to determine the environmental location, and call the monitoring device to perform real-time positioning on the target UAV according to the UAV image and the environmental location; compared with the existing private enterprises that use low-precision radar scanning devices for UAV positioning due to cost reasons, the present invention is more conducive to improving the interception accuracy of illegal UAVs.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent control, and particularly relates to an intelligent UAV interception system based on image communication. Background Art

[0002] A UAV is an unmanned aerial vehicle controlled by a radio remote control device or its own program control device. With the development and popularization of UAV technology, the application of UAVs in the civilian field is becoming more and more extensive. However, the abuse of UAVs has also brought security problems, such as privacy infringement and illegal reconnaissance. In the face of illegal UAVs, the existing method is to intercept illegal UAVs through a UAV interception system. However, when the existing UAV interception system tracks a UAV, for example, a patent for invention published under publication number CN106709498A scans and monitors the target airspace in real time through a radar. However, due to the characteristics of UAVs such as low-altitude and ultra-low-altitude flight, slow flight speed and being difficult to be detected by radar, and considering that private enterprises cannot use high-precision radars to quickly confirm illegal UAVs due to cost constraints, the efficiency of existing private enterprises in intercepting UAVs is relatively low. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide an intelligent UAV interception system based on image communication to solve the above technical problems.

[0004] To achieve the above purpose, the present invention provides the following technical solutions:

[0005] An intelligent UAV interception system based on image communication, comprising:

[0006] A target UAV recognition module, configured to obtain the original image data of the target UAV through a monitoring device, perform threat recognition on the original image data, copy the original image data when a threat is confirmed, and perform UAV image recognition and contour extraction on the two copied images respectively to obtain a UAV image and an environment image;

[0007] An intelligent interception module, configured to, after receiving the UAV image and the environment image, perform environment recognition on the environment image to determine the environmental location, and call the monitoring device to perform real-time positioning on the target UAV according to the UAV image and the environmental location, and control the interception UAVs in the corresponding area to intercept the target UAV according to the real-time positioning.

[0008] Further, an intelligent UAV interception system based on image communication further comprises a threat information storage module, configured to store the original image data of the target UAV with a threat.

[0009] Further, the target UAV recognition module comprises:

[0010] Self-warning unit, connected to all monitoring devices within a preset target airspace, used to call the corresponding monitoring data when a drone appears in the monitoring data of the monitoring device as the original image data of the target drone; wherein, the original image data is animated image data of a preset duration, and the animated image data includes the target drone and surrounding environment data;

[0011] Image preprocessing unit, used to perform threat recognition on the original image data. After confirming the existence of a threat, copy the original image data to obtain a first image and a second image, and perform drone image recognition and contour extraction on the first image and the second image respectively to obtain a drone image and an environment image; wherein, threat recognition includes recognizing the target drone information and the surrounding environment data of the target drone.

[0012] Furthermore, performing threat recognition on the original image data includes:

[0013] Performing drone information recognition and environment data recognition on the original image data to obtain a first recognition result and a second recognition result;

[0014] Judging that all information in the first recognition result corresponds to the safe drone information in the preset security database;

[0015] If not, confirm the existence of a threat;

[0016] Judging whether the environmental information in the second recognition result is the same as the environmental information at any position in the environmental bird's-eye view of the preset target airspace;

[0017] If so, obtain the permission level in the first recognition result and judge whether the permission level allows the target drone to fly in the air corresponding to the environmental information;

[0018] If not, confirm the existence of a threat.

[0019] Furthermore, the intelligent interception module includes:

[0020] Environmental positioning unit, used to receive the environment image and determine the position where the environment image belongs in the environmental bird's-eye view of the preset target airspace as environmental positioning;

[0021] Drone positioning unit, used to receive the drone image, capture the position of the target drone in real time by calling the monitoring devices within the preset target airspace according to the drone image, and perform real-time positioning on the target drone based on the multi-angle real-time captured images and environmental positioning;

[0022] An interception unit, which is used to obtain real-time positioning, draw a predicted flight route map of the target UAV according to the real-time positioning, calculate the optimal interception point of the interception UAV as the target interception point based on the predicted flight route map, the flight speed, and the calling speed of the interception UAV, and call the interception UAVs in the area where the target interception point is located and the interception UAVs in the adjacent areas to form an interception network to intercept the target UAV.

[0023] Furthermore, call the monitoring devices in the preset target airspace according to the UAV image to capture the position of the target UAV in real time, and perform real-time positioning on the target UAV according to the multi-angle real-time captured images and environmental positioning, including:

[0024] Call the multi-angle initial image data of all monitoring devices in the area where the environmental positioning belongs at the moment when the target UAV is first photographed, and calculate the initial positioning of the target UAV according to the multi-angle initial image data and the device data of the monitoring devices;

[0025] Call the monitoring devices in the preset target airspace to quickly identify and lock the target UAV in the preset target airspace based on the UAV image, and capture the action images of the target UAV in real time;

[0026] Obtain the multi-angle action images of the target UAV captured by all monitoring devices at each moment for drawing the action trajectory of the target UAV;

[0027] Generate the real-time positioning of the target UAV according to the initial positioning and the action trajectory of the target UAV.

[0028] Furthermore, draw a predicted flight route map of the target UAV according to the real-time positioning, and calculate the optimal interception point of the interception UAV as the target interception point according to the predicted flight route map, the flight speed, and the calling speed of the interception UAV, including:

[0029] Obtain the action trajectory corresponding to the real-time positioning, and predict the flight route of the target UAV by using the machine learning method according to the action trajectory to obtain the predicted flight route map;

[0030] Obtain the average flight speed of the target UAV to calculate the first moment when the target UAV passes through each optimal interception point on the predicted flight route map;

[0031] Obtain the calling speed of the interception UAVs in each optimal interception point area to calculate the second moment when the interception UAVs reach the corresponding interception positions of the optimal interception points starting from the call timing;

[0032] Calculate the optimal interception degree of each optimal interception point according to the interception urgency of the optimal interception point and the time matching degree between the first moment and the second moment corresponding to the optimal interception point;

[0033] Obtain the optimal interception point with the highest optimal interception degree as the target interception point.

[0034] Furthermore, according to the interception urgency of the optimal interception point and the time matching degree between the first moment and the second moment corresponding to the optimal interception point, calculate the optimal interception degree of each optimal interception point, including: obtaining the interception urgency of the optimal interception point ; wherein, the closer the optimal interception point is to the preset central area, the smaller the value of the interception urgency;

[0035] Obtain the first moment corresponding to the optimal interception point and the second moment ;

[0036] When , the optimal interception degree of the current optimal interception point is equal to infinitesimal;

[0037] When , the calculation formula of the optimal interception degree of the current optimal interception point is as follows: wherein, K is the preset initial value of the urgency. Furthermore, call the interception drones in the area where the target interception point is located and the interception drones in the adjacent areas to form an interception network to intercept the target drone, including:

[0038] Obtain the target drone control device in the area where the target interception point is located and the adjacent drone control device in the area adjacent to the target interception point;

[0039] Receive the data packets sent by the interception unit to several drone control devices at the same time, and extract the drone images, environmental images and the specified drone control devices in the data packets; wherein, the specified drone control devices include the target drone control device and the adjacent drone control device;

[0040] Make the drone images unable to be displayed on the un-specified drone control devices; and make the drone images be displayed on the specified drone control devices;

[0041] Combine all the drone control devices that display the drone images to construct a temporary drone control device group; wherein, the temporary drone control device group takes the target drone control device as the main device and the adjacent drone control device as the auxiliary device, and the main device sends the overall control instruction to the auxiliary device;

[0042] According to the temporary drone control device group, control the interception drones in the corresponding areas to form an interception network to intercept the target drone.

[0043] The beneficial effects of the present invention are as follows:

[0044] The present invention provides an intelligent UAV interception system based on image communication. By using image communication and combining with image monitoring devices in the target airspace, it can quickly lock illegal UAVs and dispatch interceptor UAVs to accurately intercept illegal UAVs according to the image features of illegal UAVs transmitted through image communication. Compared with the existing low-precision radar scanning devices used by private enterprises, it is more conducive to improving the interception accuracy of illegal UAVs. At the same time, compared with military enterprises, the cost of the intelligent UAV interception system based on image communication provided by the present invention is lower.

[0045] Other advantages, objectives, and features of the present invention will be described in the subsequent specification and will be obvious to those skilled in the art to some extent, or those skilled in the art can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in the written specification and the attached drawings.

[0046] The technical solutions of the present invention will be further described in detail below through the attached drawings and embodiments. Brief Description of the Drawings

[0047] The attached drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the attached drawings:

[0048] Figure 1 It is a schematic diagram of the system module of an intelligent UAV interception system based on image communication in an embodiment of the present invention;

[0049] Figure 2 It is a schematic diagram of the threat recognition process of the original image data in an intelligent UAV interception system based on image communication in an embodiment of the present invention;

[0050] Figure 3 It is a schematic diagram of the real-time positioning process of the target UAV in an intelligent UAV interception system based on image communication in an embodiment of the present invention;

[0051] Figure 4 It is a schematic diagram of the calculation process of calculating the target interception point in an intelligent UAV interception system based on image communication in an embodiment of the present invention;

[0052] Figure 5 It is a schematic diagram of the call process of calling the interceptor UAV to intercept the target UAV in an intelligent UAV interception system based on image communication in an embodiment of the present invention. Detailed Embodiments

[0053] The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and are not intended to limit the present invention.

[0054] As Figure 1 shown, the present invention provides an intelligent UAV interception system based on image communication, comprising:

[0055] A target UAV recognition module, configured to obtain the original image data of the target UAV through a monitoring device, perform threat recognition on the original image data, copy the original image data after confirming the existence of a threat, and perform UAV image recognition and contour extraction on the two copied images respectively to obtain a UAV image and an environment image;

[0056] An intelligent interception module, configured to, after receiving the UAV image and the environment image, perform environment recognition on the environment image to determine the environmental location, and call the monitoring device to perform real-time positioning on the target UAV according to the UAV image and the environmental location, and control the interception UAVs in the corresponding area to intercept the target UAV according to the real-time positioning;

[0057] The working principle of the above technical solution is as follows: In order to reduce the radar scanning cost paid by enterprises when intercepting UAVs, the present invention provides an intelligent UAV interception system based on image communication. In combination with the monitoring devices in the target airspace, it uses the method of image communication to transmit the recognized UAV device pictures to the interception system, and the interception system intercepts the illegal UAV according to the illegal UAV picture information. Specifically, this system includes a target UAV recognition module and an intelligent interception module. Among them, the target UAV recognition module is mainly used to obtain the original image data of the target UAV by using a monitoring device and perform threat recognition on the original image data. It should be noted that the monitoring device preferably uses a high-speed camera to facilitate image acquisition of the target UAV; when it is determined that the current original image data poses a threat, the original image data is copied to obtain two copied data, and UAV image recognition and contour extraction are performed on the two copied data respectively to obtain a UAV image and an environment image, where the environment image is the airspace environment image after removing the UAV; by adopting the method of image communication, this module is more conducive to improving the recognition accuracy of illegal UAVs compared with the existing private enterprises using low-precision radar scanning devices; the intelligent interception module is mainly used to, after receiving the UAV image and the environment image transmitted by the target UAV recognition module, perform environmental recognition of the target airspace on the environment image to determine the environmental location where the target UAV is first discovered, and perform real-time positioning on the target UAV according to the environmental location by calling the relevant monitoring device according to the relevant features of the transmitted UAV image, and finally control the interception UAVs in the corresponding area to intercept the target UAV according to the real-time positioning;

[0058] The beneficial effects of the above technical solution are as follows: Through the above technical solution, by means of image communication, combined with the image monitoring equipment in the target airspace, illegal drones are quickly locked, and an interceptor drone is dispatched to accurately intercept the illegal drones according to the image features of the illegal drones transmitted through image communication. Compared with the existing private enterprises using low-precision radar scanning devices, it is more conducive to improving the interception accuracy of illegal drones. At the same time, compared with military enterprises, the cost of the drone intelligent interception system using image communication provided by the present invention is lower.

[0059] In one embodiment, a drone intelligent interception system based on image communication further includes: a threat information storage module, configured to store the original image data of target drones posing threats.

[0060] The working principle and beneficial effects of the above technical solution are as follows: To enhance the control of illegal drones and make the interception information traceable, the system also provides a threat information storage module for storing the original image data of target drones determined to pose threats. It should be noted that the aerial view of the environment in the target airspace and other relevant interception data are also stored in this threat information storage module.

[0061] In one embodiment, the target drone recognition module includes:

[0062] A self-warning unit, connected to all monitoring devices in a preset target airspace, configured to call the corresponding monitoring data as the original image data of the target drone when a drone appears in the monitoring data of the monitoring device; wherein, the original image data is animated image data of a preset duration, and the animated image data includes the target drone and surrounding environment data.

[0063] An image preprocessing unit, configured to perform threat recognition on the original image data. After confirming the existence of a threat, the original image data is copied to obtain a first image and a second image, and the drone image recognition and contour extraction are respectively performed on the first image and the second image to obtain a drone image and an environment image; wherein, the threat recognition includes the recognition of the target drone information and the recognition of the surrounding environment data of the target drone.

[0064] The working principle of the above technical solution is as follows: The system includes a target UAV recognition module. Among them, this module includes a self-warning unit and an image preprocessing unit. The self-warning unit is connected to all monitoring devices within a preset target airspace. When a UAV appears in the monitoring data of any monitoring device, the corresponding monitoring data is called as the original image data of the target UAV. Among them, in order to better analyze the target UAV, the obtained original image data is preferably a moving picture of a preset duration, which includes the target UAV and the surrounding environmental data, and is sent to the image preprocessing unit for threat recognition of the original image data. After confirming the existence of a threat, the original image data is copied to obtain a first image and a second image, and at the same time, the original image data is transmitted to the threat information storage module for storage. It should be noted that threat recognition includes identifying the target UAV information and the surrounding environmental data of the target UAV. After obtaining the copied images, the first image and the second image are respectively subjected to UAV image recognition and contour extraction to obtain a UAV image and an environmental image, which are transmitted to the intelligent interception module;

[0065] The beneficial effects of the above technical solution are as follows: Through the above technical solution, the target UAV is recognized by means of image communication, and the recognition result is transmitted to the intelligent interception module for interception operation. Compared with the use of a low-precision radar scanning device, the monitoring accuracy of this module is higher.

[0066] As Figure 2 shown, in one embodiment, the threat recognition of the original image data includes:

[0067] S101. Identify the UAV information and environmental data in the original image data to obtain a first recognition result and a second recognition result;

[0068] S102. Judge whether all the information in the first recognition result corresponds to the safe UAV information in the preset security database;

[0069] If not, go to S105; if so, execute S103;

[0070] S103. Judge whether the environmental information in the second recognition result is the same as the environmental information at any position in the environmental bird's-eye view of the preset target airspace. If not, go to S105; if so, execute S104;

[0071] S104. Obtain the permission level in the first recognition result and judge whether the permission level allows the target UAV to fly in the air corresponding to the environmental information. If not, go to S105; if so, feedback no threat;

[0072] S105. Confirm the existence of a threat;

[0073] The working principle of the above technical solution is as follows: When the image preprocessing unit conducts threat recognition on the original image data, it first conducts UAV information recognition and environmental data recognition on the original image data. Among them, UAV information recognition refers to recognizing the model characteristics and surface coating markers of the UAV to obtain the first recognition result. Environmental data recognition refers to recognizing the inherent characteristics such as buildings and trees in the original image data to obtain the second recognition result. After obtaining the first recognition result, it is determined whether all the recognition information in the first recognition result corresponds one by one to the safe UAV information in the preset security database, that is, it is determined whether the model characteristics, marker recognition results, etc. are the same as one of the safe UAV information in the preset security database. The preset security database is preferably the same database as the threat information storage module. If the judgment information obtained from the first recognition result is negative, it is confirmed that there is a threat. Otherwise, it continues to determine whether the environmental information in the second recognition result is the same as the environmental information at any position in the environmental bird's-eye view of the preset target airspace, that is, it is determined whether the current target UAV is flying within the preset target airspace range to avoid false alarms. If the judgment information obtained from the second recognition result is negative, it is confirmed that there is a threat. Otherwise, it continues to obtain the permission level of the safe UAV information feedback by the preset security database in the first recognition result, and determines whether this permission level supports the target UAV to have the corresponding permission to conduct activities in the airspace corresponding to the current environmental information. If the obtained judgment result is negative, it is confirmed that there is a threat. Otherwise, it is feedback that the current UAV activity is threat-free;

[0074] The beneficial effect of the above calculation solution is as follows: Through the above technical solution, a multiple recognition method is adopted to conduct threat recognition on the original image data, which is beneficial to reducing the probability of misrecognition, improving the accuracy of threat recognition, and further improving the interception efficiency of illegal UAVs.

[0075] In one embodiment, the intelligent interception module includes:

[0076] An environmental positioning unit, which is used to receive the environmental image and determine the position where the environmental image belongs in the environmental bird's-eye view of the preset target airspace as environmental positioning;

[0077] A UAV positioning unit, which is used to receive the UAV image, call the monitoring equipment within the preset target airspace according to the UAV image to capture the position of the target UAV in real time, and conduct real-time positioning on the target UAV according to the multi-angle real-time captured image and environmental positioning;

[0078] An interception unit, which is used to obtain the real-time positioning, draw a predicted flight route map of the target UAV according to the real-time positioning, calculate the optimal interception point of the interception UAV as the target interception point according to the predicted flight route map, the flight speed of the target UAV, and the calling speed of the interception UAV, and call the interception UAVs in the area where the target interception point is located and the interception UAVs in the adjacent areas to form an interception network to intercept the target UAV;

[0079] The working principle of the above technical solution is as follows: This system includes an intelligent interception module. Among them, the intelligent interception module includes an environment positioning unit, a UAV positioning unit, and an interception unit. After receiving the environmental image transmitted by the target UAV recognition module, the environment positioning unit determines the current position where the environmental image belongs through the environmental bird's-eye view of the preset target airspace, and then determines the environmental positioning where the current target UAV is located. It is worth noting that, in order to better perform environmental positioning on the target UAV, the target airspace is pre-divided into environmental areas, and the division rules are determined according to the monitoring devices arranged within the target airspace range, and it is necessary to ensure that the monitoring devices within the divided area can achieve full monitoring of the current area; after determining the environmental positioning, the UAV positioning unit receives the UAV image transmitted by the target UAV recognition module, so as to call all the monitoring devices within the preset target airspace according to the characteristic information of the UAV image to capture the position of the target UAV in real time, and at the same time call the multi-angle real-time capture images during environmental positioning to determine the initial positioning of the UAV, and determine the flight route of the target UAV according to the subsequent multi-angle real-time capture images to complete the real-time positioning of the target UAV; finally, the interception unit draws a flight route prediction map of the target UAV according to the real-time positioning, and calculates the optimal interception point of the interception UAV as the target interception point according to the flight route prediction map, the flight speed of the target UAV, and the calling speed of the interception UAV, and then calls the interception UAVs in the area where the target interception point is located and the interception UAVs in the adjacent areas to form an interception network to intercept the target UAV; the formation of the interception network is defined by the user himself;

[0080] The beneficial effects of the above technical solution are as follows: Through the above technical solution, the identification, positioning, and interception of illegal UAVs are completed through the data of image communication, and at the same time, the illegal UAVs are intercepted according to the calculated target interception points. Compared with intercepting after scanning with a low-precision radar scanning device, the interception success rate of this module is higher.

[0081] As Figure 3 shown, in one embodiment, calling the monitoring devices within the preset target airspace according to the UAV image to capture the position of the target UAV in real time, and performing real-time positioning on the target UAV according to the multi-angle real-time capture images and environmental positioning, includes:

[0082] S201. Call the multi-angle initial image data of all the monitoring devices within the area where the environmental positioning belongs when the target UAV is first photographed, and calculate the initial positioning of the target UAV according to the multi-angle initial image data and the device data of the monitoring devices;

[0083] S202, calling the monitoring equipment in the preset target airspace, based on the drone image, quickly identifying and locking the target drone in the preset target airspace, and capturing the action image of the target drone in real time;

[0084] S203, obtaining multi-angle action images of the target UAV captured by all monitoring devices at every moment, for drawing the action trajectory of the target UAV;

[0085] S204, generating a real-time positioning of the target UAV according to the initial positioning and action trajectory of the target UAV;

[0086] The working principle and beneficial effects of the above technical solution are as follows: when the drone positioning unit locates the target drone, the first thing to consider is the initial position of the target drone, and then predicts and confirms its real-time positioning based on its constantly moving trajectory. Therefore, when this unit confirms that the target drone is a threat, it calls the multi-angle initial image data of the target drone when it is first photographed in all monitoring devices in the area to which the environmental positioning belongs. Multi-angle refers to the target drone image taken from different angles by different monitoring devices at the same time, and then the initial positioning of the target drone is calculated based on the multi-angle initial image data and the device data of the monitoring device. The calculation method preferably adopts a method based on computer vision and image processing for calculation. The device data includes the focal length of the monitoring camera, and the multi-angle initial image data includes the pixel width of the target drone in each image data. According to the following formula, multiple equations can be obtained, and the distance between each monitoring camera and the target drone is calculated by the simultaneous equations. Finally, the position of the target drone is deduced based on the layout data of the monitoring camera. The formula is:

[0087] in, is the distance between each surveillance camera and the target UAV, W is the actual width of the target UAV, F is the focal length of the camera, and P is the pixel width of the target UAV in the initial image data;

[0088] When calculating the initial position, the monitoring equipment in the preset target airspace is called synchronously. Based on the drone image, the target drone in the preset target airspace is quickly identified and locked, and the action image of the target drone is captured in real time. Then, the multi-angle action images of the target drone at each moment captured by all monitoring devices are obtained to draw the action trajectory of the target drone. Finally, the real-time positioning of the target drone is generated according to the initial positioning and action trajectory of the target drone. Compared with accurately positioning the position of the target drone at each moment, this method determines the initial positioning, and then uses the action trajectory combined with the initial positioning to predict the real-time positioning of the target drone. There is no need to perform complex positioning calculations again, and the positioning efficiency is higher.

[0089] As Figure 4 shown, in one embodiment, a flight route prediction map of the target UAV is drawn according to real-time positioning, and an optimal interception point of the interception UAV is calculated as the target interception point according to the flight route prediction map, the flight speed of the target UAV, and the call speed of the interception UAV, including:

[0090] S301. Obtain the action trajectory corresponding to the real-time positioning, and predict the flight route of the target UAV by using a machine learning method according to the action trajectory to obtain a flight route prediction map;

[0091] S302. Obtain the average flight speed of the target UAV to calculate the first moment when the target UAV passes through each optimal interception point on the flight route prediction map;

[0092] S303. Obtain the call speed of the interception UAV in each optimal interception point area to calculate the second moment when the interception UAV reaches the corresponding interception position of the optimal interception point from the start of the call;

[0093] S304. Calculate the optimal interception degree of each optimal interception point according to the interception urgency of the optimal interception point and the time matching degree between the first moment and the second moment corresponding to the optimal interception point;

[0094] S305. Obtain the optimal interception point with the highest optimal interception degree as the target interception point;

[0095] The working principle and beneficial effects of the above technical solution are as follows: When calculating the target interception point, the interception unit first obtains the flight trajectory calculated by the UAV positioning unit, and predicts the flight route of the target UAV by using machine learning based on the flight trajectory to obtain a subsequent flight route prediction map. The prediction method is already relatively mature in the prior art and will not be elaborated here. After obtaining the flight route prediction map, according to the calculated average flight speed of the target UAV, calculate the first moment when the target UAV passes through each optimal interception point on the flight route prediction map, and at the same time obtain the call speed of the interception UAV within the area of each optimal interception point to calculate the second moment when the interception UAV reaches the specified interception position corresponding to the optimal interception point from the start of being called. This second moment refers to the moment when the last interception UAV reaches the corresponding interception position. Finally, according to the interception urgency of the optimal interception point and the time matching degree between the first moment and the second moment corresponding to the optimal interception point, calculate the optimal interception degree of each optimal interception point, and screen out the optimal interception point with the highest optimal interception degree as the target interception point, and intercept the target UAV at the target interception point. Through the above technical solution, the precise interception of illegal UAVs is realized, the number of ineffective calls of the interception UAVs is reduced, and the interception efficiency of illegal UAVs is improved; it should be noted that the optimal interception point involved in this solution refers to the point where the interception UAV can complete the formation of the interception network within the preset interception time. When designing the optimal interception point, the entire target airspace is pre-divided into a three-dimensional grid map including multiple cube grids. Assume that the target UAV is in any grid, and then simulate the call of the UAVs in the current area and adjacent areas for this target UAV, and judge whether the call time for the interception UAVs to form the interception network meets the preset interception time threshold set in advance. If it meets, define this grid as the optimal interception point. If it does not meet, continue to judge the next network until all grids are traversed and judged to obtain several optimal interception points. The first moment refers to the time when the target UAV just enters the grid corresponding to the optimal interception point. Through the design of the optimal interception point, it is beneficial to improve the interception probability of the interception UAVs for precise interception of the target UAV.

[0096] In one embodiment, calculating the optimal interception degree of each optimal interception point according to the interception urgency of the optimal interception point and the time matching degree between the first moment and the second moment corresponding to the optimal interception point includes: obtaining the interception urgency of the optimal interception point ; wherein, the closer the optimal interception point is to the preset central area, the smaller the value of the interception urgency;

[0097] obtaining the first moment corresponding to the optimal interception point and the second moment ;

[0098] When When it is [time], the optimal interception degree of the current optimal interception point equals infinitesimal;

[0099] When it is [time], the optimal interception degree of the current optimal interception point has the following calculation formula: wherein, K is the preset initial value of urgency; the beneficial effects of the above technical solution are: by defining and calculating the optimal interception degree and determining the appropriate interception time, the target UAV can be intercepted far away from the preset central area, which is beneficial to improving the reliability of the interception system.

[0100] As Figure 5 shown, in one embodiment, the interception UAVs in the area where the target interception point is located and the interception UAVs in the adjacent area are called to form an interception network to intercept the target UAV, including:

[0101] S401. Obtain the target UAV control device in the area where the target interception point is located and the adjacent UAV control device in the area adjacent to the target interception point;

[0102] S402. Receive the data packets simultaneously sent by the interception unit to several UAV control devices, and extract the UAV images, environmental images and the designated UAV control devices in the data packets; wherein, the designated UAV control devices include the target UAV control device and the adjacent UAV control device;

[0103] S403. Prevent the UAV images from being displayed on the non-designated UAV control devices; and display the UAV images on the designated UAV control devices;

[0104] S404. Combine all the UAV control devices that display the UAV images to construct a temporary UAV control device group; wherein, the temporary UAV control device group takes the target UAV control device as the main device and the adjacent UAV control device as the auxiliary device, and the main device sends the overall control instruction to the auxiliary device;

[0105] S405. According to the temporary UAV control device group, control the interception UAVs in the corresponding area to form an interception network to intercept the target UAV;

[0106] The working principle of the above technical solution is as follows: When the interception unit calls the interception UAV to intercept the target UAV, it first obtains the target UAV control equipment in the area where the target interception point is located and the adjacent UAV control equipment in the area adjacent to the target interception point, and defines them as designated equipment. Then it sends data packets and designated equipment information to the UAV control equipment in the entire preset target airspace. Then each UAV control equipment in the preset target airspace receives the data packets simultaneously sent by the interception unit to all UAV control equipment, and extracts the UAV images, environmental images and the designated UAV control equipment from the data packets; among them, the designated UAV control equipment includes the target UAV control equipment and the adjacent UAV control equipment, and at the same time makes the UAV images unable to be displayed on the UAV control equipment that is not designated; and makes the UAV images displayed on the designated UAV control equipment, that is, makes the information received by the UAV control equipment that does not need to be mobilized be information without UAVs. At this time, the UAV control equipment will continue to standby, while the control equipment that receives the UAV information will start to form an interception network with the interception UAVs. During the formation of the interception network, all the UAV control equipment that displays UAV images is combined to construct a temporary UAV control equipment group; among them, the temporary UAV control equipment group takes the target UAV control equipment as the main equipment and the adjacent UAV control equipment as the auxiliary equipment. The main equipment sends overall control instructions to the auxiliary equipment. Finally, according to the temporary UAV control equipment group, the corresponding area of the interception UAVs is controlled to form an interception network to intercept the target UAV.

[0107] The beneficial effects of the above technical solution are as follows: Through the above technical solution, the formation of the interception instruction and the control of the UAV are decentralized to the UAV control equipment. The UAV control equipment completes the control of the interception UAV. At the same time, in the form of specified image communication transmission, the image data is transmitted throughout the area, and then the display content is controlled by the specified information, reducing the time error in the call of the interception UAVs by different UAV control equipment caused by point-to-point transmission. At the same time, it is not necessary to mobilize all the interception UAVs for interception as a whole, reducing the ineffective call frequency of the UAVs, which is beneficial to improving the intelligent level of the UAV interception system.

[0108] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. An intelligent drone interception system based on image communication, characterized in that: include: The target drone identification module is used to obtain the original image data of the target drone through the monitoring equipment, perform threat identification on the original image data, copy the original image data after confirming the existence of a threat, and perform drone image identification and contour extraction on the two copied images to obtain the drone image and the environment image; Intelligent interception module, wherein the intelligent interception module includes: An environment positioning unit is used to receive an environment image and determine the location of the environment image through an environment bird's-eye view of a preset target airspace as environment positioning; The UAV positioning unit is used to receive the UAV image, call the monitoring equipment in the preset target airspace according to the UAV image to capture the position of the target UAV in real time, and locate the target UAV in real time according to the multi-angle real-time captured image and environmental positioning; The interception unit is used to obtain real-time positioning and the action trajectory corresponding to the real-time positioning, and predict the flight path of the target UAV using a machine learning method based on the action trajectory to obtain a flight path prediction map; The average flight speed of the target UAV is obtained to calculate the first moment of each optimal interception point of the target UAV passing through the flight route prediction map; Obtain the interception drone call speed in each optimal interception point area to calculate the second moment when the interception drone reaches the interception position corresponding to the optimal interception point from the start of the call; The optimal interception degree of each optimal interception point is calculated according to the interception urgency of the optimal interception point and the time matching degree between the first moment and the second moment corresponding to the optimal interception point; The optimal interception point with the highest optimal interception degree is obtained as the target interception point, and the interception drones in the area where the target interception point is located and the interception drones in the adjacent areas are called to form an interception network to intercept the target drone.

2. According to claim 1, the intelligent drone interception system based on image communication is characterized in that: Also includes: The threat information storage module is used to store the original image data of the target drone that poses a threat.

3. The intelligent drone interception system based on image communication according to claim 1 is characterized in that: The target drone identification module includes: The self-warning unit is connected to all monitoring devices in the preset target airspace, and is used to call corresponding monitoring data when a drone appears in the monitoring data of the monitoring device as the original image data of the target drone; wherein the original image data is dynamic image data of a preset time length, and the dynamic image data includes the target drone and the surrounding environment data; The image preprocessing unit is used to perform threat identification on the original image data, and after confirming the existence of the threat, the original image data is copied to obtain the first image and the second image, and the first image and the second image are respectively subjected to drone image identification and contour extraction to obtain the drone image and the environment image; wherein the threat identification includes identifying the target drone information and identifying the environment data surrounding the target drone.

4. The intelligent drone interception system based on image communication according to claim 3 is characterized in that: Perform threat identification on raw image data, including: Performing drone information recognition and environmental data recognition on the original image data to obtain a first recognition result and a second recognition result; Determining that all information of the first recognition result corresponds to the safety drone information in a preset safety database; If not, confirm that there is a threat; Determine whether the environmental information of the second recognition result is the same as the environmental information of any position in the environmental bird's-eye view of the preset target airspace; If yes, obtain the permission level in the first recognition result, and determine whether the permission level allows the target UAV to fly in the air corresponding to the environmental information; If not, confirm that there is a threat.

5. The intelligent drone interception system based on image communication according to claim 1 is characterized in that: Based on the drone image, the monitoring equipment in the preset target airspace is called to capture the position of the target drone in real time, and the target drone is positioned in real time based on the multi-angle real-time captured images and environmental positioning, including: Calling the multi-angle initial image data of all monitoring devices in the area to which the environmental positioning belongs when the target UAV is first photographed, and calculating the initial positioning of the target UAV based on the multi-angle initial image data and the device data of the monitoring devices; Call the monitoring equipment in the preset target airspace, quickly identify and lock the target drone in the preset target airspace based on the drone image, and capture the action image of the target drone in real time; Obtain multi-angle action images of the target UAV at every moment captured by all monitoring devices to draw the action trajectory of the target UAV; According to the initial positioning and action trajectory of the target UAV, the real-time positioning of the target UAV is generated.

6. The intelligent drone interception system based on image communication according to claim 1 is characterized in that: According to the interception urgency of the optimal interception point and the time matching degree between the first moment and the second moment corresponding to the optimal interception point, the optimal interception degree of each optimal interception point is calculated, including: Get the interception urgency of the optimal interception point ; Among them, the closer the optimal interception point is to the preset central area, the smaller the interception urgency value; Get the first moment corresponding to the optimal interception point and the second moment ; when When the optimal interception degree of the current optimal interception point is is equal to infinitesimal; when When the optimal interception degree of the current optimal interception point is The calculation formula is as follows: ， Among them, A preset initial value for urgency.

7. The intelligent drone interception system based on image communication according to claim 1 is characterized in that: Calling interception drones in the area where the target interception point is located and interception drones in adjacent areas to form an interception network to intercept the target drone, including: Obtain the target UAV control equipment in the area where the target interception point is located, and the adjacent UAV control equipment in the area adjacent to the target interception point; Receive data packets sent by the interception unit to several drone control devices at the same time, and extract drone images, environment images and designated drone control devices in the data packets; wherein the designated drone control devices include target drone control devices and adjacent drone control devices; Preventing the drone image from being displayed on an unspecified drone control device; and enabling the drone image to be displayed on a specified drone control device; Combine all drone control devices that display drone images to build a temporary drone control device group; the temporary drone control device group uses the target drone control device as the main device and the adjacent drone control devices as the auxiliary devices, and the main device sends overall control instructions to the auxiliary devices; According to the temporary drone control equipment group, the interception drones in the corresponding area are controlled to form an interception network to intercept the target drone.

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