An interference intercept system and method for unknown aerial vehicles

Abstract

The application provides an interference interception system and method for unknown aircrafts, wherein an image acquisition module is configured to acquire at least one unknown aircraft image; a target identification module is configured to determine whether the shape of a target aircraft is the same as the shape of a passable aircraft for each unknown aircraft image, wherein the target aircraft is an unknown aircraft contained in the unknown aircraft image; a target control module is configured to control the target aircraft to fly from a no-fly zone to an interception area if the shape of the target aircraft is not the same as the shape of the passable aircraft; and a target interception module is configured to control at least one unmanned aerial vehicle for intercepting the target aircraft to fly to the interception area to intercept the target aircraft. The above scheme is used to intercept the aircraft entering the no-fly zone, so as to avoid safety hazards.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of aircraft control, in particular to an interference interception system and method for unknown aircraft. BACKGROUND

[0002] With the continuous maturity of remote sensing technology, navigation technology and electronic technology, the use range of aircraft is rapidly expanding, and the functions that can be achieved are increasingly diversified, which brings convenience to the fields of communication, navigation and transportation. Based on the different shapes of different aircraft and the different functions they achieve, different flight restricted areas are set up for different aircraft by the relevant departments. In the flight restricted area of a certain type of aircraft, the aircraft of this type cannot fly normally in this flight restricted area due to the flight conditions (including flight space, flight authority, etc.) of the flight restricted area. If a certain type of aircraft forcibly enters the flight restricted area set for it, it is likely that the flight conditions provided by the area cannot meet the needs of the aircraft, resulting in the aircraft being unable to fly normally, thus causing a safety hazard.

[0003] However, during the flight of the aircraft, it may enter the flight restricted area set for it due to external interference or errors in the calculation of the target flight trajectory, thus causing a safety hazard. Therefore, how to intercept the aircraft that enters the flight restricted area to avoid a safety hazard has become a problem to be solved. SUMMARY

[0004] Therefore, the purpose of the present application is to provide an interference interception system and method for unknown aircraft to intercept the aircraft that enters the flight restricted area to avoid a safety hazard.

[0005] In a first aspect, the present application provides an interference interception system for unknown aircraft, which comprises an image acquisition module, a target identification module, a target control module and a target interception module:

[0006] The image acquisition module is configured to acquire at least one unknown aircraft image, wherein each unknown aircraft image contains an unknown aircraft in the flight restricted area;

[0007] The target identification module is configured to determine whether the shape of the target aircraft is the same as that of the passable aircraft for each unknown aircraft image, wherein the target aircraft is the unknown aircraft contained in the unknown aircraft image, and the passable aircraft is the aircraft that has flight authority in the flight restricted area;

[0008] The target control module is configured to control the target aircraft to fly from the flight restricted area to the interception area if the shape of the target aircraft is not the same as that of the passable aircraft;

[0009] The target interception module is configured to control at least one unmanned aerial vehicle to fly to the interception area for intercepting the target aerial vehicle and perform an interception task of intercepting the target aerial vehicle.

[0010] Optionally, the system further comprises a warning information sending module.

[0011] After the target identification module determines whether the shape of the target aerial vehicle is the same as the shape of the passable aerial vehicle for each unknown aerial vehicle image, the target control module is further configured to:

[0012] If the shape of the target aerial vehicle is the same as the shape of the passable aerial vehicle, the target aerial vehicle is controlled to keep the current flight trajectory.

[0013] After the target identification module determines whether the shape of the target aerial vehicle is the same as the shape of the passable aerial vehicle for each unknown aerial vehicle image, the warning information sending module is configured to:

[0014] If the shape of the target aerial vehicle is not the same as the shape of the passable aerial vehicle, preset warning information is sent to the control center.

[0015] Optionally, the system further comprises a target positioning module and a trajectory generation module.

[0016] The target positioning module is configured to acquire position coordinates of the target aerial vehicle at at least one time point through a radar after the image acquisition module acquires at least one unknown aerial vehicle image.

[0017] The trajectory generation module is configured to generate an actual flight trajectory of the target aerial vehicle according to the position coordinates of the target aerial vehicle at the at least one time point.

[0018] Optionally, the system further comprises a trajectory prediction module and a flight trajectory sending module.

[0019] The trajectory prediction module is configured to input the actual flight trajectory of the target aerial vehicle into a trained flight trajectory prediction model to determine a predicted flight trajectory of the target aerial vehicle in a future preset time period after the trajectory generation module generates the actual flight trajectory of the target aerial vehicle according to the position coordinates of the target aerial vehicle at the at least one time point.

[0020] The flight trajectory sending module is configured to send the predicted flight trajectory of the target aerial vehicle in the future preset time period to the control center.

[0021] Optionally, the target interception module is specifically used for:

[0022] controlling at least one of the UAVs to fly to the interception area;

[0023] determining a target UAV formation with the same identification as the shape of the target aircraft from a UAV formation database according to the shape of the target aircraft;

[0024] controlling at least one of the UAVs to target-intercept the target aircraft in the target UAV formation.

[0025] Optionally, the system further comprises a target scanning module, a target reconstruction module and a model sending module;

[0026] The target scanning module is configured to scan the surface of the target aircraft by a three-dimensional scanner arranged on at least one of the UAVs to obtain a surface coordinate point set of the target aircraft after the target interception module controls at least one of the UAVs to fly to the interception area to target-intercept the target aircraft.

[0027] The target reconstruction module is configured to establish three-dimensional model data of the target aircraft according to the surface coordinate point set.

[0028] The model sending module is configured to send the three-dimensional model data to a control center.

[0029] Optionally, the system comprises an image acquisition module and an image processing module;

[0030] The image acquisition module is configured to acquire at least one initial aircraft image by image acquisition equipment for each of the unknown aircrafts contained in the no-fly zone before the image acquisition module acquires at least one unknown aircraft image, wherein each of the initial aircraft images contains one unknown aircraft in the no-fly zone.

[0031] The image processing module is configured to perform Gaussian filtering processing on each of the initial aircraft images to obtain at least one of the unknown aircraft images.

[0032] In a second aspect, the embodiments of the present application provide an interference interception method for unknown aircrafts, applied to an interference interception system for unknown aircrafts, the system comprising an image acquisition module, a target identification module, a target control module and a target interception module, and the method comprising:

[0033] The image acquisition module acquires at least one unknown aircraft image, wherein each unknown aircraft image contains an unknown aircraft in the restricted area;

[0034] The target identification module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each unknown aircraft image, wherein the target aircraft is the unknown aircraft contained in the unknown aircraft image, and the passable aircraft is an aircraft having flight authority in the restricted area;

[0035] If the shape of the target aircraft is not the same as the shape of the passable aircraft, the target control module controls the target aircraft to fly from the restricted area to an interception area;

[0036] The target interception module controls at least one unmanned aerial vehicle for intercepting the target aircraft to fly to the interception area and perform an interception task of intercepting the target aircraft.

[0037] Optionally, after the target identification module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each unknown aircraft image, the method further comprises:

[0038] If the shape of the target aircraft is the same as the shape of the passable aircraft, the target control module controls the target aircraft to maintain the current flight trajectory;

[0039] The system further comprises a warning information sending module; after the target identification module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each unknown aircraft image, the method further comprises:

[0040] If the shape of the target aircraft is not the same as the shape of the passable aircraft, the warning information sending module sends preset warning information to a control center.

[0041] Optionally, the system further comprises a target positioning module and a trajectory generation module; after the image acquisition module acquires at least one unknown aircraft image, the method further comprises:

[0042] The target positioning module acquires the position coordinates of the target aircraft at at least one time point through a radar;

[0043] The trajectory generation module generates the actual flight trajectory of the target aircraft according to the position coordinates of the target aircraft at at least one time point.

[0044] Optionally, the system further comprises a trajectory prediction module and a flight trajectory sending module; after the trajectory generation module generates the actual flight trajectory of the target aircraft according to the position coordinates of the target aircraft at at least one time point, the method further comprises:

[0045] The trajectory prediction module inputs the actual flight trajectory of the target aircraft into the trained flight trajectory prediction model to determine the predicted flight trajectory of the target aircraft in a future preset time period;

[0046] The flight trajectory sending module sends the predicted flight trajectory of the target aircraft in the future preset time period to the control center.

[0047] Optionally, the target interception module controls at least one unmanned aerial vehicle for intercepting the target aircraft to fly to the interception area to target intercept the target aircraft, comprising:

[0048] The target interception module controls at least one of the unmanned aerial vehicles to fly to the interception area;

[0049] The target interception module determines a target unmanned aerial vehicle formation with the same identifier as the shape of the target aircraft from an unmanned aerial vehicle formation database according to the shape of the target aircraft;

[0050] The target interception module controls at least one of the unmanned aerial vehicles to target intercept the target aircraft in the target unmanned aerial vehicle formation.

[0051] Optionally, the system further comprises a target scanning module, a target reconstruction module and a model sending module; after the target interception module controls at least one unmanned aerial vehicle for intercepting the target aircraft to fly to the interception area to target intercept the target aircraft, the method further comprises:

[0052] The target scanning module scans the surface of the target aircraft by a three-dimensional scanner arranged on at least one of the unmanned aerial vehicles to obtain a set of surface coordinate points of the target aircraft;

[0053] The target reconstruction module establishes three-dimensional model data of the target aircraft according to the set of surface coordinate points;

[0054] The model sending module sends the three-dimensional model data to the control center.

[0055] Optionally, the system comprises an image acquisition module and an image processing module; before the image acquisition module acquires at least one unknown aircraft image, the method further comprises:

[0056] The image acquisition module acquires at least one initial aircraft image by respectively acquiring images of each unknown aircraft in the no-fly zone through an image acquisition device, wherein each initial aircraft image respectively contains one unknown aircraft in the no-fly zone.

[0057] The image processing module respectively performs Gaussian filtering processing on each initial aircraft image to obtain at least one unknown aircraft image.

[0058] The technical scheme provided in the application includes but is not limited to the following beneficial effects:

[0059] The image acquisition module is configured to acquire at least one unknown aircraft image, wherein each unknown aircraft image respectively contains one unknown aircraft in the no-fly zone; the target identification module is configured to determine whether the shape of a target aircraft is the same as the shape of a passable aircraft for each unknown aircraft image, wherein the target aircraft is the unknown aircraft contained in the unknown aircraft image, and the passable aircraft is an aircraft having flight permission in the no-fly zone; through the above modules, whether each aircraft has flight permission in the no-fly zone can be determined according to the shape of the aircraft in the no-fly zone.

[0060] The target control module is configured to control the target aircraft to fly from the no-fly zone to an interception area if the shape of the target aircraft is not the same as the shape of the passable aircraft; the target interception module is configured to control at least one unmanned aerial vehicle for intercepting the target aircraft to fly to the interception area and perform an interception task of intercepting the target aircraft; through the above modules, the aircraft without flight permission in the no-fly zone can be controlled to fly from the no-fly zone to the interception area, and the aircraft can be intercepted by the unmanned aerial vehicle.

[0061] The above system is adopted, and through mutual cooperation of the image acquisition module, the target identification module, the target control module and the target interception module, whether each aircraft has flight permission in the no-fly zone can be determined according to the shape of the aircraft in the no-fly zone, then the aircraft without flight permission in the no-fly zone can be controlled to fly from the no-fly zone to the interception area, and the aircraft can be intercepted by the unmanned aerial vehicle, so that the aircraft driving into the no-fly zone can be intercepted to avoid safety hazards.

[0062] In order to make the above-mentioned purposes, features and advantages of the application more obvious and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor based on these drawings.

[0064] Figure 1 The structural schematic diagram of the interference interception system for unknown aircraft provided by the embodiment one of the present application is shown.

[0065] Figure 2 The structural schematic diagram of the second interference interception system for unknown aircraft provided by the embodiment one of the present application is shown.

[0066] Figure 3 The structural schematic diagram of the third interference interception system for unknown aircraft provided by the embodiment one of the present application is shown.

[0067] Figure 4 The structural schematic diagram of the fourth interference interception system for unknown aircraft provided by the embodiment one of the present application is shown.

[0068] Figure 5 The structural schematic diagram of the fifth interference interception system for unknown aircraft provided by the embodiment one of the present application is shown.

[0069] Figure 6 The structural schematic diagram of the sixth interference interception system for unknown aircraft provided by the embodiment one of the present application is shown.

[0070] Figure 7 The flow chart of the interference interception method for unknown aircraft provided by the embodiment two of the present application is shown. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the following will combine the drawings in the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of the present application.

[0072] Embodiment one

[0073] For the purpose of making the present application more clearly understood, the following further Figure 1 The content described by referring to the structural schematic diagram of the interference interception system for unknown aircraft provided by the embodiment one of the present application is used to make a detailed description of the embodiment one of the present application.

[0074] Referring to Figure 1 , Figure 1 The structural schematic diagram of the interference interception system for unknown aircraft provided by the embodiment one of the present application is shown, wherein the system comprises an image acquisition module 101, a target identification module 102, a target control module 103 and a target interception module 104.

[0075] The image acquisition module is used to acquire at least one unknown aircraft image, wherein each unknown aircraft image contains an unknown aircraft in the no-fly zone.

[0076] Specifically, the image acquisition module acquires the image containing each unknown aircraft existing in the no-fly zone to obtain at least one unknown aircraft image.

[0077] The target identification module is used to judge whether the shape of a target aircraft is the same as the shape of a passable aircraft for each unknown aircraft image, wherein the target aircraft is the unknown aircraft contained in the unknown aircraft image, and the passable aircraft is an aircraft having flight permission in the no-fly zone.

[0078] Specifically, for each unknown aircraft image, the target identification module judges whether the shape of the unknown aircraft (i.e. the target aircraft) in the unknown aircraft image is the same as the shape of the passable aircraft. The passable aircraft is an aircraft having flight permission in the no-fly zone which is set in advance. Through this step, it can be judged whether the unknown aircraft contained in each unknown aircraft image has flight permission in the no-fly zone, and then the unknown aircraft is controlled (whether it needs to be intercepted) according to the judgment result.

[0079] The target control module is used to control the target aircraft to fly from the no-fly zone to the interception area if the shape of the target aircraft is not the same as the shape of the passable aircraft.

[0080] Specifically, if the shape of the target aircraft is not the same as the shape of the passable aircraft, it means that the target aircraft is not an aircraft having flight permission in the no-fly zone, so the target aircraft needs to be controlled and intercepted to drive it out of the no-fly zone.

[0081] The target interception module is configured to control at least one unmanned aerial vehicle for performing an interception task of intercepting the target aerial vehicle to fly to the interception area.

[0082] Specifically, at least one unmanned aerial vehicle for performing the interception task is pre-configured, the interception task is to intercept the target aerial vehicle, and the interception manner includes controlling the at least one unmanned aerial vehicle to fly in a target array, the target array is that each unmanned aerial vehicle is uniformly arranged on an interception circle with the same flight interval, the interception circle has the aerial vehicle as the center and has a preset interception distance as the radius, so as to surround the target aerial vehicle and achieve the target interception of the target aerial vehicle.

[0083] In a feasible implementation, referring to Figure 2 , Figure 2 A structure diagram of a second interference interception system for unknown aerial vehicles provided by an embodiment of the present application is shown, wherein the system further comprises a warning information sending module 201.

[0084] After the target identification module determines whether the shape of the target aerial vehicle is the same as the shape of the passable aerial vehicle for each unknown aerial vehicle image, the target control module is further configured to:

[0085] If the shape of the target aerial vehicle is the same as the shape of the passable aerial vehicle, the target aerial vehicle is controlled to keep the current flight trajectory.

[0086] Specifically, if the shape of the target aerial vehicle is the same as the shape of the passable aerial vehicle, it indicates that the target aerial vehicle is an aerial vehicle that has the permission to fly in the no-fly zone, and the target aerial vehicle does not need to be intercepted and intervened.

[0087] After the target identification module determines whether the shape of the target aerial vehicle is the same as the shape of the passable aerial vehicle for each unknown aerial vehicle image, the warning information sending module is configured to:

[0088] If the shape of the target aerial vehicle is not the same as the shape of the passable aerial vehicle, preset warning information is sent to the control center.

[0089] Specifically, when it is determined that the target aerial vehicle without the permission to fly in the no-fly zone appears in the no-fly zone, the warning information sending module sends the preset warning information to the control center, so that the control center can timely learn the situation, so that the control center can timely perform subsequent processing.

[0090] In a feasible implementation, referring to Figure 3 , Figure 3Fig. 3 shows a structural schematic diagram of a third interference interception system for unknown aircrafts according to the first embodiment of the present application, wherein the system further comprises a target positioning module 301 and a trajectory generation module 302.

[0091] The target positioning module is configured to acquire position coordinates of the target aircraft at at least one time point through radar after the image acquisition module acquires at least one image of the unknown aircraft.

[0092] Specifically, the radar is radio detection and ranging, which is used to detect, locate, track, image and identify targets by using the reflection or scattering of electromagnetic waves. The target positioning module acquires position coordinates of the target aircraft at at least one time point through radar.

[0093] The trajectory generation module is configured to generate an actual flight trajectory of the target aircraft according to the position coordinates of the target aircraft at at least one time point.

[0094] Specifically, the trajectory generation module marks the position coordinates of the target aircraft at at least one time point in a coordinate system to obtain a plurality of coordinate points, and then performs curve fitting on the plurality of coordinate points to obtain the actual flight trajectory of the target aircraft.

[0095] In a feasible implementation, referring to Figure 4 shown in the figure, Figure 4 Fig. 4 shows a structural schematic diagram of a fourth interference interception system for unknown aircrafts according to the first embodiment of the present application, wherein the system further comprises a trajectory prediction module 401 and a flight trajectory sending module 402.

[0096] The trajectory prediction module is configured to input the actual flight trajectory of the target aircraft into a trained flight trajectory prediction model to determine a predicted flight trajectory of the target aircraft in a future preset time period after the trajectory generation module generates the actual flight trajectory of the target aircraft according to the position coordinates of the target aircraft at at least one time point.

[0097] Specifically, a flight trajectory prediction model for predicting the flight trajectory of an aircraft is trained in advance. After the trajectory generation module generates the actual flight trajectory of the target aircraft according to the position coordinates of the target aircraft at at least one time point, the actual flight trajectory of the target aircraft is input into the flight trajectory prediction model to determine a predicted flight trajectory of the target aircraft in a future preset time period.

[0098] The flight trajectory sending module is configured to send the predicted flight trajectory of the target aircraft in the future preset time period to a control center.

[0099] Specifically, the flight trajectory sending module sends the predicted flight trajectory of the target aircraft in a future preset time period to the control center, so that the control center can control the target aircraft according to the predicted flight trajectory.

[0100] In a feasible implementation, the target interception module is specifically configured to:

[0101] Control at least one of the UAVs to fly to the interception region.

[0102] Specifically, since the target aircraft has been controlled to fly to the interception region in the previous step, at least one of the UAVs also needs to be controlled to fly to the interception region to achieve the interception of the target aircraft.

[0103] According to the shape of the target aircraft, a target UAV formation having the same identity as the shape of the target aircraft is determined from a UAV formation database.

[0104] Specifically, considering the influence of the airflow generated by the UAV flight on the aircraft in flight, the shapes of different aircrafts need to be intercepted by different UAV formations, and a UAV formation database is preconfigured, which stores the UAV formation having the same identity (representing a correlation) as the shape of each aircraft.

[0105] When the target aircraft needs to be intercepted, a target UAV formation having the same identity as the shape of the target aircraft is determined from the UAV formation database, and the UAVs arranged in the target UAV formation are used to intercept the target aircraft.

[0106] Control at least one of the UAVs to fly to the interception region.

[0107] In a feasible implementation, referring to Figure 5 shown, Figure 5 a fifth interference interception system for unknown aircraft provided by the embodiment one of the present application is shown, wherein the system further comprises a target scanning module 501, a target reconstruction module 502 and a model sending module 503.

[0108] The target scanning module is configured to scan the surface of the target aircraft by a three-dimensional scanner arranged on at least one of the UAVs to obtain a set of surface coordinate points of the target aircraft after the target aircraft is intercepted by the at least one UAV controlled by the target interception module.

[0109] The three-dimensional scanner is configured to create a point cloud of a geometric surface of an object, the point cloud being a set of coordinate points containing a plurality of coordinates of the surface of the object.

[0110] The target reconstruction module is configured to establish three-dimensional model data of the target aircraft according to the set of surface coordinate points.

[0111] The target reconstruction module is configured to reconstruct a three-dimensional model of the target aircraft according to the set of surface coordinate points to obtain the three-dimensional model data.

[0112] The model sending module is configured to send the three-dimensional model data to a control center.

[0113] In one possible implementation, referring to Figure 6 as shown in the drawings, Figure 6 Fig. 6 shows a structural schematic diagram of a sixth interference interception system for unknown aircrafts according to an embodiment of the present application, wherein the system comprises an image acquisition module 601 and an image processing module 602.

[0114] The image acquisition module is configured to acquire at least one initial aircraft image by image acquisition equipment for each unknown aircraft contained in the flight restricted area before the image acquisition module acquires at least one unknown aircraft image, wherein each initial aircraft image contains one unknown aircraft in the flight restricted area.

[0115] The image processing module is configured to perform Gaussian filtering on each initial aircraft image to obtain at least one unknown aircraft image.

[0116] Specifically, the image processing method can further include image denoising, image enhancement, etc. in addition to the Gaussian filtering, which are all image preprocessing methods.

[0117] In addition, the interference interception system for unknown aircraft provided by the application further comprises an identification and early warning module, a comprehensive positioning template, a destruction module, an airborne early warning and interference module, and a comprehensive control center. The identification and early warning module comprises an early warning unit, a multi-sensor unit, a signal data preprocessing unit, and a wireless communication unit, which are respectively carried on the unmanned aerial vehicle and arranged in the comprehensive control center. The comprehensive positioning template comprises a radar unit, a satellite unit, a tracking unit, and a wireless communication unit, which are arranged in the comprehensive control center. The destruction module comprises a signal receiving unit, a capturing unit, and an attacking unit, which are respectively carried on the unmanned aerial vehicle and arranged in the comprehensive control center. The airborne early warning and interference module comprises a control unit, a marking unit, a communication unit, an interference unit, a destruction unit, an identification unit, and a data processing unit, which are carried on the unmanned aerial vehicle. The comprehensive control center comprises a console, a radar, an electronic jammer, and an unmanned aerial vehicle warehouse, which are used for controlling the unmanned aerial vehicle, issuing control instructions, processing data, and monitoring unknown targets.

[0118] In the identification and early warning module, the identification and early warning unit is mainly used for monitoring targets in a delimited space or a moving space. Once a single or multiple targets illegally intrude, the early warning unit will issue a warning command, and the early warning system will immediately respond to track the target and send instructions to capture or destroy the target if necessary. The multi-sensor unit mainly collects information such as the position, height, speed, angle, and direction of the unknown target by using various sensors. The signal data preprocessing unit mainly preprocesses signal data by using various signal processing algorithms, including de-coherence, filtering, analysis, separation, and other mathematical operations. The wireless communication unit is mainly used for transmitting and receiving processed information or sending various control instructions and data information. The comprehensive positioning template comprises a radar unit, a satellite unit, a tracking unit, and a wireless communication unit. The radar unit is mainly used for positioning and identifying single or multiple targets that intrude into the delimited range, obtaining latitude and longitude information through various calculations, and transmitting the information to the control center or the unmanned aerial vehicle. The satellite unit is mainly used for recording the position information and trajectory information of the intruding target by continuously shooting the trajectory image of the target, predicting the movement direction of the target, and transmitting the above information to the control center or the unmanned aerial vehicle, so that the control center establishes a three-dimensional coordinate system. The tracking unit is mainly used for tracking and marking the number of the intruding target and sending the position, trajectory, and other information of the target corresponding to the number to the control center to establish an intrusion target coordinate system. The coordinate system inside the unmanned aerial vehicle immediately responds to the control center to realize multi-unmanned aerial vehicle cooperative early warning and interference. The interference unit is mainly used for deceiving the position and direction of single or multiple intruding targets or making them force-land or stop working. The wireless communication unit is mainly used for information exchange between the above units, modules, man-machine, and machine-machine.

[0119] In the destruction module, the signal receiving unit is mainly used for receiving information of unknown targets, unmanned aerial vehicles, control centers and the like, so as to realize information intercommunication between modules. The capturing unit is mainly used for capturing unknown targets according to control commands. The attacking unit is mainly used for destroying unknown targets according to control commands. The airborne early warning and jamming module comprises a control unit, a marking unit, a communication unit, a jamming unit, a destruction unit, an identification unit and a data processing unit. The control unit is mainly used for controlling the flight attitude and trajectory of the unmanned aerial vehicle, and simultaneously controlling multiple unmanned aerial vehicles in cooperation, so that multiple unmanned aerial vehicles form an early warning radar grid, and realize repeated search on a single grid to avoid unknown targets from avoiding early warning. The marking unit is mainly used for marking locations and targets and drawing a three-dimensional map to describe positions, so as to save target characteristics and formulate an early warning range. The communication unit is mainly used for transmitting information in a complex environment. The jamming unit and the destruction unit are mainly used for jamming and destroying targets according to needs. The identification unit is mainly used for drawing the shape of a target and objects carried by the target by means of a scanner, so as to judge the safety of the target. The unit can identify according to stored data information or directly identify. The data processing unit is mainly used for de-coherence, filtering, separation and the like of received data.

[0120] In the comprehensive control center, the console is mainly used for controlling unmanned aerial vehicles, demarcating early warning ranges and selecting early warning modes, and simultaneously controls a target object to realize visualization by means of three-dimensional modeling according to data information transmitted by satellites and radars. The console can control a single unmanned aerial vehicle or multiple unmanned aerial vehicles to perform fixed area interception early warning or mobile early warning. The console can divide an area into grids, and set early warning time of each grid or early warning times of unmanned aerial vehicles. The console is provided with an independent data management library, so as to store a large amount of satellite data and unmanned aerial vehicle data and the like. The radar is mainly used for identifying targets in cooperation with the satellite unit, and records the action trajectory and position information of the target. The electronic jammer is mainly used for sending jamming signals to deceive targets away from sensitive areas or make the targets force land. The unmanned aerial vehicle warehouse is mainly used for storing unmanned aerial vehicles, and realizes single unmanned aerial vehicle early warning or multiple unmanned aerial vehicle cooperative early warning, and realizes fixed area interception early warning and mobile area interception early warning according to the command of the console.

[0121] In the above interference interception system for unknown aircraft, the interception early warning function that can be realized by the system can be divided into two modes, one is a fixed interception early warning mode, and the other is a mobile interception early warning mode.

[0122] The fixed interception and early warning mode primarily relies on an identification and early warning module, a comprehensive positioning module, a destruction module, and a comprehensive control center. The fixed interception and early warning system divides the area centered on the control center into different grids, assigning each grid a data number. Simultaneously, the radar provides continuous early warning for each grid. Once one or more targets intrude into the area defined by a grid, the radar immediately responds and sends relevant information to the control center. At the same time, satellites and multi-sensor modules are mobilized to continuously track and photograph the grid, recording its direction of movement, speed, and trajectory, which is then transmitted to the control center. The control center uses this information to establish a coordinate system. Meanwhile, the data processing unit uses algorithms to analyze the target transmission signals into constant-mode signals, using the OC-ACMA algorithm (a constant-mode algorithm) to determine the number of signals, thereby estimating the number of intruding targets. The control center uses this information to determine whether the intruding targets are dangerous. Then, electronic jammers are used to deceive the targets in terms of direction and position, and single or multiple UAVs are dispatched in formation. These formations can arbitrarily change their formation as required, forming a three-dimensional land-air system to expand the capture or destruction range. Simultaneously, the system tracks the targets and decides whether to destroy or capture them. The airborne communication unit adjusts its direction and speed of motion in real time based on information from the control center and satellites, exhibiting automatic adjustment and adaptive effects.

[0123] Specific steps in the fixed interception and early warning mode:

[0124] Step one: The system is powered on. The operator selects the early warning mode for initialization settings, reads the pre-fetched commands, and begins operation according to the pre-stored commands. If none are available, the control center will divide the surrounding space into multiple grid blocks, using itself as the center point and labeling them to obtain the grid's coordinate number. Each grid block is independent and unique. The radar initializes, collecting signals from the designated area to obtain the geographic coordinates of the grid locations and matching them with the assigned coordinate numbers. Simultaneously, radar monitoring of distant areas is conducted to prepare for early warning. After initialization, the system proceeds to the next step.

[0125] Step two: During the early warning process, signal data is received in real time, and relatively high-fidelity signal data is obtained through operations such as filtering, noise reduction, extraction, and separation. If an unknown target is detected, the control center automatically mobilizes radar and satellites to extract targeted data and matches it with the cloud database. If it is a false alarm, the false alarm target is marked, its feature information is extracted and stored in the database, and the process proceeds to the next step.

[0126] Step three: If the target is dangerous, the control center deploys electronic jamming to "lure" it, forcing it to land or enter a pre-set trap zone. After rendering the dangerous target inoperable, its features and shape are extracted and stored for future reference. The system can then provide targeted warnings and interference based on the extracted features. If the target is moving rapidly and cannot be interfered with or "lured," the next step can proceed.

[0127] Step four: The control center controls multiple drones to form a coercion formation and a trap formation. The coercion formation tracks the target in real time and forces it to fly towards the designated trap. The trap formation is mainly equipped with capture and destruction devices to capture or destroy the coerced target. After the target is dealt with, it is brought back to the control center, and its characteristics are recorded and stored in the database.

[0128] The mobile interception and early warning mode primarily relies on an early warning module, a comprehensive positioning module, an airborne early warning and jamming module, and a comprehensive control center. Mobile interception and early warning can conduct continuous or periodic early warning monitoring within a range defined or memorized by the control center, or it can operate without a defined range, with UAVs using path optimization algorithms to achieve rapid early warning. The mobile early warning system uses a single UAV as the center, forming multiple circular search grids. Each grid undergoes multiple overlapping searches to avoid missing targets. If one or more targets intrude, the control center uses radar and satellites to collect information such as the target's direction and location, establishes a coordinate system for the target, and sends commands to nearby UAVs. Upon receiving the commands, nearby UAVs quickly proceed to the target. Upon reaching their destination, some UAVs lay traps, while others simultaneously identify, mark, and electronically jam the target, luring it into the trap zone for capture or destruction using the recording and destruction module. The UAV swarm is equipped with scanners that can scan targets from different angles, creating a 3D model of the object and transmitting it to the control center. The control center visualizes the 3D model and related data for further control operations.

[0129] Specific steps in the mobile interception and warning mode:

[0130] Step one: The system is powered on. The operator selects the warning mode for initialization settings, reads the pre-fetched commands, and begins operation according to the pre-stored commands. If none are available, the UAV will establish a coordinate system and draw a grid around itself, forming a warning formation. The grids drawn between UAVs should overlap as much as possible to improve positioning accuracy. Then, the control center selects the warning area and warning time, and the radar performs initialization. After initialization, the system proceeds to the next step.

[0131] Step two: During the early warning process, the drone formation can arbitrarily change its formation as required, receive signal data in real time, and obtain relatively high-fidelity signal data through filtering, noise reduction, extraction, and separation. If an unknown target is detected, the drone will send the early warning information to the control center and other nearby drones. After receiving the information, nearby drones will approach the target and perform data matching. The control center will automatically mobilize radar and satellites to perform targeted data extraction and match the information with the cloud database. If both sets of data determine that the target is safe, the target will be marked, and the early warning will continue. If the target is dangerous, proceed to the next step.

[0132] Step three involves handling dangerous targets. The drone swarm will coordinate according to commands from the control center, forming "coercion" and "trap" formations. Upon approaching the target, the drone swarm uses scanners to perform a comprehensive scan and construct a 3D model. This model data is then sent to the control center. Based on the visualized 3D model and related data, the control center operates the drone swarm, typically using the coercion formation to electronically interfere with the target, forcing it to descend or move into the "trap" formation. The "trap" formation is equipped with capture and destruction devices. When the target is unaffected by electronic interference, the "trap" formation will use the destruction devices to attack the target, rendering it inoperable. Simultaneously, the captured or destroyed targets' features are extracted, memorized, and transmitted back to the control center, where the data is stored.

[0133] The two aforementioned early warning tasks require communication during operation. However, during communication, the signal is not always perfectly accurate due to threshold effects, noise, and multipath effects, which introduce other signals. Therefore, this technology utilizes algorithms such as NLMS (Normalized Least Mean Square), OC-ACMA (a constant-mode algorithm), MTOEP (an estimation algorithm), and EPUMA (an estimation algorithm) to process the signal and ensure its accuracy and reliability. During the identification process, to store the target information, algorithms such as YOLOx (a target detection algorithm), five-frame difference method, and TDOA (a time difference-based positioning method) are used for target identification, tracking, and localization.

[0134] It's important to note that the NLMS algorithm used in the filtering algorithm is an improved version of the LMS (Least Mean Square) algorithm. In the LMS algorithm, the adjustment of the tap weights is proportional to the tap input vector. When the tap input vector is large, LMS encounters the problem of gradient noise amplification. To overcome this problem, the NLMS algorithm can be used. It's called NLMS because it normalizes the tap weight adjustment using the squared Euclidean norm of the tap input vector. Combined with deep learning algorithms, this algorithm can effectively and automatically learn the filtering coefficients, resulting in a more efficient filtering algorithm. This algorithm can learn autonomously and achieve filtering without external debugging.

[0135] The OC-ACMA algorithm is an improved version of the ACMA algorithm (analytical constant modulus algorithm). This algorithm can separate the constant modulus signal from the noisy signal and has high resolution. After the target intrusion, the data receiving unit receives the target signal and simultaneously converts the signal into a constant modulus signal. The algorithm can determine the number of intruding targets (i.e., the number of points where the singular value is significantly smaller than other singular values) by analyzing the constant modulus signal. This algorithm can achieve quantity estimation under different noise ratios and sampling numbers.

[0136] The combination of the MTOEP and EPUMA algorithms is a highly efficient DOA (Direction of Arrival) estimation algorithm. This algorithm can overcome the influence of the large number of coherent signals caused by multipath effects and the resulting decrease in matrix rank. Therefore, this algorithm can eliminate this problem, so that when estimating the direction of intrusion, it can be free from interference by other noise signals.

[0137] This system employs an improved YOLOx algorithm to detect and track the movement of intruding drones. The YOLOx network mainly consists of three parts: the CSPDarkNet network structure, the FPN network structure, and the YOLOxHead network structure. The CSPDarkNet network structure is the backbone feature extraction network of YOLOx, and its output consists of three effective feature layers. The FPN network structure is an enhanced feature extraction network of YOLOx, which fuses the three effective feature layers of different scales output by CSPDarkNet. The YOLOxHead network structure is the classifier and regressor of YOLOx. YOLOxHead uses the three feature maps output by FPN to determine whether a feature point corresponds to an object. While traditional YOLOHead implements classification and regression in a single convolution, YOLOxHead separates classification and regression and then integrates them at the end.

[0138] The TDOA (Time Difference of Arrival) algorithm is used in this system to fully utilize redundant TDOA information. To address the initial value estimation problem of the Newton-Raphson iterative solution, multiple sets of linear equations with lower dimension are constructed, avoiding the nonlinearity and sparsity issues of the original model. Then, a clustering algorithm is used to remove outliers in the linear equation solution process, and the initial value estimates are substituted into the iterative solution to obtain the positioning result. This algorithm can estimate the direction of the target's arrival, allowing a swarm of drones to approach and achieve real-time tracking. Furthermore, the TDOA algorithm can collect signal information using different arrays to obtain the target's two-dimensional angle of arrival, thus determining the target's direction.

[0139] The TDOA algorithm utilizes antenna arrays, which come in various types such as L-shaped and circular. The working principle of an antenna array can be viewed as the superposition of electromagnetic waves (electromagnetic fields). When several electromagnetic waves propagate to the same area, according to the superposition principle, they will undergo vector superposition. The superposition result depends not only on the amplitude of each electromagnetic wave but also on the phase difference between them within the encounter interval. Based on this, real-time localization and trajectory tracking of target sound sources can be achieved.

[0140] To improve tracking accuracy, this system uses a combination of the five-frame difference algorithm and the YOLOX algorithm. In the basic flowchart of the five-frame difference method for recognition, five consecutive target images f... t-2 (x, y), f t-1 (x, y), f t (x, y), f t+1 (x, y), f t+2 (x, y), where f t (x, y) is the intermediate frame, f t-1 (x, y) represents the frame at time t-1, f t-2 (x, y) represents the frame at time t-2, f t+1 (x, y) represents the frame at time t+1, f t+2 (x, y) represents the frame at time t+2, where t represents time. First, the five drone images are converted to grayscale. Then, median filtering is used to denoise the grayscale images. Drone videos contain a significant amount of noise during transmission due to various factors. Median filtering removes this noise, improving accuracy and recall. Threshold selection is crucial for the binarized grayscale drone images. A high threshold results in severe fragmentation of detected drones, while a low threshold leads to excessive noise in the detected images. After the control center and drone swarm mark and identify the target, the data is stored in a database. Subsequently, when processing the same target, the drone swarm will operate according to pre-set instructions.

[0141] The drones used provide computer applications for autonomous flight path planning, aerial photography, 2D orthophoto reconstruction, and 3D model reconstruction. This helps industry users comprehensively improve the efficiency of aerial surveying and mapping, transforming real-world scenarios into digital assets. Model Reconstruction: Import original aerial images and output high-precision 2D orthophotos and realistic 3D models. Real-time Reconstruction: Generate 2D orthophotos or 3D models in real time during flight, enabling on-the-fly mapping. LiDAR Data Processing: One-click output of high-precision true-color point cloud results. Detailed Inspection: Set shooting targets based on models or point clouds, automatically generate shooting routes, and automate inspection processes. Model Application: Measure various key data such as coordinates, distance, area, and volume of target objects, and perform operations such as naming and exporting the measurement results.

[0142] The recording and detection device used is a Ravis event detection dual-light integrated machine. This product integrates a high-precision millimeter-wave radar, a 9-megapixel global exposure CMOS (Complementary Metal Oxide Semiconductor) camera, and an online temperature measurement thermal imager. The online temperature measurement thermal imager can perceive changes in scene and target temperature in real time; the high-precision millimeter-wave radar can achieve all-weather multi-target detection and accurately acquire speed and position information.

[0143] Storage devices enable unified storage: providing block and file services within the same storage system, simplifying data center architecture, reducing operation and maintenance costs, and flexibly responding to different business needs. Multiple protocols are unified: supporting protocols such as FC (Fibre Channel), iSCSI (Internet Small Computer System Interface), CIFS (Common Internet File System), NFS (Network File System), and FTP (File Transfer Protocol). High availability: adopting a fully redundant architecture, full modularity, redundant caching, and dual-active controller design. High scalability: dual controllers support up to 600 hard drives. It supports horizontal expansion to 8 controllers, with the system expandable up to 1TB of memory. Intelligent local replication includes three local data protection functions: intelligent cloning, intelligent snapshots, and intelligent backup. It can meet the needs of application testing, development, analysis, and backup, effectively saving storage space and reducing investment costs. Intelligent volume mirroring creates a mirror of the volume mapped to the host, saving two identical copies of the data in two separate storage pools. When one copy of the data is corrupted, it provides uninterrupted application IO (Input / Output) access. Intelligent tiering allows online migration of hot data between different storage media, achieving a balance between storage cost and performance, and improving customer ROI. Intelligent heterogeneous virtualization can take over third-party storage resources through its own heterogeneous storage virtualization technology, forming a unified virtual resource pool and providing data protection and migration services between storage systems.

[0144] The visualization data platform utilizes an intelligent large-screen management platform, which possesses capabilities for large-screen display and control, information dissemination, voice control, central control management, and operator dispatch. Based on large-screen content playback and display control, it enables large-screen portals and multi-screen interaction; in conjunction with a voice analysis server, it achieves intelligent voice dispatching for the large screen; combined with information dissemination, it allows for the display of published content on the screen, and also enables control of the large-screen content display via tablets. It meets the large-screen usage needs of users in command centers, exhibition centers, data centers, indoor and outdoor locations.

[0145] The creation of a 3D model of the target, fully displayed in the control center, utilizes a VR (Virtual Reality) panoramic application platform. This platform, centered on virtual reality (VR) technology, provides an immersive interactive experience that blends the virtual and real worlds, facilitating the development of industry business applications. By combining front-end multi-dimensional sensing devices and business data, the platform projects real-world elements such as people, vehicles, events, and objects into a virtual scene, enabling scene roaming, marking and plotting, video projection, and a series of interconnected applications. This provides users with a new mode for understanding the sensing data within a region and supporting management decision-making.

[0146] Example 2

[0147] See Figure 7 As shown, Figure 7 The flowchart illustrates a method for intercepting interference against an unknown aircraft according to Embodiment 2 of the present invention. The method is applied to an interference interception system for unknown aircraft, which includes an image acquisition module, a target recognition module, a target control module, and a target interception module. The method includes steps S701 to S704:

[0148] S701: The image acquisition module acquires at least one image of an unknown aircraft, wherein each image of the unknown aircraft contains an unknown aircraft in a no-fly zone;

[0149] S702: For each image of an unknown aircraft, the target recognition module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft, wherein the target aircraft is the unknown aircraft contained in the image of the unknown aircraft, and the passable aircraft is the aircraft that has flight rights in the no-fly zone;

[0150] S703: If the shape of the target aircraft is different from the shape of the passable aircraft, the target control module controls the target aircraft to fly from the no-fly zone to the interception zone;

[0151] S704: The target interception module controls at least one UAV used to intercept the target aircraft to fly to the interception area and performs the interception task of intercepting the target aircraft.

[0152] In one feasible implementation, after the target recognition module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each unknown aircraft image, the method further includes:

[0153] If the shape of the target aircraft is the same as that of the passable aircraft, the target control module controls the target aircraft to maintain its current flight trajectory.

[0154] The system further includes a warning information sending module; after the target recognition module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each image of the unknown aircraft, the method further includes:

[0155] If the shape of the target aircraft is different from that of the passable aircraft, the warning information sending module will send the preset warning information to the control center.

[0156] In one feasible implementation, the system further includes a target localization module and a trajectory generation module; after the image acquisition module acquires at least one image of an unknown aircraft, the method further includes:

[0157] The target positioning module obtains the position coordinates of the target aircraft at at least one point in time using radar.

[0158] The trajectory generation module generates the actual flight trajectory of the target aircraft based on the position coordinates of the target aircraft at at least one point in time.

[0159] In one feasible implementation, the system further includes a trajectory prediction module and a flight trajectory transmission module; after the trajectory generation module generates the actual flight trajectory of the target aircraft based on the position coordinates of the target aircraft at at least one time point, the method further includes:

[0160] The trajectory prediction module inputs the actual flight trajectory of the target aircraft into the trained flight trajectory prediction model to determine the predicted flight trajectory of the target aircraft within a preset time period in the future;

[0161] The flight trajectory transmission module sends the predicted flight trajectory of the target aircraft within a preset time period to the control center.

[0162] In one feasible implementation, the target interception module controls at least one UAV used for intercepting the target aircraft to fly to the interception area to intercept the target aircraft, including:

[0163] The target interception module controls at least one of the drones to fly to the interception area;

[0164] The target interception module determines the target drone formation with the same identifier as the target drone from the drone formation database based on the shape of the target drone.

[0165] The target interception module controls at least one of the UAVs to intercept the target aircraft in the target UAV formation.

[0166] In one feasible implementation, the system further includes a target scanning module, a target reconstruction module, and a model transmission module; after the target interception module controls at least one UAV used for intercepting the target aircraft to fly to the interception area to intercept the target aircraft, the method further includes:

[0167] The target scanning module obtains a set of surface coordinate points of the target aircraft by scanning the surface of the target aircraft with a three-dimensional scanner installed on at least one of the UAVs;

[0168] The target reconstruction module establishes three-dimensional model data of the target aircraft based on the set of surface coordinate points;

[0169] The model sending module sends the 3D model data to the control center.

[0170] In one feasible implementation, the system includes an image acquisition module and an image processing module; before the image acquisition module acquires at least one image of an unknown aircraft, the method further includes:

[0171] The image acquisition module acquires images of each unknown aircraft contained in the no-fly zone using an image acquisition device to obtain at least one initial aircraft image, wherein each initial aircraft image contains an unknown aircraft in the no-fly zone.

[0172] The image processing module performs Gaussian filtering on each of the initial aircraft images to obtain at least one image of the unknown aircraft.

[0173] The interference interception system for unknown aircraft provided in this embodiment of the invention can be specific hardware on a device or software or firmware installed on the device. The system provided in this embodiment of the invention has the same implementation principle and technical effects as the aforementioned method embodiments. For the sake of brevity, any parts not mentioned in the system embodiments can be referred to the corresponding content in the aforementioned method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the above method embodiments, and will not be repeated here.

[0174] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. The system embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some communication interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0175] 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.

[0176] In addition, the functional units in the embodiments provided by the present invention 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.

[0177] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0178] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0179] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. All should be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An interference interception system for unidentified flying objects, characterized in that, The system includes an image acquisition module, a target recognition module, a target control module, a target interception module, a target scanning module, a target reconstruction module, a model transmission module, a target localization module, a trajectory generation module, a trajectory prediction module, and a flight trajectory transmission module. The image acquisition module is used to acquire at least one image of an unidentified flying object, wherein each image of the unidentified flying object contains an unidentified flying object in a no-fly zone. The target recognition module is used to determine whether the shape of the target aircraft is the same as the shape of the passable aircraft for each image of the unknown aircraft, wherein the target aircraft is the unknown aircraft contained in the image of the unknown aircraft, and the passable aircraft is the aircraft that has flight rights in the no-fly zone; The target control module is used to control the target aircraft to fly from the no-fly zone to the interception zone if the shape of the target aircraft is different from the shape of the passable aircraft. The target interception module is used to control at least one UAV used to intercept the target aircraft to fly to the interception area and perform the interception task of intercepting the target aircraft. The target scanning module is used to scan the surface of the target aircraft by a three-dimensional scanner mounted on at least one of the drones after the target interception module controls at least one drone to intercept the target aircraft and fly to the interception area to intercept the target aircraft, thereby obtaining a set of surface coordinate points of the target aircraft. The target reconstruction module is used to establish three-dimensional model data of the target aircraft based on the set of surface coordinate points. The model sending module is used to send the 3D model data to the control center; The target positioning module is used to obtain the position coordinates of the target aircraft at at least one time point by radar after the image acquisition module acquires at least one image of the unknown aircraft; The trajectory generation module is used to generate the actual flight trajectory of the target aircraft based on the position coordinates of the target aircraft at at least one point in time. The trajectory prediction module is used to input the actual flight trajectory of the target aircraft into the trained flight trajectory prediction model after the trajectory generation module generates the actual flight trajectory of the target aircraft based on the position coordinates of the target aircraft at at least one time point to determine the predicted flight trajectory of the target aircraft in the future preset time period. The flight trajectory transmission module is used to send the predicted flight trajectory of the target aircraft within a preset time period to the control center.

2. The interference interception system for unknown aircraft according to claim 1, characterized in that, The interference interception system for unknown aircraft also includes a warning information transmission module; After the target recognition module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each image of the unknown aircraft, the target control module is further configured to: If the shape of the target aircraft is the same as that of the passable aircraft, then control the target aircraft to maintain its current flight trajectory. After the target recognition module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each image of the unknown aircraft, the warning information sending module is used to: If the shape of the target aircraft is different from that of the passable aircraft, a preset warning message will be sent to the control center.

3. The interference interception system for unknown aircraft according to claim 1, characterized in that, When the target interception module controls at least one UAV used for intercepting the target aircraft to fly to the interception area to intercept the target aircraft, it is specifically used for: Control at least one of the drones to fly to the interception area; Based on the shape of the target aircraft, a target drone formation with the same identifier as the target aircraft is determined from the drone formation database; Control at least one of the drones to intercept the target aircraft in the target drone formation.

4. The interference interception system for unknown aircraft according to claim 1, characterized in that, The interference interception system for unidentified flying objects includes an image acquisition module and an image processing module; The image acquisition module is used to acquire at least one initial aircraft image by using an image acquisition device to acquire images of each of the unknown aircraft contained in the no-fly zone before the image acquisition module acquires at least one image of the unknown aircraft. Each initial aircraft image contains an unknown aircraft in the no-fly zone. The image processing module is used to perform Gaussian filtering on each of the initial aircraft images to obtain at least one image of the unknown aircraft.

5. A method for intercepting interference from unknown aircraft, characterized in that, An interference interception system for unidentified flying objects (UFOs) is provided, comprising an image acquisition module, a target recognition module, a target control module, a target interception module, a target scanning module, a target reconstruction module, a model transmission module, a target localization module, a trajectory generation module, a trajectory prediction module, and a flight trajectory transmission module. The interference interception method for UFOs includes: The image acquisition module acquires at least one image of an unidentified flying object, wherein each image of the unidentified flying object contains an unidentified flying object in a no-fly zone; For each image of an unknown aircraft, the target recognition module determines whether the shape of the target aircraft is the same as the shape of a passable aircraft. The target aircraft is the unknown aircraft contained in the image of the unknown aircraft, and the passable aircraft is an aircraft that has flight rights in the no-fly zone. If the shape of the target aircraft is different from that of the passable aircraft, the target control module controls the target aircraft to fly from the no-fly zone to the interception zone; The target interception module controls at least one UAV used to intercept the target aircraft to fly to the interception area and executes the interception task of intercepting the target aircraft. After the target interception module controls at least one UAV to intercept the target aircraft to fly to the interception area and intercept the target aircraft, the target scanning module scans the surface of the target aircraft using a 3D scanner mounted on at least one of the UAVs to obtain a set of surface coordinate points of the target aircraft. The target reconstruction module establishes three-dimensional model data of the target aircraft based on the set of surface coordinate points; The model sending module sends the 3D model data to the control center; After the image acquisition module acquires at least one image of an unknown aircraft, the method further includes: The target positioning module obtains the position coordinates of the target aircraft at at least one point in time using radar. The trajectory generation module generates the actual flight trajectory of the target aircraft based on the position coordinates of the target aircraft at at least one point in time. The trajectory prediction module inputs the actual flight trajectory of the target aircraft into the trained flight trajectory prediction model to determine the predicted flight trajectory of the target aircraft within a preset time period in the future; The flight trajectory transmission module sends the predicted flight trajectory of the target aircraft within a preset time period to the control center.

6. The interference interception method for unknown aircraft according to claim 5, characterized in that, After the target identification module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each image of the unknown aircraft, the interference interception method for the unknown aircraft further includes: If the shape of the target aircraft is the same as that of the passable aircraft, the target control module controls the target aircraft to maintain its current flight trajectory. The system further includes a warning information sending module; after the target identification module determines whether the shape of the target aircraft is the same as the shape of the passable aircraft for each image of the unknown aircraft, the interference interception method for the unknown aircraft further includes: If the shape of the target aircraft is different from that of the passable aircraft, the warning information sending module will send the preset warning information to the control center.

Images