CN118276605A - Unmanned aerial vehicle interception method and device, electronic equipment and storage medium - Google Patents

Abstract

The invention provides an unmanned aerial vehicle interception method, an unmanned aerial vehicle interception device, electronic equipment and a storage medium, which are applied to an unmanned aerial vehicle interception system, and an optimal cruising path is determined through a path planning algorithm to control the unmanned aerial vehicle interception system to automatically cruise; monitoring an obstacle appearing in front of the system in real time, and avoiding the obstacle according to a preset obstacle avoidance algorithm; acquiring an airspace image corresponding to a target cruising area in real time, inputting the airspace image into a preset target detection model, if the unmanned aerial vehicle is determined to exist, inputting the unmanned aerial vehicle image into a preset target tracking model, determining a flight track corresponding to the unmanned aerial vehicle, and adjusting a aiming angle corresponding to the interception equipment; according to a preset interception signal selection rule corresponding to the number of detected unmanned aerial vehicles, an unmanned aerial vehicle interception signal matched with the rule is sent along an aiming angle. The automatic cruising of unmanned aerial vehicle interception system can be realized, and when an invasive unmanned aerial vehicle is found, the invasive unmanned aerial vehicle is accurately and effectively intercepted by utilizing various interception mode combinations, so that the safety of a large-scale airspace is ensured.

Description

A drone interception method, device, electronic device and storage medium

Technical Field

The present disclosure relates to the technical field of flying object interception, and in particular to a method, device, electronic device and storage medium for intercepting a drone.

Background technique

In recent years, with the continuous development of technologies such as sensing, image transmission, and artificial intelligence, drones have gradually become a hot area in intelligent technology. With the continuous development and maturity of drone technology, it has been widely used in various fields due to its advantages such as small size, light weight, strong maneuverability, and good concealment. The rapid development of civil drones is promoting the transformation and upgrading of traditional industries. Drones can implement drone operations according to the needs and work standards of various industries, replacing traditional operating methods, which can not only effectively reduce manpower and material costs, but also improve work efficiency and quality, and reduce environmental pollution. At present, drones have demonstrated good technical and economic effects in the fields of aerial photography, agricultural plant protection, disaster relief, terrain exploration, urban management, geographic information surveying and mapping, etc.

However, the rapid development of the drone industry has brought convenience to people's lives, but it has also brought many safety hazards. In recent years, there have been frequent incidents of drone "illegal flights" disrupting aviation order and infringing on citizens' privacy. However, since drones are small aerial devices, they pose great difficulties for supervision. The existing anti-drone interception system is mainly a fixed-point passive interception method. The interception equipment has poor maneuverability, limited interception range, and a single interception method. The interception efficiency is low and cannot meet the effective protection of a large area. As a result, in large areas where drones need to be intercepted, the safety of the target airspace can only be guaranteed by increasing the number of anti-drone interception equipment, which seriously increases the cost of anti-drone.

Summary of the invention

The disclosed embodiments at least provide a method, device, electronic device and storage medium for intercepting a drone. By establishing a path planning mathematical model, a path planning algorithm is used to find the optimal cruising path, and an obstacle avoidance algorithm is used to realize automatic cruising of the drone interception system. When an invading drone is found, a combination of multiple interception methods is used to accurately and effectively intercept the invading drone, thereby ensuring the safety of a large range of airspace.

The present disclosure provides a method for intercepting a drone, which is applied to a drone interception system. The method includes:

Obtaining a target cruising area, and determining an optimal cruising path according to a preset cruising point through a path planning algorithm set in a preset path planning model to control the automatic cruising of the UAV interception system;

During the cruise, the obstacles appearing in front of the UAV interception system are monitored in real time, and obstacles are avoided according to a preset obstacle avoidance algorithm;

Collecting airspace images corresponding to the target cruising area in real time, inputting the airspace images into a preset target detection model to determine whether there is an invading drone, and if so, inputting the detected drone images into a preset target tracking model to determine the flight trajectory corresponding to the invading drone;

According to the flight trajectory, the aiming angle corresponding to the interception device carried in the UAV interception system is adjusted; the number of detected UAVs is determined, and according to the preset interception signal selection rule corresponding to the number of UAVs, a UAV interception signal matching the preset interception signal selection rule is sent along the aiming angle.

In an optional implementation manner, controlling the drone interception system to automatically cruise specifically includes:

Controlling the image acquisition device carried by the UAV interception system to acquire the current road image in real time, and performing preprocessing including graying, denoising and distortion correction on the road image;

Extracting road boundary features contained in the preprocessed road image;

The road boundary features are matched and compared with a preset road template, and if they match, the current position is determined to be a feasible road;

If there is no match, the current position is determined to be an infeasible road, and the image acquisition device is controlled to rotate a preset angle, and the above road image acquisition steps are repeated until a feasible road is detected.

In an optional implementation, real-time monitoring of obstacles appearing in front of the drone interception system specifically includes:

Controlling the ultrasonic sensor carried by the drone interception system to monitor obstacles appearing ahead in real time, and controlling the drone interception system to stop moving when an obstacle is detected;

Controlling the laser rangefinder carried by the UAV interception system to emit two ranging laser beams toward the obstacle in sequence within a preset time interval, and respectively determining the obstacle distance information corresponding to the two ranging laser beams;

Determine the motion state of the obstacle relative to the drone interception system based on the distance information;

When the motion state is a moving state toward, the UAV interception system is controlled to retreat.

In an optional implementation, avoiding obstacles according to a preset obstacle avoidance algorithm specifically includes:

Determining the position information of the obstacle relative to the drone interception system;

Controlling the rotation speed of the driving wheel on the side close to the obstacle to drive the UAV interception system to be greater than the rotation speed of the driving wheel on the other side, so as to make the UAV interception system turn;

Real-time monitoring of whether there are still obstacles within the field of view of the drone interception system;

If yes, maintain the steering state of the drone interception system until there are no obstacles within the field of view;

If not, the driving wheels on both sides of the drone interception system are adjusted to rotate synchronously so that the drone interception system resumes straight-line travel.

In an optional implementation, the flight trajectory corresponding to the intruding drone is determined based on the following steps:

Inputting the drone image output by the preset target detection model into the preset target tracking model in real time;

In chronological order, for each frame of the drone image, a Kalman filter prediction is performed on the previous frame of the drone image, and the drone image of that frame is updated according to the prediction result. At the same time, the motion features and appearance features retained when the target tracking model is initialized are matched to determine the flight trajectory.

In an optional implementation manner, the preset interception signal selection rule specifically includes:

When the number of the drone is one, controlling the laser interception device carried by the drone interception system to work and send a high-energy laser beam as the drone interception signal;

When the number of the drones is multiple and less than a preset number threshold, the laser interception device and the navigation decoy device carried by the drone interception system are controlled to work, and a high-energy laser beam and a navigation decoy signal are sent as the drone interception signal at the same time;

When the number of the drones is greater than a preset threshold, the laser interception equipment, navigation decoy equipment and multi-band radio jamming equipment carried in the drone interception system are controlled to operate, and high-energy laser beams, navigation decoy signals and communication frequency jamming signals are sent as the drone interception signals.

The present disclosure also provides a drone interception device, including:

A path planning module is used to obtain a target cruising area, determine an optimal cruising path according to a preset cruising point through a path planning algorithm set in a preset path planning model, and control the automatic cruising of the UAV interception system;

An obstacle avoidance module is used to monitor obstacles appearing in front of the UAV interception system in real time during cruising, and avoid obstacles according to a preset obstacle avoidance algorithm;

A target detection and tracking module is used to collect airspace images corresponding to the target cruising area in real time, input the airspace images into a preset target detection model, determine whether there is an invading drone, and if so, input the detected drone image into a preset target tracking model to determine the flight trajectory corresponding to the invading drone;

The interception module is used to adjust the aiming angle corresponding to the interception device carried in the UAV interception system according to the flight trajectory; determine the number of detected UAVs, and send a UAV interception signal matching the preset interception signal selection rule along the aiming angle according to the preset interception signal selection rule corresponding to the number of UAVs.

An embodiment of the present disclosure also provides an electronic device, including: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the above-mentioned drone interception method or steps in any possible implementation of the above-mentioned drone interception method are performed.

The embodiments of the present disclosure also provide a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program executes the above-mentioned drone interception method, or the steps in any possible implementation of the above-mentioned drone interception method.

The embodiments of the present disclosure also provide a computer program product, including a computer program/instruction, which, when executed by a processor, implements the above-mentioned drone interception method, or the steps in any possible implementation of the above-mentioned drone interception method.

The disclosed embodiment provides a method, device, electronic device and storage medium for intercepting unmanned aerial vehicles, which are applied to an unmanned aerial vehicle interception system, obtain a target cruising area, determine the optimal cruising path to control the automatic cruising of the unmanned aerial vehicle interception system according to the preset cruising point through the path planning algorithm set in the preset path planning model; during the cruising process, monitor the obstacles appearing in front of the unmanned aerial vehicle interception system in real time, and avoid the obstacles according to the preset obstacle avoidance algorithm; collect the airspace image corresponding to the target cruising area in real time, input the airspace image into the preset target detection model, determine whether there is an intruding unmanned aerial vehicle, and if there is, input the detected unmanned aerial vehicle image into the preset target tracking model to determine the flight trajectory corresponding to the intruding unmanned aerial vehicle; according to the flight trajectory, adjust the aiming angle corresponding to the interception device carried in the unmanned aerial vehicle interception system; determine the number of detected unmanned aerial vehicles, and send the unmanned aerial vehicle interception signal matching the preset interception signal selection rule along the aiming angle according to the preset interception signal selection rule corresponding to the number of unmanned aerial vehicles. By establishing a path planning mathematical model, using the path planning algorithm to find the optimal path for cruising, cooperating with the obstacle avoidance algorithm to realize the automatic cruising of the unmanned aerial vehicle interception system, and when an intruding unmanned aerial vehicle is found, a combination of multiple interception methods is used to accurately and effectively intercept the intruding unmanned aerial vehicle, so as to ensure the safety of a large range of airspace.

In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments. The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used together with the specification to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can also be obtained based on these drawings without creative work.

FIG1 shows a schematic diagram of a drone interception system provided by an embodiment of the present disclosure;

FIG2 shows a flow chart of a method for intercepting a drone provided by an embodiment of the present disclosure;

FIG3 shows a schematic diagram of a drone interception device provided by an embodiment of the present disclosure;

FIG. 4 shows a schematic diagram of an electronic device provided by an embodiment of the present disclosure.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the present disclosure for protection, but merely represents the selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present disclosure.

It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not require further definition and explanation in the subsequent drawings.

The term "and/or" herein only describes an association relationship, indicating that three relationships may exist. For example, A and/or B may represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set consisting of A, B, and C.

According to research, in recent years, there have been frequent incidents of drones flying illegally, disrupting aviation order and infringing on citizens' privacy. However, since drones are small aerial devices, they pose great difficulties for supervision. The existing anti-drone interception system is mainly a fixed-point passive interception method. The interception equipment has poor maneuverability, limited interception range, and a single interception method. The interception efficiency is low and cannot meet the requirements of effective protection of large areas. As a result, in large areas where drones need to be intercepted, the safety of the target airspace can only be guaranteed by increasing the number of anti-drone interception equipment, which seriously increases the cost of anti-drone.

Based on the above research, the present disclosure provides a method, device, electronic device and storage medium for intercepting unmanned aerial vehicles, which are applied to unmanned aerial vehicle interception systems, obtain target cruising areas, and determine the optimal cruising path to control the unmanned aerial vehicle interception system to cruise automatically according to the preset cruising points through the path planning algorithm set in the preset path planning model; during the cruising process, monitor the obstacles appearing in front of the unmanned aerial vehicle interception system in real time, and avoid the obstacles according to the preset obstacle avoidance algorithm; collect the airspace image corresponding to the target cruising area in real time, input the airspace image into the preset target detection model, determine whether there is an invading unmanned aerial vehicle, and if there is, input the detected unmanned aerial vehicle image into the preset target tracking model to determine the flight trajectory corresponding to the invading unmanned aerial vehicle; according to the flight trajectory, adjust the aiming angle corresponding to the interception device carried in the unmanned aerial vehicle interception system; determine the number of detected unmanned aerial vehicles, and send the unmanned aerial vehicle interception signal matching the preset interception signal selection rule along the aiming angle according to the preset interception signal selection rule corresponding to the number of unmanned aerial vehicles. By establishing a path planning mathematical model, using the path planning algorithm to find the optimal path for cruising, cooperating with the obstacle avoidance algorithm to realize the automatic cruising of the unmanned aerial vehicle interception system, and when an invading unmanned aerial vehicle is found, a combination of multiple interception methods is used to accurately and effectively intercept the invading unmanned aerial vehicle, so as to ensure the safety of a large range of airspace.

To facilitate understanding of this embodiment, the application object of a drone interception method disclosed in the embodiment of the present disclosure is first introduced in detail. The drone interception method provided in the embodiment of the present disclosure can be applied to a drone interception system. See Figure 1, which is a schematic diagram of a drone interception system provided in the embodiment of the present disclosure. As shown in Figure 1, the drone interception system includes an automatic cruise module, a drone detection and tracking module, a drone interception module, a control center, an energy supply module, and a communication module.

Specifically, the automatic cruise module includes a navigation unit, an obstacle avoidance unit, a power unit, and an automatic cruise control unit, wherein the navigation unit, the obstacle avoidance unit, and the power unit are electrically connected to the automatic cruise control unit in sequence, and the automatic cruise control unit communicates with the control center through the communication module to realize the control of the automatic cruise module by the control center.

Here, the navigation unit includes a path planning device and a positioning device; the obstacle avoidance unit includes a laser rangefinder, an ultrasonic sensor, and a CCD industrial camera, and each part of the obstacle avoidance unit is controlled by the automatic cruise control unit; the power unit includes a driving wheel, a guide wheel, and a driving motor.

Furthermore, the UAV detection and tracking module includes a target detection unit, a target tracking unit, a gimbal unit, and a detection and tracking control unit, wherein the target detection unit, the target tracking unit, and the gimbal unit are electrically connected to the detection and tracking control unit in sequence, and the detection and tracking control unit is communicated with the control center through the communication module to realize the control of the UAV detection and tracking module by the control center.

Furthermore, the drone interception module includes a GPS navigation decoy device, a multi-band radio jammer, a laser interception device, and an interception module control unit.

Furthermore, the control center includes a control unit, a data processing unit, and a display unit, which are used to process the data transmitted to the control center by the automatic cruise module, the drone detection and tracking module, and the drone interception module, and then control the automatic cruise module, the drone detection and tracking module, and the drone interception module, as well as control the start and stop of the entire system.

Here, the data processing module is used to process the data information collected by the automatic cruise module, drone detection and tracking module, and drone interception module and transmitted to the control center, so as to realize the processing, storage, and deletion of the data information; the display module is used to display the processed data information, and to display the working status of each module and the situation of the protected airspace in real time.

Secondly, a method for intercepting a drone disclosed in an embodiment of the present disclosure is introduced in detail. The execution subject of the method for intercepting a drone provided in an embodiment of the present disclosure is generally a computer device with certain computing capabilities, and the computer device includes, for example: a terminal device or a server or other processing device, and the terminal device can be a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. In some possible implementations, the method for intercepting a drone can be implemented by a processor calling a computer-readable instruction stored in a memory.

Referring to FIG. 2 , there is shown a flow chart of a method for intercepting a drone provided by an embodiment of the present disclosure. The method includes steps S201 to S204, wherein:

S201, obtaining a target cruising area, and determining an optimal cruising path according to a preset cruising point by using a path planning algorithm set in a preset path planning model to control the automatic cruising of the UAV interception system.

In the specific implementation, the airspace range that the drone interception system needs to protect is first obtained, and then the target cruising area within the airspace range is determined. In the drone interception system, the path planning device in the navigation unit included in the automatic cruise module uses a path planning algorithm to find the optimal path for the system cruise based on the set cruising area through a path planning mathematical model, and takes factors such as terrain and obstacles into consideration during the path planning process. At the same time, the control positioning device determines the current position and target position of the drone interception system in real time.

Here, the positioning device can use the Global Positioning System (GPS) and inertial navigation technology to determine the latitude, longitude and altitude of the system in real time.

As a possible implementation, the objective function of the cruising distance of path planning can be expressed as follows:

Among them, n represents the number of preset cruise points that the drone interception system needs to pass through; _dij represents the distance between the i-th cruise point and the j-th cruise point in the motion trajectory of the drone interception system, _dij ≥0 and _dii =0; D represents the shortest cruise distance of path planning; the value range of the variable _xij is: if the cruise point (i, j) is on the required cruise path, then _xij =1, otherwise _xij =0.

It should be noted that the above objective function also needs to follow the following rule constraints: any cruise point in the cruise path of the drone interception system can only have one path in and out during a cruise; there is no sub-loop in the generated path to ensure that each cruise point will not be passed twice during a cruise, thereby improving the cruise efficiency.

Furthermore, the automatic cruise control method of the drone interception system can be implemented through the following steps 1 to 4:

Step 1: Control the image acquisition device carried by the UAV interception system to obtain the current road image in real time, and perform preprocessing including graying, denoising and distortion correction on the road image.

Step 2: extracting road boundary features contained in the preprocessed road image.

Step 3: Match and compare the road boundary features with a preset road template. If they match, the current location is determined to be a feasible road.

Step 4: If there is no match, the current position is determined to be an infeasible road, and the image acquisition device is controlled to rotate a preset angle, and the above road image acquisition steps are repeated until a feasible road is detected.

In the specific implementation, the road picture is obtained by controlling the CCD industrial camera. The road edge is dark-colored road signs, and the middle road surface is light-colored. The current road graphics can be obtained by graying, denoising, distortion correction and threshold segmentation of the captured pictures. The automatic cruise control unit processes the road graphics information, sends out a control signal to handle the corresponding situation, and then sends the control signal to the drive motor, so as to adjust the driving posture of the system in real time to ensure the correct driving direction.

Here, the CCD industrial camera in the drone interception system is controlled to obtain the current road image of the system during cruising, and the OpenCV image processing and computer vision function library are used to pre-process the acquired image: grayscale, denoising, and distortion correction. Then the processed image is threshold segmented to extract the road boundary features. Finally, the extracted features are matched and compared with the pre-set road template. If the two match, the recognition is successful, indicating that the location is a feasible road; if the match fails, it means that the current location is not a feasible road, and the camera is controlled to rotate a certain angle for re-recognition, and this cycle is repeated until a feasible road location is found.

Optionally, the CCD industrial camera model that can be used is DFK22AUC03.

S202: During the cruise, obstacles appearing in front of the UAV interception system are monitored in real time, and obstacles are avoided according to a preset obstacle avoidance algorithm.

In a specific implementation, the detection of obstacles in front of the drone interception system can be achieved based on the following steps 1 to 4:

Step 1: Control the ultrasonic sensor carried by the drone interception system to monitor obstacles appearing in front in real time. When an obstacle is detected, control the drone interception system to stop moving.

Step 2: Control the laser rangefinder carried by the UAV interception system to emit two ranging laser beams toward the obstacle in sequence within a preset time interval, and respectively determine the obstacle distance information corresponding to the two ranging laser beams.

Step 3: Determine the motion state of the obstacle relative to the drone interception system based on the distance information.

Step 4: When the motion state is a moving state toward, control the UAV interception system to retreat.

In specific implementation, during the cruising process, the unmanned and connected system controls the ultrasonic sensor to monitor the obstacles appearing in front in real time. When the ultrasonic sensor detects an obstacle, the system stops moving and the laser rangefinder starts working. Within the time of Δt, two laser beams are emitted for distance measurement. The measured obstacle distances are L1 and L2 respectively. By calculating the value of L1-L2, the automatic cruise control unit can determine whether the obstacle is stationary, moving towards the system or moving away from the system; the running speed of the obstacle is calculated by the formula (L1-L2)/Δt, which is used as the basis for controlling the movement of the automatic cruise module, that is, when the obstacle approaches a certain distance L, the automatic cruise control unit issues a command to control the system to retreat to avoid collision; otherwise, it continues to move forward.

Furthermore, when an obstacle is detected in front of the drone interception system, the orientation information of the obstacle relative to the drone interception system is determined; the rotation speed of the driving wheel on the side close to the obstacle that drives the drone interception system to move is controlled to be greater than the rotation speed of the driving wheel on the other side, so that the drone interception system can turn; real-time monitoring is performed to see whether there is still an obstacle within the field of view of the drone interception system; if so, the steering state of the drone interception system is maintained until there is no obstacle within the field of view; if not, the driving wheels on both sides of the drone interception system are adjusted to rotate synchronously, so that the drone interception system can resume straight-line driving.

In the specific implementation, the position information of the obstacle is determined by extracting the image features taken by the CCD industrial camera and the information returned by the obstacle avoidance module and transmitted to the automatic cruise control unit. The automatic cruise control unit outputs a control signal to make the speed of the driving wheel on the side close to the obstacle greater than the speed of the driving wheel on the other side, so that the system turns to avoid the obstacle. After turning a certain angle, no obstacle can be detected in the field of view, so that the automatic cruise control unit changes the control signal again, so that the two driving wheels rotate synchronously and the system returns to a straight-line driving state.

Here, four wheels are installed at the bottom of the drone interception system, two driving wheels are installed at the rear, and the driving motor is connected to the driving wheels to provide a power source for the driving wheels, which is used to drive the system to perform forward, backward and turning movements; two guide wheels are installed at the front and are connected to the system through a rotating pair. They can rotate freely around the rotating axis and are used to guide the system movement; when the system stops moving, the brakes fix the four wheels to prevent the vehicle from slipping due to external interference or when parking on a slope.

S203, collecting airspace images corresponding to the target cruising area in real time, inputting the airspace images into a preset target detection model to determine whether there is an invading drone, and if so, inputting the detected drone image into a preset target tracking model to determine the flight trajectory corresponding to the invading drone.

In specific implementation, when the drone interception system is performing automatic cruising, it collects airspace images in the area in real time to monitor whether there are invading drones. When an invading drone is found, it immediately locks the drone target and tracks and locates the drone target.

Here, the airspace image of the target cruising area is collected by the camera installed on the drone interception system, and the collected image is used as the input of the target detection algorithm. The target detection algorithm is used to detect whether there is an invading drone in the current airspace. When an invading drone is found, the image of the locked drone target is collected.

Optionally, YOLO can be used as the target detection model, and the established drone dataset can be used to implement real-time detection and positioning of intruding drones by the drone detection and tracking module.

Furthermore, the drone detection and tracking process can be implemented through the following steps 1-2:

Step 1: Input the drone image output by the preset target detection model into the preset target tracking model in real time.

Step 2: For each frame of the drone image, perform Kalman filter prediction on the previous frame of the drone image in chronological order, update the drone image of that frame according to the prediction result, and simultaneously match the motion features and appearance features retained when the target tracking model is initialized to determine the flight trajectory.

In the specific implementation, the target tracking model is pre-trained on a joint network based on the established drone dataset. The target tracking model takes the output of the target detection model as input, performs Kalman filter prediction on the previous frame and updates the current frame based on the detection results. It also performs multiple matches based on the motion and appearance features retained during initialization, and finally outputs the confirmed trajectory.

S204. According to the flight trajectory, adjust the aiming angle corresponding to the interception device carried in the UAV interception system; determine the number of detected UAVs, and according to the preset interception signal selection rule corresponding to the number of UAVs, send a UAV interception signal matching the preset interception signal selection rule along the aiming angle.

In the specific implementation, the position information of the UAV target sent by the target detection module and the target tracking module is calculated, and the horizontal and pitch deflection angles of the interception equipment are adjusted to keep the tracked target in the center of the image at all times. The adjustment process can be achieved using the IPD control algorithm.

Here, the intercepting device can be a gimbal, using a two-axis gimbal, with a horizontal rotation angle of 0°~360°, a vertical rotation angle of 0°~±90°, a horizontal rotation speed of 0.1°~160°/s, and a vertical rotation speed of 0.1°~120°/s.

Specifically, when the number of drones is one, the laser interception device carried by the drone interception system is controlled to work, and a high-energy laser beam is sent as a drone interception signal; when the number of drones is multiple and less than a preset number threshold, the laser interception device and navigation deception device carried by the drone interception system are controlled to work, and a high-energy laser beam and navigation deception signal are sent as a drone interception signal; when the number of drones is greater than the preset number threshold, the laser interception device, navigation deception device and multi-band radio jamming equipment carried by the drone interception system are controlled to work, and a high-energy laser beam, navigation deception signal and communication frequency jamming signal are sent as a drone interception signal.

It should be noted that the preset quantity threshold can be set according to actual needs and is not specifically limited here.

Here, according to the number of UAV targets locked by the system, GPS navigation decoy equipment, multi-band radio jammer equipment, and laser interception equipment are dispatched. Because laser interception equipment has the advantages of high precision, fast response, and low cost of use. So when the system detects only one invading UAV, the laser interception equipment is activated to intercept the invading UAV; because multi-band radio jammers do not produce waste or harmful substances, do not pollute the environment, and have a wide range of action, and have the ability to strike multiple targets, so when the system detects multiple invading UAVs, GPS navigation decoy equipment and laser interception equipment are activated at the same time to intercept multiple invading UAVs; when the invading UAV invades the protected airspace in the form of a "UAV cluster", GPS navigation decoy equipment, multi-band radio jammer equipment, and laser interception equipment are activated at the same time to intercept multiple UAV clusters to prevent them from slipping through the net.

Among them, the GPS navigation spoofing device obtains the actual GPS navigation signal of the target UAV under specific authorized circumstances, generates a GPS navigation spoofing signal with a GPS signal simulator based on the actual GPS navigation signal, and then transmits it to the target UAV, forcing the UAV to deviate from its own route and lure it to a designated location, thereby achieving the purpose of driving it away from flight.

Furthermore, multi-band radio jammers can generate interference signals of the same frequency band with greater power than the communication frequency of the drone, and use multiple omnidirectional antennas to simultaneously transmit communication frequency interference signals of multiple bands, thereby implementing omnidirectional interference on the drone cluster and blocking the flight control link between the remote control and the drone over a large area, forcing the drone to return, land or hover, so that it does not enter the protection area.

Among them, there are two types of communication frequency interference signals: interference with fixed-frequency signals of drones, which can release interference signals of the same frequency band at the same frequency for technical blocking; interference with frequency-hopping signals of drones. When the frequency band of each individual time slot of the target drone changes, it should be able to automatically combine the identified signal characteristics and frequency-hopping parameters, and release the same-frequency band interference signals of the corresponding frequency in each time slot for blocking.

Furthermore, laser interception equipment emits high-energy laser beams to illuminate drones. When the high-energy laser beams come into contact with drones, they generate heat and damage the structure or key components of the drones. The laser beams can quickly burn the drones’ electronic equipment, power units, and sensors, forcing the drones to lose control or flight capabilities and eventually crash.

Here, the laser interception equipment includes a laser transmitter, a concentrator, and a laser controller. The laser transmitter laser interception module is the core component, responsible for generating high-energy laser beams; laser transmitters usually work in a pulsed mode and can release a large amount of energy in a short period of time. It needs to have high precision and high stability to ensure that the drone can be effectively intercepted. The concentrator is used to focus and guide the laser beam, and usually includes optical components such as reflectors and lenses, through which parameters such as the direction, shape and focal length of the beam can be controlled. Through precise optical control, it can be ensured that the laser beam acts accurately on the key parts of the drone. The laser controller is responsible for controlling the operation of the laser transmitter and processing various information during the interception process. The laser controller needs to have the characteristics of intelligence, automation and high efficiency to ensure that the laser interception module can work stably and reliably.

The disclosed embodiment provides a method for intercepting a drone, which is applied to a drone interception system, obtains a target cruising area, and determines an optimal cruising path to control the automatic cruising of the drone interception system according to a preset cruising point through a path planning algorithm set in a preset path planning model; during the cruising process, the obstacles appearing in front of the drone interception system are monitored in real time, and obstacles are avoided according to a preset obstacle avoidance algorithm; an airspace image corresponding to the target cruising area is collected in real time, and the airspace image is input into a preset target detection model to determine whether there is an intruding drone, and if so, the detected drone image is input into a preset target tracking model to determine the flight trajectory corresponding to the intruding drone; according to the flight trajectory, the aiming angle corresponding to the interception device carried in the drone interception system is adjusted; the number of detected drones is determined, and according to the preset interception signal selection rule corresponding to the number of drones, a drone interception signal matching the preset interception signal selection rule is sent along the aiming angle. By establishing a path planning mathematical model, using a path planning algorithm to find the optimal path for cruising, cooperating with an obstacle avoidance algorithm to realize the automatic cruising of the drone interception system, and when an intruding drone is found, a combination of multiple interception methods is used to accurately and effectively intercept the intruding drone, thereby ensuring the safety of a large range of airspace.

Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

Based on the same inventive concept, a drone interception device corresponding to the drone interception method is also provided in the embodiment of the present disclosure. Since the principle of solving the problem by the device in the embodiment of the present disclosure is similar to the above-mentioned drone interception method in the embodiment of the present disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

Please refer to FIG. 3 , which is a schematic diagram of a drone interception device provided by an embodiment of the present disclosure. As shown in FIG. 3 , the drone interception device 300 provided by an embodiment of the present disclosure includes:

The path planning module 310 is used to obtain the target cruising area, determine the optimal cruising path according to the preset cruising point through the path planning algorithm set in the preset path planning model, and control the automatic cruising of the UAV interception system.

The obstacle avoidance module 320 is used to monitor obstacles appearing in front of the drone interception system in real time during the cruising process, and avoid the obstacles according to a preset obstacle avoidance algorithm.

The target detection and tracking module 330 is used to collect the airspace image corresponding to the target cruising area in real time, input the airspace image into a preset target detection model, determine whether there is an invading drone, and if so, input the detected drone image into a preset target tracking model to determine the flight trajectory corresponding to the invading drone.

The interception module 340 is used to adjust the aiming angle corresponding to the interception device carried in the drone interception system according to the flight trajectory; determine the number of detected drones, and send a drone interception signal matching the preset interception signal selection rule along the aiming angle according to the preset interception signal selection rule corresponding to the number of drones.

For descriptions of the processing flow of each module in the device and the interaction flow between each module, reference may be made to the relevant descriptions in the above method embodiment, which will not be described in detail here.

The disclosed embodiment provides a drone interception device, which is applied to a drone interception system, obtains a target cruising area, and determines an optimal cruising path to control the drone interception system to cruise automatically according to a preset cruising point through a path planning algorithm set in a preset path planning model; during the cruise, the obstacles appearing in front of the drone interception system are monitored in real time, and obstacles are avoided according to a preset obstacle avoidance algorithm; the airspace image corresponding to the target cruising area is collected in real time, and the airspace image is input into a preset target detection model to determine whether there is an invading drone, and if so, the detected drone image is input into a preset target tracking model to determine the flight trajectory corresponding to the invading drone; according to the flight trajectory, the aiming angle corresponding to the interception device carried in the drone interception system is adjusted; the number of detected drones is determined, and according to the preset interception signal selection rule corresponding to the number of drones, a drone interception signal matching the preset interception signal selection rule is sent along the aiming angle. By establishing a path planning mathematical model, using a path planning algorithm to find the optimal path for cruising, cooperating with an obstacle avoidance algorithm to realize the automatic cruising of the drone interception system, and when an invading drone is found, a combination of multiple interception methods is used to accurately and effectively intercept the invading drone, thereby ensuring the safety of a large range of airspace.

Corresponding to the drone interception method in FIG. 2 , the embodiment of the present disclosure further provides an electronic device 400. As shown in FIG. 4 , it is a schematic diagram of the structure of the electronic device 400 provided in the embodiment of the present disclosure, including:

Processor 41, memory 42, and bus 43; memory 42 is used to store execution instructions, including internal memory 421 and external memory 422; the internal memory 421 here is also called internal memory, which is used to temporarily store the calculation data in the processor 41, and the data exchanged with the external memory 422 such as the hard disk. The processor 41 exchanges data with the external memory 422 through the internal memory 421. When the electronic device 400 is running, the processor 41 communicates with the memory 42 through the bus 43, so that the processor 41 executes the steps of the drone interception method in Figure 2.

The embodiment of the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the drone interception method described in the above method embodiment are executed. The storage medium can be a volatile or non-volatile computer-readable storage medium.

The disclosed embodiments also provide a computer program product, which includes computer instructions. When the computer instructions are executed by a processor, the steps of the drone interception method described in the above method embodiment can be executed. For details, please refer to the above method embodiment, which will not be repeated here.

The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is implemented as a computer storage medium. In another optional embodiment, the computer program product is implemented as a software product, such as a software development kit (SDK).

Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present disclosure, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims (10)

1. An unmanned aerial vehicle interception method, characterized by being applied to an unmanned aerial vehicle interception system, comprising:

acquiring a target cruising region, and determining an optimal cruising path to control the unmanned aerial vehicle interception system to automatically cruise according to a preset cruising point through a path planning algorithm set in a preset path planning model;

during cruising, monitoring an obstacle appearing in front of the unmanned aerial vehicle interception system in real time, and avoiding the obstacle according to a preset obstacle avoidance algorithm;

Acquiring an airspace image corresponding to the target cruising area in real time, inputting the airspace image into a preset target detection model, determining whether an invasive unmanned aerial vehicle exists, and if so, inputting the detected unmanned aerial vehicle image into a preset target tracking model, and determining a flight track corresponding to the invasive unmanned aerial vehicle;

according to the flight track, adjusting a corresponding aiming angle of interception equipment carried in the unmanned aerial vehicle interception system; and determining the number of the detected unmanned aerial vehicles, and sending unmanned aerial vehicle interception signals matched with a preset interception signal selection rule along the aiming angle according to the preset interception signal selection rule corresponding to the number of the unmanned aerial vehicles.

2. The method according to claim 1, characterized by controlling the unmanned aerial vehicle interception system to automatically cruise, comprising in particular:

Controlling image acquisition equipment carried in the unmanned aerial vehicle interception system to acquire a current road image in real time, and preprocessing including graying, denoising and distortion correction is performed on the road image;

extracting road boundary features contained in the preprocessed road image;

Matching and comparing the road boundary characteristics with a preset road template, and if so, determining the current position as a feasible road;

If the road images are not matched, determining that the current position is an infeasible road, controlling the image acquisition equipment to rotate by a preset angle, and repeating the acquisition steps of the road images until the feasible road is detected.

3. The method according to claim 1, characterized in that the obstacle present in front of the unmanned aerial vehicle interception system is monitored in real time, in particular comprising:

Controlling an ultrasonic sensor carried in the unmanned aerial vehicle interception system to monitor an obstacle appearing in front in real time, and controlling the unmanned aerial vehicle interception system to stop moving when the obstacle is detected;

controlling a laser range finder carried in the unmanned aerial vehicle interception system to emit two beams of ranging laser to an obstacle in sequence within a preset time interval, and respectively determining obstacle distance information corresponding to the two beams of ranging laser;

determining the motion state of the obstacle relative to the unmanned aerial vehicle interception system according to the distance information;

and when the motion state is the orientation motion state, controlling the unmanned aerial vehicle interception system to retreat.

4. The method according to claim 1, wherein obstacle avoidance is performed according to a preset obstacle avoidance algorithm, comprising:

Determining azimuth information of the obstacle relative to the unmanned aerial vehicle interception system;

controlling one side close to an obstacle, and driving the rotation speed of a driving wheel for driving the unmanned aerial vehicle interception system to move to be larger than the rotation speed of a driving wheel on the other side so as to enable the unmanned aerial vehicle interception system to turn;

Monitoring whether an obstacle still exists in the visual field range of the unmanned aerial vehicle interception system in real time;

If yes, maintaining the steering state of the unmanned aerial vehicle interception system until no obstacle exists in the visual field range;

if not, the driving wheels on two sides of the unmanned aerial vehicle interception system are adjusted to synchronously rotate, so that the unmanned aerial vehicle interception system resumes straight running.

5. The method of claim 1, wherein the corresponding flight trajectory of the invasive drone is determined based on:

inputting the unmanned aerial vehicle image output by the preset target detection model into the preset target tracking model in real time;

according to the time sequence, carrying out Kalman filtering prediction on the unmanned aerial vehicle image of the previous frame aiming at each frame, updating the unmanned aerial vehicle image of the frame according to a prediction result, and simultaneously, matching the motion characteristics and the appearance characteristics reserved during the initialization of the target tracking model to determine the flight track.

6. The method according to claim 1, wherein the preset intercept signal selection rule specifically comprises:

When the number of the unmanned aerial vehicles is one, controlling laser interception equipment carried in the unmanned aerial vehicle interception system to work, and sending high-energy laser beams to serve as unmanned aerial vehicle interception signals;

When the number of the unmanned aerial vehicles is more than or less than a preset number threshold, controlling the laser interception equipment and the navigation decoy equipment carried in the unmanned aerial vehicle interception system to work, and simultaneously sending high-energy laser beams and navigation decoy signals as the unmanned aerial vehicle interception signals;

When the number of the unmanned aerial vehicles is larger than a preset number threshold, the laser interception equipment, the navigation decoy equipment and the multi-band radio interference equipment carried in the unmanned aerial vehicle interception system are controlled to work, and meanwhile, high-energy laser beams, navigation decoy signals and communication frequency interference signals are sent to serve as unmanned aerial vehicle interception signals.

7. An unmanned aerial vehicle intercepting apparatus, comprising:

The path planning module is used for acquiring a target cruising area, and determining an optimal cruising path to control the unmanned aerial vehicle interception system to automatically cruise according to a preset cruising point through a path planning algorithm arranged in a preset path planning model;

the obstacle avoidance module is used for monitoring the obstacle appearing in front of the unmanned aerial vehicle interception system in real time in the cruising process and avoiding the obstacle according to a preset obstacle avoidance algorithm;

The target detection tracking module is used for collecting an airspace image corresponding to the target cruising area in real time, inputting the airspace image into a preset target detection model, determining whether an invasive unmanned aerial vehicle exists, and if so, inputting the detected unmanned aerial vehicle image into the preset target tracking model, and determining a flight track corresponding to the invasive unmanned aerial vehicle;

The interception module is used for adjusting an aiming angle corresponding to interception equipment carried in the unmanned aerial vehicle interception system according to the flight track; and determining the number of the detected unmanned aerial vehicles, and sending unmanned aerial vehicle interception signals matched with a preset interception signal selection rule along the aiming angle according to the preset interception signal selection rule corresponding to the number of the unmanned aerial vehicles.

8. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine readable instructions executable by the processor, the processor and the memory in communication over the bus when the electronic device is running, the machine readable instructions when executed by the processor performing the steps of the drone interception method of any one of claims 1 to 6.

9. A computer readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, performs the steps of the unmanned aerial vehicle interception method according to any one of claims 1 to 6.

10. A computer program product comprising computer instructions which, when executed by a processor, implement the steps of the unmanned aerial vehicle interception method of any one of claims 1 to 6.