KR20210035039A - Apparatus and method for detecting unmanned aerial vehicle - Google Patents

Abstract

Disclosed are a method and a device for detecting an unmanned aerial vehicle. According to one embodiment of the present invention, the method for detecting an unmanned aerial vehicle comprises the steps of: receiving an image from one or more cameras located in an unmanned aerial vehicle protected area; analyzing an input image and extracting the unmanned aerial vehicle from the input image; and providing the extracted data related to the drone to train a drone detection model. The photographing time or photographing position of the one or more cameras may be variably controlled.

Description

UAV detection method and apparatus {APPARATUS AND METHOD FOR DETECTING UNMANNED AERIAL VEHICLE}

The present invention relates to a method and apparatus for detecting an unmanned aerial vehicle, and more particularly, to a method and an apparatus for detecting an unmanned aerial vehicle using a random arrangement of cameras and random visual imaging.

In recent years, social unrest has arisen due to accidents involving small unmanned aerial vehicles invading airports, public places, and protected areas. In particular, various technologies are being discussed to protect people and property from attacks through small unmanned aerial vehicles that are dedicated for military purposes. As applicable technologies, detection technology through radar, UAV detection technology based on image signal analysis, UAV detection technology based on noise characteristics, etc. are proposed, but there is a problem that detection is difficult when the UAV is small in size.

In the case of an unmanned aerial vehicle detection device using an image, when an unmanned aerial vehicle image is acquired from a long distance, since the image is small and difficult to detect, a zooming lens must be used to secure an unmanned aerial vehicle image of a certain size or more. In addition, there arises a problem that an economic burden increases due to a rapid increase in the number of cameras required.

An object of the present invention for solving the above problems is to provide a method of detecting an unmanned aerial vehicle using a random arrangement of cameras and random visual photographing.

Another object of the present invention for solving the above problems is to provide an unmanned aerial vehicle detection apparatus using the unmanned aerial vehicle detection method.

In order to achieve the above object, a method for detecting a drone according to an embodiment of the present invention includes: receiving an image from one or more cameras located in an unmanned aerial vehicle protected area; Analyzing an input image and extracting a drone from the input image; And providing the extracted data related to the unmanned aerial vehicle to train the unmanned aerial vehicle detection model, and at this time, a photographing time or a photographing position of one or more cameras may be variably controlled.

The area covered by the one or more cameras may be set to be smaller than the area of the UAV protection area.

The installation positions of the one or more cameras are randomly set, and the focal length of each camera may be set to a fixed state by zooming.

The unmanned aerial vehicle detection method may further include providing a signal for controlling a photographing time of the one or more cameras to each camera.

Providing a signal for controlling the photographing time of the one or more cameras to each camera may include generating a pseudo random binary sequence (PRBS); Generating a photographing time control signal for each camera by delaying the pseudorandom binary sequence in time using different offsets; And transmitting the photographing time control signal to each camera.

The method of detecting the unmanned aerial vehicle may further include providing a signal for controlling the positions of the one or more cameras to each camera.

Providing a signal for controlling the positions of one or more cameras to each camera may include: generating a pseudo random number (PRN); Randomly setting position coordinates of each camera based on the pseudorandom number according to a starting point of the camera; Generating a position control signal for moving each camera to a corresponding position coordinate; And transmitting the position control signal to each camera.

The position control signal may include a Panning, Tilting, Zooming (PTZ) control signal.

An apparatus for detecting an unmanned aerial vehicle according to an embodiment of the present invention for achieving the above other object includes: a processor; And a memory for storing at least one command executed through the processor, wherein the at least one command is extracted from each image analysis device for extracting the UAV from images collected from one or more cameras located in the UAV protected area. An instruction to receive data related to the unmanned aerial vehicle; An instruction to train an unmanned aerial vehicle detection model using the extracted unmanned aerial vehicle-related data; And a command to provide the unmanned aerial vehicle detection model to the one or more image analysis devices. In this case, the photographing time or the photographing position of the one or more cameras may be variably controlled.

The area covered by the one or more cameras may be set to be smaller than the area of the UAV protection area.

The installation positions of the one or more cameras are randomly set, and the focal length of each camera may be set to a fixed state by zooming.

The at least one command may further include a command to provide a signal for controlling the shooting time of the one or more cameras to each camera.

The command for providing a signal for controlling the shooting time of the one or more cameras to each camera includes: a command for generating a pseudo random binary sequence (PRBS); A command for generating a photographing time control signal for each camera by delaying the pseudorandom binary sequence in time using different offsets; And a command to transmit the photographing time control signal to each camera.

The at least one command may further include a command to provide a signal for controlling the position of the one or more cameras to each camera.

The command for providing a signal for controlling the positions of the one or more cameras to each camera includes: a command for generating a pseudo random number (PRN); A command to randomly set position coordinates of each camera according to a start point of recording of the camera based on the pseudorandom number; A command for generating a position control signal for moving each camera to a corresponding position coordinate; And a command to transmit the position control signal to each camera.

The position control signal may include a Panning, Tilting, Zooming (PTZ) control signal.

According to the embodiments of the present invention as described above, it is possible to minimize the number of cameras used to detect the unmanned aerial vehicle and reduce the number of devices for analyzing images captured by the camera, thereby reducing the cost required for the system. have.

Therefore, in order to detect a small UAV with a small effective area that cannot be detected through a radar through camera images, when configuring the UAV protected area, only a small number of cameras are used to detect the UAV in advance to prevent damage caused by unauthorized intrusion of UAVs. Can be prevented.

1 is an overall conceptual diagram of a system for detecting an unmanned aerial vehicle based on an image signal according to an embodiment of the present invention.
2 is a conceptual diagram illustrating an arrangement of an unmanned aerial vehicle detection area according to an embodiment of the present invention.
3 is a conceptual diagram of configuring an unmanned aerial vehicle detection area using random placement of cameras and random time capture according to an embodiment of the present invention.
4 is a conceptual diagram of an embodiment of a camera control for detecting an unmanned aerial vehicle according to the present invention.
5 is a conceptual diagram of another embodiment of a camera control for detecting an unmanned aerial vehicle according to the present invention.
6 is a flowchart of a method for detecting an unmanned aerial vehicle according to an embodiment of the present invention.
7 is a block diagram of an apparatus for detecting an unmanned aerial vehicle according to an embodiment of the present invention.

In the present invention, various modifications may be made and various embodiments may be provided, and specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to a specific embodiment, it should be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention. In describing each drawing, similar reference numerals have been used for similar elements.

Terms such as first, second, A, and B may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another component. For example, without departing from the scope of the present invention, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element. The term “and/or” includes a combination of a plurality of related described items or any of a plurality of related described items.

When a component is referred to as being "connected" or "connected" to another component, it is understood that it may be directly connected or connected to the other component, but other components may exist in the middle. It should be. On the other hand, when a component is referred to as being "directly connected" or "directly connected" to another component, it should be understood that there is no other component in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present application, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof does not preclude in advance.

Unless otherwise defined, all terms used herein including technical or scientific terms have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms as defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in the present application. Does not.

Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

1 is an overall conceptual diagram of a system for detecting an unmanned aerial vehicle based on an image signal according to an embodiment of the present invention.

In a system for detecting an unmanned aerial vehicle based on an image signal according to an embodiment of the present invention, the unmanned aerial vehicle detection area for monitoring the invasion of the unmanned aerial vehicle 10 is several small-scale unmanned aerial vehicle detection areas (detection area #i, ??, and detection area #k).

Referring to Figure 1, a plurality of cameras (210, 220, 230) located in the unmanned aerial vehicle detection area #i take a picture of the unmanned aerial vehicle 10 entering the area, and the captured image is transferred to the image analysis device #i (200). send. The image analysis device #i (200) analyzes images received from a plurality of cameras (210, 220, 230) to detect the result of unmanned aerial vehicle detection and related images through the IoT gateway 500, through the IoT sensor-based unmanned aerial vehicle detection device ( 700) can be provided.

In addition, in the unmanned aerial vehicle detection area #k, the plurality of cameras 310 and 320 and the image analysis device #k 300 may interlock to detect the unmanned aerial vehicle and transmit related images to the IoT sensor-based unmanned aerial vehicle detection device 700.

The cameras 210, 220, 230, 310, and 320 that photograph the UAV and the image analysis devices 200 and 300 that analyze the image captured by the camera are interconnected through IoT networking, and the detected UAV information ( You can perform collaborative tasks that share location, speed, direction of movement, etc.). The IoT sensor-based unmanned aerial vehicle detection device 700 may extract an unmanned aerial vehicle object from an image including an unmanned aerial vehicle received from the image analysis devices 200 and 300. The unmanned aerial vehicle detection apparatus 700 generates a learning model for unmanned aerial vehicle detection through deep learning on the extracted unmanned aerial vehicle object, and provides it to the image analysis devices 200 and 300. Each image analysis device can perform an inference task to detect and classify the UAV in real time using the UAV detection model.

Typically, in order to protect a specific area from the invasion of the UAV by analyzing the image characteristics of the UAV, it is necessary to monitor the protected area in real time for 24 hours using a camera. In addition, when the UAV detection through deep learning is used, the small UAV has a problem that the detection probability is lowered because the size of the UAV image becomes very small depending on the distance.

In the present invention, a plurality of zooming cameras are installed for the purpose of protecting human and physical assets from invasion of the UAV, but by randomly controlling the shooting time and shooting position of the camera as described through the following examples, the UAV It can effectively reduce the number of cameras used for image acquisition and analysis.

In addition, the present invention proposes a method of configuring a common apparatus for analyzing images captured by a plurality of cameras, and analyzing images captured by each camera at a random location and time.

2 is a conceptual diagram illustrating an arrangement of an unmanned aerial vehicle detection area according to an embodiment of the present invention.

2 shows the concept of a camera arrangement for an unmanned aerial vehicle detection area. In order to construct a front area S that protects the UAV from intrusion, it is necessary to install a number of cameras capable of covering the area.

2, by configuring the beam surface area A _i with the camera #i, configuring the beam surface area A _j with the camera #j, and configuring the beam surface area A _k with the camera #k, Front area S can be built. The image captured by each camera may be transmitted to the image analysis apparatus 200. In order to distinguish a plurality of camera images received by the image analysis apparatus 200, camera installation location information (eg, GPS information) and photographing time information may be used.

When constructing a UAV protected area, the field of view (FOV) of a camera detecting UAV has a close relationship with the UAV detection area. When the angle of view of the camera is wide, the area for monitoring the drone is widened, but the size of the drone displayed on the video image decreases, and the accuracy of detection and classification of the drone through deep learning is degraded.

On the other hand, when using a zooming lens to shoot a drone located at a distance, the angle of view decreases and the area to monitor the drone is reduced, but the size of the drone displayed on the video image increases, resulting in the accuracy of UAV detection and classification through deep learning. Becomes higher. However, when configuring the UAV detection area by setting the angle of view of the camera small as described above, the number of cameras required increases rapidly, and a method to overcome this is needed.

3 is a conceptual diagram of configuring an unmanned aerial vehicle detection area using random placement of cameras and random time capture according to an embodiment of the present invention.

_{Referring to FIG. 3, a plurality of beam surface areas (A 1} , A ₂ , A ₃ , A ₄ , A ₅ , A ₆ , A ₇₎ are used with a plurality of cameras to monitor the UAV appearing in the area in front of the UAV protected area. , A ₈ , A ₉ ) must be configured to detect the unmanned aerial vehicle 10 entering the corresponding surface area. Such a configuration proposed in the present invention is to reduce the number of surveillance cameras and video analysis devices, and it is assumed that the UAV flying in the UAV protected area continuously flies without hovering in a specific area.

That is, when the UAV 10 moves along a specific trajectory 30 in the UAV protected area, the beam surface areas (A ₁ , A ₂ , A ₃ , A ₄ , A ₅ , A _{6) formed by multiple cameras} , A ₇ , A ₈ , and A ₉ ), the corresponding UAV can be detected through the UAV image analysis device interlocking with the corresponding camera. At this time, multiple camera beam surface areas (A ₁ , A ₂ , A ₃ , A ₄ , A ₅ , A ₆ , A ₇ , A ₈ , A ₉ ) are always set to “On” to control the corresponding beam surface area. When all the cameras capture an image and transmit it to the image analysis device, the computing load of the image analysis device (200 in FIG. 2) increases, resulting in a problem that the number of image analysis devices must be increased.

In the present invention, this problem is solved through a method of transitioning a plurality of cameras to the "On/Off state".

In the embodiment illustrated in FIG. 3, an unmanned aerial vehicle may be detected by analyzing images provided by cameras (camera #1, camera #2, camera #4, camera #6, camera #8) starting to shoot.

At this time, the shooting time of the _{camera is t sh} , the number of images captured by the camera per unit time (Frame/sec) is F, the average shooting period of the _{camera is T av} , the number of cameras is N _c , the surface area of the camera beam is Ai, and the drone When the surface area of the protected area is S and the probability of unmanned aerial vehicle detection is P _d , the area of the UAV using a camera is N _{c, *} Ai.

In addition, assuming that the UAV is located at an arbitrary location in the UAV and detects the UAV with a single frame photographed by the camera, the probability P _{Dect_T} of detecting the UAV within the UAV protected area can be defined as in Equation 1 below. have.

In the case of a small unmanned aerial vehicle as a detection target, since the object of the unmanned aerial vehicle is detected and classified through tracking, a plurality of image frames are utilized. In this case, when the number of image frames required for the UAV object detection and tracking process is F _req , the probability of detecting the UAV within the UAV protected area can be expressed as Equation 2 below.

Meanwhile, as a method for calculating the area occupied by the UAV entering the UAV protected area, a random walk model, a Markov chain model, or the like can be used.

Assuming that the UAV is flying in a random walk model, and the average occupied area of the UAV during the _{T av time, which is the shooting cycle for all cameras, is C av} , the probability of detecting the UAV within the UAV protected area is expressed as Equation 3 below. Can be.

In the embodiments according to the present invention, after setting a total photographing period Tav that is commonly applied to all cameras, a method of allocating a photographing time for each camera within the entire photographing period may be used.

According to the embodiment of FIG. 3 described above, the area of the area for monitoring the UAV using a camera may be set smaller than the area of the total UAV protected area. That is, due to the movement characteristics of the unmanned aerial vehicle, even though the area according to the camera arrangement is set to be smaller than the total unmanned aerial vehicle protected area area, it is possible to effectively detect the unmanned aerial vehicle without significantly lowering the detection probability of the unmanned aerial vehicle.

4 is a conceptual diagram of an embodiment of a camera control for detecting an unmanned aerial vehicle according to the present invention.

In the embodiment shown in FIG. 4, a method of randomly controlling the shooting time of each camera while fixing the position and angle of view of the cameras disposed in the UAV protected area is shown.

In order to implement this method, the UAV detection system according to the present invention may include a pseudorandom binary sequence (PRBS) generator 410, a camera photographing time control unit 420, and a camera interface 430. The unmanned aerial vehicle detection system according to the present invention may include the unmanned aerial vehicle detection server 700 and the image analysis apparatus 200 as described through FIG. 1. In addition, the pseudorandom binary sequence (PRBS) generation unit 410, the camera shooting time control unit 420, and the camera interface, which are components of the UAV detection system, are the UAV detection server 700 and image analysis according to the function and implementation needs. It can be distributedly disposed on the device 200.

Assuming that there are K cameras monitoring the UAV protected area, a Pseudo Random Binary Sequence (Pseudo Random Binary Sequence) using the Pseudo Random Binary Sequence (PRBS) generator 410 is used to arbitrarily determine the shooting time of the K cameras. : PRBS) is generated and used to determine the shooting time of each camera. The generated pseudorandom binary sequence may be transmitted to the camera photographing time control unit 420.

The camera capture time control unit 420 may generate PRBSi corresponding to each camera by time offset shifting the PRBS data received from the pseudorandom binary sequence (PRBS) generator 410. The PRBSi consists of sequences corresponding to the shooting time of each camera, and is transmitted to individual cameras through the camera interface 430. In the present invention, shooting times of K cameras may be randomly set using this method.

The camera interface 430 may transmit a message for controlling the shooting time of each camera to the camera through a camera control protocol (eg, LANC; Logic Application Control Bus System).

According to the embodiment described with reference to FIG. 4, by installing a plurality of low-cost cameras facing a certain position in the UAV protection area and randomly adjusting the shooting time and the shooting time interval, it is possible to effectively configure the UAV protected area without PTZ equipment. have.

5 is a conceptual diagram of another embodiment of a camera control for detecting an unmanned aerial vehicle according to the present invention.

In the embodiment of FIG. 5, in order to efficiently detect the UAV while reducing the number of cameras covering the UAV protected area, a method of controlling the position of the camera disposed in the UAV protected area, a photographing angle, and the like is shown. That is, one camera can continuously move to various locations within the UAV protected area at intervals of time or move the lens direction to take a picture.

In order to implement this method, the UAV detection system may include a pseudorandom number (PRN) generation unit 510, a camera position selection unit 520, a position control signal generation unit 530, and a camera interface 540. have. The unmanned aerial vehicle detection system according to the present invention may include the unmanned aerial vehicle detection server 700 and the image analysis apparatus 200 as described through FIG. 1. In addition, the pseudorandom number (PRN) generation unit 510, the camera position selection unit 520, the position control signal generation unit 530, and the camera interface 540, which are components of the UAV detection system, are If necessary, it may be distributed and disposed in the unmanned aerial vehicle detection server 700 and the image analysis apparatus 200.

The pseudorandom number (PRN) generator 510 may generate a pseudorandom number and transmit it to the camera position selector 520. The camera position selecting unit 520 is based on the pseudorandom number received from the pseudorandom number generating unit 510, based on the position coordinates for each camera according to the time point (t1, t2, t3 ??) at which the camera starts recording. (x1, y1,z1), (x2,y2,z2), (x3,y3,z3)} can be set randomly.

The position control signal generation unit 530 generates a position control signal required to move the camera in position coordinates of the camera and transmits it to the camera interface 540. In this case, the position control signal may include a Panning, Tilting, Zooming (PTZ) control signal. The camera interface 540 may control the position of the camera by generating a control signal for a PTZ motor attached to the camera. At this time, the camera interface may transmit not only a position control signal for the camera, but also a shooting ON/OFF signal for the camera to each camera. That is, the embodiments described through FIGS. 3 to 5 may be used independently or in combination with other embodiments.

According to the embodiment described with reference to FIG. 5, by using only a few high-performance PTZ cameras to capture and analyze an image at a random time at a random location, it is possible to detect an unmanned aerial vehicle in an economical manner.

6 is a flowchart of a method for detecting an unmanned aerial vehicle according to an embodiment of the present invention.

The method for detecting a drone according to an embodiment of the present invention may be performed by an unmanned aerial vehicle detection system, more specifically, at least one of the unmanned aerial vehicle detection server and the image analysis device described through the above embodiments.

The unmanned aerial vehicle detection system receives images from one or more cameras located in the unmanned aerial vehicle protected area (S610). In more detail, each image analysis device may receive an image from one or more cameras controlled by the device.

The unmanned aerial vehicle detection system or image analysis device detects the unmanned aerial vehicle by analyzing the image input from the camera (S620). The unmanned aerial vehicle-related data is provided to the unmanned aerial vehicle detection server, and the unmanned aerial vehicle detection server may train the unmanned aerial vehicle detection model by using the extracted unmanned aerial vehicle-related data (S630). The learned and generated UAV detection model is provided to one or more image analysis devices (S640), so that each image analysis device may perform an inference task of detecting and classifying UAVs in real time in a field.

Meanwhile, although not shown in FIG. 6, the method for detecting a drone according to the present invention may further include providing a signal for controlling a shooting time of one or more cameras to each camera.

In this step, a Pseudo Random Binary Sequence (PRBS) is generated, and a Pseudo Random Binary Sequence is delayed using different offsets to generate a shooting time control signal for each camera, and a shooting time control signal Can be transmitted to each camera.

The method for detecting a drone according to the present invention may further include providing a signal for controlling the position of the one or more cameras to each camera. In this step, a Pseudo Random Number (PRN) is generated, the position coordinates of each camera are randomly set according to the starting point of the camera based on the pseudorandom number, and each camera is moved to the corresponding position coordinates. By generating a position control signal for, it can be transmitted to each camera.

In this case, the position control signal may include a Panning, Tilting, Zooming (PTZ) control signal.

7 is a block diagram of an apparatus for detecting an unmanned aerial vehicle according to an embodiment of the present invention.

An apparatus for detecting an unmanned aerial vehicle according to an embodiment of the present invention includes at least one processor 710, a memory 720 for storing at least one command executed through the processor, and a transmission/reception device connected to a network to perform communication ( 730).

The UAV detection device may further include an input interface device 740, an output interface device 750, and a storage device 760. Each of the components included in the UAV detection apparatus 700 may be connected by a bus 770 to communicate with each other.

The processor 710 may execute a program command stored in at least one of the memory 720 and the storage device 760. The processor 710 may mean a central processing unit (CPU), a graphics processing unit (GPU), or a dedicated processor in which methods according to embodiments of the present invention are performed. Each of the memory 720 and the storage device 760 may be configured with at least one of a volatile storage medium and a nonvolatile storage medium. For example, the memory 720 may be formed of at least one of read only memory (ROM) and random access memory (RAM).

Here, the at least one command may include: a command for causing the processor to receive data related to the UAV extracted from each image analysis apparatus for extracting the UAV from images collected from one or more cameras located in the UAV protected area; An instruction to train an unmanned aerial vehicle detection model using the extracted unmanned aerial vehicle-related data; And a command to provide the unmanned aerial vehicle detection model to the one or more image analysis devices.

In the present invention, a photographing time or a photographing position of the one or more cameras is variably controlled.

The area covered by the one or more cameras may be set to be smaller than the area of the UAV protection area.

The installation positions of the one or more cameras are randomly set, and the focal length of each camera may be set to a fixed state by zooming.

The at least one command may further include a command to provide a signal for controlling the shooting time of the one or more cameras to each camera.

The command for providing a signal for controlling the shooting time of the one or more cameras to each camera includes: a command for generating a pseudo random binary sequence (PRBS); A command for generating a photographing time control signal for each camera by delaying the pseudorandom binary sequence in time using different offsets; And a command to transmit the photographing time control signal to each camera.

The at least one command may further include a command to provide a signal for controlling the position of the one or more cameras to each camera.

The command for providing a signal for controlling the positions of the one or more cameras to each camera includes: a command for generating a pseudo random number (PRN); A command to randomly set position coordinates of each camera according to a start point of recording of the camera based on the pseudorandom number; A command for generating a position control signal for moving each camera to a corresponding position coordinate; It may include a command to transmit the position control signal to each camera.

In this case, the position control signal may include a Panning, Tilting, Zooming (PTZ) control signal.

According to the embodiments of the present invention as described above, after combining a plurality of cameras and a single image analysis device, a UAV invading a UAV protected area through a camera that randomly photographs at an arbitrary position at a time. By detecting, it is possible to minimize the number of cameras used for detection of the UAV and reduce the number of devices that analyze images captured by the camera, thereby reducing the cost required for the system.

The operation of the method according to the embodiment of the present invention can be implemented as a computer-readable program or code on a computer-readable recording medium. The computer-readable recording medium includes all types of recording devices that store data that can be read by a computer system. In addition, a computer-readable recording medium may be distributed over a network-connected computer system to store and execute a computer-readable program or code in a distributed manner.

Further, the computer-readable recording medium may include a hardware device specially configured to store and execute program commands, such as ROM, RAM, and flash memory. The program instructions may include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like.

While some aspects of the invention have been described in the context of an apparatus, it may also represent a description according to a corresponding method, where a block or apparatus corresponds to a method step or characteristic of a method step. Similarly, aspects described in the context of a method can also be represented by a corresponding block or item or a feature of a corresponding device. Some or all of the method steps may be performed by (or using) a hardware device such as, for example, a microprocessor, a programmable computer or electronic circuit. In some embodiments, one or more of the most important method steps may be performed by such an apparatus.

In embodiments, a programmable logic device (eg, a field programmable gate array) may be used to perform some or all of the functionality of the methods described herein. In embodiments, the field programmable gate array may work with a microprocessor to perform one of the methods described herein. In general, the methods are preferably performed by some hardware device.

Although the above has been described with reference to preferred embodiments of the present invention, those skilled in the art will be able to variously modify and change the present invention within the scope not departing from the spirit and scope of the present invention described in the following claims. You will understand that you can.

Claims (16)

Receiving an image from one or more cameras located in the UAV protected area;
Analyzing an input image and extracting a drone from the input image; And
Providing the extracted unmanned aerial vehicle related data to train the unmanned aerial vehicle detection model,
The photographing time or photographing position of the one or more cameras is variably controlled. The method according to claim 1,
The area covered by the one or more cameras is set to be smaller than the area of the UAV protection area. The method according to claim 1,
The installation position of the one or more cameras is set at random, and the focal length of each camera is set to a fixed state by zooming. The method according to claim 1,
The method further comprising providing a signal for controlling the shooting time of the one or more cameras to each camera. The method of claim 4,
Providing a signal for controlling the shooting time of the one or more cameras to each camera,
Generating a pseudo random binary sequence (PRBS);
Generating a photographing time control signal for each camera by delaying the pseudorandom binary sequence in time using different offsets; And
And transmitting the photographing time control signal to each camera. The method according to claim 1,
The method further comprising providing a signal for controlling the position of the one or more cameras to each camera. The method of claim 6,
Providing a signal for controlling the position of the one or more cameras to each camera,
Generating a pseudo random number (PRN);
Randomly setting position coordinates of each camera based on the pseudorandom number according to a starting point of the camera;
Generating a position control signal for moving each camera to a corresponding position coordinate; And
And transmitting the position control signal to each camera. The method of claim 7,
The position control signal includes a PTZ (Panning, Tilting, Zooming) control signal. An unmanned aerial vehicle detection device interworking with one or more image analysis devices,
Processor; And
Includes a memory for storing at least one instruction executed through the processor,
The at least one command,
A command for receiving data related to the unmanned aerial vehicle extracted from each image analysis device for extracting the unmanned aerial vehicle from images collected from one or more cameras located in the unmanned aerial vehicle protected area;
An instruction to train an unmanned aerial vehicle detection model using the extracted unmanned aerial vehicle-related data; And
Including an instruction to provide the unmanned aerial vehicle detection model to the one or more image analysis devices,
The photographing time or photographing position of the one or more cameras is variably controlled. The method of claim 9,
An area covered by the one or more cameras is set to be smaller than an area of the UAV protection area. The method of claim 9,
The installation position of the one or more cameras is set at random, and the focal length of each camera is set to a fixed state by zooming. The method of claim 9,
The at least one command,
The unmanned aerial vehicle detection apparatus further comprising a command to provide a signal for controlling the shooting time of the one or more cameras to each camera. The method of claim 12,
The command to provide a signal for controlling the shooting time of the one or more cameras to each camera,
An instruction to generate a pseudo random binary sequence (PRBS);
A command for generating a photographing time control signal for each camera by delaying the pseudorandom binary sequence in time using different offsets; And
An unmanned aerial vehicle detection apparatus comprising a command to transmit the photographing time control signal to each camera. The method of claim 9,
The at least one command,
Further comprising a command to provide a signal for controlling the position of the one or more cameras to each camera, UAV detection apparatus. The method of claim 14,
The command to provide a signal for controlling the position of the one or more cameras to each camera,
An instruction to generate a pseudo random number (PRN);
A command to randomly set position coordinates of each camera according to a start point of recording of the camera based on the pseudorandom number;
A command for generating a position control signal for moving each camera to a corresponding position coordinate; And
And a command to transmit the position control signal to each camera. The method of claim 15,
The position control signal includes a PTZ (Panning, Tilting, Zooming) control signal.

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