KR20210014951A - Method and system for detecting aerial vehicle - Google Patents

Abstract

Provided are a method for detecting an unmanned aerial vehicle and a system thereof. The system for detecting the unmanned aerial vehicle comprises: a radar device which detects a target using a radar signal and generates target information on the target; a target detection device having multiple sensors and tracking the target by operating the multiple sensors using the target information; and an operation device receiving the target information from the radar device and transmitting the target information to the target detection device according to a predetermined policy.

Description

Unmanned aerial vehicle detection method and system {METHOD AND SYSTEM FOR DETECTING AERIAL VEHICLE}

The present invention relates to a method and system for detecting an unmanned aerial vehicle.

Unmanned aerial vehicles (unmanned aerial vehicles, unmanned aerial vehicles, unmanned aerial vehicles, drones, etc.) are aircraft that are not on board by a pilot. An unmanned aerial vehicle is a vehicle that is remote piloted from the ground, operates autonomously in an automatic or semi-auto-piloted format according to a pre-programmed route, or performs a mission according to its own environmental judgment by mounting artificial intelligence. . In addition, the unmanned aerial vehicle may collectively refer to the entire system, such as Ground Control Station/System (GCS) and communication equipment (data link) and support equipments.

As the operation of unmanned aerial vehicles becomes more active, the need for anti-drone technology (or unmanned aerial vehicle defense technology) to prevent accidents or crimes caused by unmanned aerial vehicles is also increasing. In general, anti-drone technology may include a detection technology that detects the approach of an unmanned aerial vehicle and a neutralization technology that neutralizes the flight of an unmanned aerial vehicle.

The problem to be solved by the present invention is to provide an unmanned aerial vehicle detection method and system capable of increasing the detection speed and quality of an unmanned aerial vehicle.

According to an embodiment of the present invention, an unmanned aerial vehicle detection system for detecting an unmanned aerial vehicle is provided. The unmanned aerial vehicle detection system includes a radar device that detects a target using a radar signal and generates target information about the target, multiple sensors, and operates the multiple sensors using target information to track the target. It includes an operating device that receives target information from a detection device and a radar device, and transmits target information to the target detection device according to a predetermined policy, but the initial focal length of multiple sensors is supported by one radar beam emitted from the radar device. Based on the beam size in the azimuth and elevation directions, the entire ROI range of the radar cell is calculated, and a focal length that satisfies the entire ROI range is selected among candidate focal lengths calculated based on the minimum detectable Pixels on Target (PoT). The radar device may update the target information according to a predetermined period, and the target detection device may adjust the focal length of the multiple sensors by reflecting the target size, target speed, and target distance of the updated target information.

According to an embodiment of the present invention, sensors such as an optical sensor and a depth information extraction sensor are operated together to compensate for the shortcomings of a radar with a relatively large error and a low recognition rate, thereby detecting an unmanned aerial vehicle more quickly and a target recognition rate. Can increase.

Accordingly, it is possible to improve the recognition quality of the unmanned aerial vehicle, improve the tracking performance of the unmanned aerial vehicle, and further accurately determine whether the detected unmanned aerial vehicle is illegal.

1 is a view for explaining an unmanned aerial vehicle detection system according to an embodiment of the present invention.
2 is a view for explaining a radar device according to an embodiment of the present invention.
3 is a view for explaining an operating device according to an embodiment of the present invention.
4 is a view for explaining a target detection device according to an embodiment of the present invention.
5 is a diagram illustrating a method of detecting an unmanned aerial vehicle according to an embodiment of the present invention.
6 is a diagram illustrating a method of detecting an unmanned aerial vehicle according to an exemplary embodiment of the present invention.
7 is a diagram illustrating a method of detecting an unmanned aerial vehicle according to an exemplary embodiment of the present invention.
8 is a diagram illustrating a method of detecting an unmanned aerial vehicle according to an embodiment of the present invention.
9 to 12 are diagrams for explaining a method of setting a focal length for multiple sensors according to an embodiment of the present invention.
13 is a diagram illustrating a computing system according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art may easily implement the present invention. However, the present invention may be implemented in various forms and is not limited to the embodiments described herein. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and similar reference numerals are assigned to similar parts throughout the specification.

Throughout the specification and claims, when a certain part "includes" a certain component, it means that other components may be further included rather than excluding other components unless otherwise stated.

Now, a method and system for estimating an unmanned aerial vehicle according to an embodiment of the present invention will be described in detail with reference to the drawings.

1 is a view for explaining an unmanned aerial vehicle detection system according to an embodiment of the present invention.

Referring to FIG. 1, an unmanned aerial vehicle detection system 1 according to an embodiment of the present invention may include a radar device 10, an operation device 20, and a target detection device 30. According to a specific implementation purpose, the unmanned aerial vehicle detection system 1 may further include a network 40 for electrically connecting the radar device 10, the operating device 20, and the target detection device 30.

The radar device 10 detects a target using a radar signal. Here, the target may be an unmanned aerial vehicle, but may also mean an arbitrary object detected by a radar signal before being identified as an unmanned aerial vehicle. The radar device 10 may generate target information on the detected target and transmit the target information to the operating device 20 or the target detection device 30.

In some embodiments of the present invention, the target information may include at least one of identification information (id) of a target, azimuth angle information, elevation angle information, distance information, movement speed information, movement direction information, and risk information, but the present invention The range of is not limited thereto, and the type and number of information included in the target information may be changed as much as possible according to a specific implementation purpose.

Such target information may be updated according to a predetermined period. That is, the radar device 10 may repeatedly detect the target or newly detect the target according to a predetermined period to update target information. Here, the predetermined period may mean a period having a predetermined time interval or a period having a variable time interval. When the target information is updated, the radar device 10 may transmit the updated target information to the operating device 20 or the target detection device 30.

The operating device 20 may provide information on a target to the target detection device 30, receive detection result data from the target detection device 30, and process it. Specifically, the operating device 20 may receive target information from the radar device 10 and transmit the target information to the target detection device 30 according to a predetermined policy. For example, when the operating device 20 receives a plurality of target information from the radar device 10, the operating device 20 selects one of the plurality of target information according to a predetermined priority, and the target detection device ( 30), or may be provided to the target detection apparatus 30 sequentially in an order according to a predetermined priority.

In some embodiments of the present invention, the risk information may be used to select target information to be transmitted to the target detection device 30 from among target information received by the operating device 20 from the radar device 10. In other words, the operating device 20 selects target information to be transmitted to the target detection device 30 according to the risk information (eg, in the order of high risk) from among a plurality of target information received from the radar device 10. I can.

In addition, the operating device 20 may transmit the detection result data received from the target detection device 30 to a response system such as UTM (Unified Threat Management). If the detected target is determined to be an illegal unmanned aerial vehicle, the response system may, for example, take steps to neutralize the flight of the unmanned aerial vehicle.

In some embodiments of the present invention, the operating device 20 is a server, a personal computer, a notebook computer, a tablet computer, a computing device including a smartphone, or an application specific integrated circuit (ASIC), an FPGA ( It may be implemented with hardware such as a programmable semiconductor device including a Field Programmable Gate Array. In addition, the operating device 20 may be implemented with software such as a program or application that can be executed through a processor such as a CPU (Central Processing Unit) or a GPU (Graphic Processing Unit). Furthermore, the operating device 30 may be implemented in the form of a combination of hardware and software.

The target detection device 30 detects a target. Specifically, the target detection device 30 may perform a function such as tracking a target or recognizing a target. In particular, the target detection device 30 includes multiple sensors, and target detection performance may be improved by using the radar device 10 and multiple sensors together. Specifically, the target detection device 30 may perform a function of automatically tracking a target by receiving target information generated by the radar device 10 and operating multiple sensors using the target information.

The target detection device 30 may receive target information through the operating device 20, or may receive target information directly from the radar device 10 without passing through the operating device 20. When receiving target information through the operating device 20, the target detection device 30 may receive target information selected according to a predetermined policy from the operating device 20, and receive target information from the radar device 10. In the case of being directly provided, the target detection device 30 may select target information (eg, select target information with the highest risk) according to a predetermined priority from among target information provided from the radar device 10.

At least some of the radar device 10, the operating device 20, and the target detection device 30 may directly exchange data using, for example, a data transmission cable. Alternatively, at least some of the radar device 10, the operating device 20, and the target detection device 30 may exchange data through the network 400.

In some embodiments of the present invention, the network 400 is a wireless network, including a local area network (LAN), a wired network including a wide area network (WAN), a WiFi network, a Bluetooth network, a cellular network, and the like. A network or a combination of a wired network and a wireless network may be included, but the scope of the present invention is not limited thereto.

2 is a view for explaining a radar device according to an embodiment of the present invention.

Referring to FIG. 2, the radar device 10 according to an embodiment of the present invention may include a radar module 11 and a radar signal processing module 13.

The radar module 11 fires a radar beam at the target and acquires a radar signal detecting the target. Specifically, the radar module 11 may detect a position or a moving speed of the target by receiving a radar signal reflected and returned from the target.

The radar signal processing module 13 processes the radar signal acquired by the radar module 11. Specifically, the radar signal processing module 13 may generate the target information described above with respect to FIG. 1 from the radar signal received by the radar module 11. For example, the radar signal processing module 13 generates elevation angle information, distance information, movement speed information, movement direction information, etc. of a target from the radar signal received by the radar module 11, and identification information or Risk information can be additionally created. The generated target information may be implemented in a data structure that can be read by the operating device 20 or the target detection device 30. As mentioned in connection with FIG. 1, the target information may be updated according to a predetermined period.

3 is a view for explaining an operating device according to an embodiment of the present invention.

Referring to FIG. 3, the operating device 20 according to an embodiment of the present invention may include an operating processing module 21 and an image processing module 23.

The operation processing module 21 may process data provided from the target detection device 30. For example, the operation processing module 21 changes the format of the data in order to receive data on a detection result or recognition result for a target from the target detection device 30 and transmit the data to a corresponding system such as UTM. Or, you can process the data as needed.

The image processing module 23 recognizes a target using a neural network-based machine learning algorithm. Specifically, the image processing module 23 uses a weight previously learned through a database in which pre-data on the unmanned aerial vehicle is stored, and a new target detection result or target recognition result provided from the target detection device 30 Recognition performance can be improved by adding it as a data set and re-learning.

In FIG. 3, the image processing module 23 is shown to be included in the operation processing module 21, but the scope of the present invention is not limited thereto, and the target detection device 30 may be implemented to include the image processing module. have. In this case, the image processing module implemented in the target detection device 30 performs a process of relearning by adding the target detection result or the target recognition result generated by the target detection device 30 as a new data set, and the image processing module The data as a result of recognizing the target may be provided to the operation device 20 (for example, the operation processing module 21).

4 is a view for explaining a target detection device according to an embodiment of the present invention.

Referring to FIG. 4, a target detection device 30 according to an embodiment of the present invention includes a multi-sensor 31, a multi-sensor information acquisition module 33, a pan/tilt (PT) driving module 35, and a multi-sensor. It may include an information processing module 37.

The multiple sensor 31 refers to a sensor used to detect a target by interlocking with the radar device 10. In some embodiments of the present invention, the multiple sensors 31 may include an optical sensor and a depth information extraction sensor. The optical sensor may include, for example, an electro-optic (Electro-Optica, EO) sensor (or camera), an infrared sensor (or camera), and the like, and also a zoom for obtaining an image of a distant target. It may further include a lens (zoom lens).

Meanwhile, the depth information extraction sensor may include a LiDAR (Light Detection And Ranging, LiDAR) sensor. Using the lidar sensor, it is possible to detect various characteristics of the target, such as distance to the target, direction, speed, temperature, material distribution and concentration characteristics, etc. by shining a laser at the target.

The multi-sensor information acquisition module 33 may acquire sensing information that detects a target using the multi-sensor 31. The sensing information may include information such as a 2-dimensional (2D) position and a 3-dimensional (3D) position of the target, a movement direction, a movement speed, and a distance to the target.

The PT driving module 35 is mounted on the multiple sensors 31 to control the positions of the multiple sensors 31. Specifically, the PT driving module 35 may control the multiple sensors 31 to perform a pan or tilt operation. That is, the PT driving module 35 allows the multi-sensor 31 to pan or tilt to obtain an image in a desired direction.

In particular, the target detection device 30 may control the PT driving module 35 by converting target information received from the radar device 10 or the operating device 20 into pan and tilt information. Accordingly, the target detection device 30 can track a target detected by the radar device 10.

Meanwhile, the target detection device 30 may control the position of the multiple sensors 31 as described above, and then adjust the zoom value and the focus value of the optical sensor. That is, after moving the position, the multi-sensor 31 may adjust a zoom value based on a preset initial focal length or may adjust a focus value based on distance information among target information. An embodiment of setting the initial focal length will be described later with reference to FIGS. 9 to 12.

In this way, the target detection device 30 may automatically set the PTZF of the multi-sensor 31 based on the target information received from the radar device 10 or the operating device 20. Here, PTZF means pan, tilt, zoom, and focus.

The multi-sensor information processing module 37 may process sensing information acquired by the multi-sensor information acquisition module 33. In addition, the multi-sensor information processing module 37 may generate multi-sensor information including at least one of image information and depth information acquired through the multi-sensor 31.

Meanwhile, the multi-sensor information processing module 37 may encode multi-sensor information and transmit the encoded multi-sensor information to the operating device 20. Then, the operating device 20 may decode the encoded multi-sensor information and select a target of interest based on the decoded multi-sensor information. The target of interest may mean a target determined to need tracking among targets detected by the radar device 10.

The operating device 20 may generate target information of interest for the selected target of interest and transmit the target information of interest to the target detection device 30. In some embodiments of the present invention, the target of interest information may include at least one of 2D coordinate information of the target of interest (ie, x coordinate and y coordinate of the target in a 2D image), movement speed information, and size information.

The target detection device 30 receiving the target of interest information from the operating device 20 may track the target of interest or recognize the target of interest using the target of interest information.

In some embodiments of the present invention, as described above with respect to FIG. 3, the target detection device 30 uses a weight previously learned through a database storing pre-data on an unmanned aerial vehicle, and It may include an image processing module that executes a neural network-based machine learning algorithm that performs a process of re-learning by adding a target detection result or a target recognition result of interest as a new data set. In this way, the target detection device 30 may recognize a target of interest using a neural network-based machine learning algorithm, and then provide the recognition result data to the operating device 20.

On the other hand, in some embodiments of the present invention, the operating device 20 changes a target of interest according to a predetermined policy, generates changed target of interest information for the changed target of interest, and sends the target detection device 30 Change interest target information can be communicated. In addition, the target detection device 30 receiving the change-interest target information from the operating device 20 may change the tracking and recognition target by using the change-interest target information.

5 is a diagram illustrating a method of detecting an unmanned aerial vehicle according to an embodiment of the present invention.

5, in the unmanned aerial vehicle detection method according to an embodiment of the present invention, the radar device 10 detects a target using a radar signal, and then receives target information (initial target information) for the detected target. It can be acquired (S101). In addition, the radar device 10 may transmit initial target information to the operating device 20 (S103).

The operating device 20 may distribute the initial target information received from the radar device 10 (S105). For example, when the operating device 20 receives a plurality of target information from the radar device 10 and there are a plurality of target detection devices 30, the operating device 20 is based on the risk information of each of the plurality of initial target information. Based on the initial target information with the highest risk, it may be transmitted to the plurality of target detection devices 30 in order (S107). As another example, when the operating device 20 receives a plurality of target information from the radar device 10 and the target detection device 30 is one, the operating device 20 is based on the risk information of each of the plurality of initial target information. Thus, initial target information with the highest risk may be transmitted to a single target detection device 30 (S107).

Meanwhile, the radar device 10 may directly transmit initial target information to the target detection device 30 (S109). That is, the target detection device 30 may directly receive target information from the radar device 10. In this case, for example, the target detection device 30 may select, for example, initial target information with the highest risk from among the target information provided by the radar device 10.

Next, the target detection device 30 may automatically set the PTZF of the multiple sensors 31 and generate sensing information that detects the target by using the multiple sensors 31 (S111).

The step (S111) is to convert the initial target information received from the radar device 10 or the operating device 20 into pan and tilt information (S1111), and the position of the multi-sensor 31 using pan and tilt information. It may include moving (S1113) to obtain an image in a desired direction.

In addition, the step S111 may include adjusting the zoom value of the multiple sensors 31 (eg, optical sensor) (S1115) and adjusting the focus value (S1117).

Next, the target detection device 30 may process the sensing information to generate multi-sensor information including at least one of image information and depth information acquired through the multi-sensor 31 (S113).

Subsequently, the target detection device 30 may encode the multi-sensor information (S115) and transmit the encoded multi-sensor information to the operating device 20 (S117).

6 is a diagram illustrating a method of detecting an unmanned aerial vehicle according to an exemplary embodiment of the present invention.

6, in the unmanned aerial vehicle detection method according to an embodiment of the present invention, the operating device 20 decodes the encoded multi-sensor information and reproduces the decoded multi-sensor information (for example, decoded image information) ( S119) You can.

Next, the operating device 20 may select a target of interest based on the decoded multi-sensor information and generate target information of interest for the selected target of interest (S121). In addition, the operating device 20 may transmit the target information of interest to the target detection device 30 (S123).

The target detection device 30 receiving the target of interest information may track the target of interest by using the target of interest information (S125). In particular, the target detection device 30 may automatically track a target of interest (ie, an unmanned aerial vehicle).

For example, the target detection device 30 may correct the location information of the target of interest while automatically tracking the target of interest. That is, the target detection device 30 may perform error correction in a manner that periodically performs detection, thereby periodically correcting the location information of the target of interest. In the present specification, the meaning of a period may mean a period having a predetermined time interval or a period having a variable time interval.

Meanwhile, as described above with respect to FIG. 1, the radar device 10 may update initial target information according to a predetermined period. The target detection device 30 may adjust the zoom value of the multiple sensors 31 by reflecting the updated initial target information.

Specifically, the target detection device 30 considers the updated initial target information including the updated identification information, distance information, movement speed information, etc. of the target, and the multi-sensor 31 in consideration of the size of the target of interest acquired through detection. You can adjust the zoom value of. For example, when the speed information is reflected, when the speed of the target is fast, the focal length may be lowered to widen the range in which the target can move in the image sensed by the multi-sensor 31. That way, you won't miss the target during automatic tracking. In general, target distance, target size, target speed and focal length may have the following relationship.

Meanwhile, the target detection device 30 may periodically adjust the focus value for the detected region of interest (ROI). In contrast, the target detection apparatus 30 may perform focus value adjustment when a change in a target distance, a target size, etc. is out of a predetermined level or range for the detected target area ROI.

Meanwhile, the target detection device 30 may control the PT driving module 35 by continuously updating the pan and tilt values according to the movement of the target in order not to miss the target while performing automatic tracking. For example, the target detection device 30 continuously adjusts the pan and tilt values so that the target is located in the center or in a predetermined area including the center of the image sensed by the multi-sensor 31 while performing automatic tracking. By updating, the PT driving module 35 can be controlled.

The target detection device 30 may transmit the tracking result for the target of interest to the operating device 20 (S127). Then, the operating device 20 may process the corresponding tracking result data as necessary, and then transmit it to a corresponding system such as UTM (S129).

7 is a diagram illustrating a method of detecting an unmanned aerial vehicle according to an exemplary embodiment of the present invention.

Referring to Figure 7, in the unmanned aerial vehicle detection method according to an embodiment of the present invention, the operating device 20, for example, while the target detection device 30 performs automatic tracking on the target of interest (S125), in advance A target of interest may be changed according to a predetermined policy, and change interest target information for the changed target of interest may be generated (S131). For example, when the operating device 20 recognizes a target having a higher risk than the current target of interest, the operating device 20 may change the target to a target of interest and generate information about the target of interest.

Subsequently, the operating device 20 may transmit the changed target information of interest to the target detection device 30 (S133). Then, the target detection device 30 may change an automatic tracking target using the changed target of interest information (ie, changed target of interest information) and perform automatic tracking on the changed target of interest (S135).

On the other hand, the operating device 20 receives new target information on the new target detected from the radar device 10 (S137), changes the new target into a target of interest based on the new target information, and changes the target information of interest thereto. Can be created (S139).

Subsequently, the operating device 20 may transmit the changed target information of interest to the target detection device 30 (S141). Then, the target detection device 30 may perform automatic tracking using the changed target information of interest (S143).

Next, the target detection device 30 may transmit the changed tracking result of the target of interest to the operating device 20 (S127). Then, the operating device 20 may process the corresponding tracking result data as necessary, and then transmit it to a corresponding system such as UTM (S129).

8 is a diagram illustrating a method of detecting an unmanned aerial vehicle according to an embodiment of the present invention.

Referring to FIG. 8, in the method for detecting an unmanned aerial vehicle according to an embodiment of the present invention, the target detection device 30 may recognize a target of interest after performing automatic tracking on a target of interest (S125). When the size of the target of interest is smaller than the size that can be recognized, the target detection device 30 performs a zoom operation on the multiple sensors 30 in a line that does not miss tracking of the target of interest in consideration of the moving speed of the target of interest. , Can be adjusted to increase the focal length.

The target detection device 30 may transmit the recognition result for the target of interest (ie, the target recognition result) to the operating device 20 (S147).

The operating device 20 may perform image processing for recognizing a target using a neural network-based machine learning algorithm (S149). Specifically, the operating device 20 uses the weights previously learned through the database in which the pre-data on the unmanned aerial vehicle is stored, and adds the target detection result or target recognition result provided from the target detection device 30 as a new data set. Therefore, recognition performance can be improved by relearning.

Meanwhile, the target detection device 30 may also perform image processing for recognizing a target using a neural network-based machine learning algorithm (S151). Specifically, the target detection device 30 performs a process of re-learning by adding the target detection result or the target recognition result generated by the target detection device 30 as a new data set, and recognizes the target through the image processing module. As a result, data may be provided to the operating device 20 (S153).

Then, the operating device 20 may process the corresponding recognition result data as necessary and then transmit it to a corresponding system such as UTM (S129).

9 to 12 are diagrams for explaining a method of setting a focal length for multiple sensors according to an embodiment of the present invention.

As described above with reference to FIG. 4, after moving the position of the multiple sensors 31, the target detection device 30 may adjust the zoom value of the optical sensor of the multiple sensors 31 based on the initial focal length. have. To this end, the accuracy or resolution of the 3D target obtained from the radar device 10 may be considered. This resolution is defined according to the resolution of the radar beam. In general, the resolution of the radar device 10 is significantly lower than that of an optical sensor (eg, an Electro-Optica (EO) sensor, an infrared sensor, etc.). Therefore, it may be necessary to analyze the arrangement and specifications of the radar beam for target detection.

Referring to FIG. 9, the radar beam is not formed in a right-angled shape (a rectangle at a specific distance) due to its characteristics, and is formed in an elliptical shape and gradually increasing in size as the distance from the radiation point increases. The initial focal length of the multi-sensor 31 may be set in the following manner.

First, in order to reflect the accuracy of the 3D target acquired from the radar device 10, the size of the radar beam area that can be covered at the maximum detection distance is calculated based on the azimuth angle supported by one radar beam and the beam size in the elevation direction. . For example, if a rectangle corresponding to 1.5° in the azimuth direction and 5.0° in the elevation direction is assumed as the size of one radar beam, the coverage in the azimuth and elevation directions is shown in the table when overlapping between the radar beams is not considered. Same as (a) (b) in 1 (unit: m).

동안은 4 개의 레이더 셀(CELL) 범위 내에 존재하게 된다.

는 표적에 대한 탐지 시간을 고려하여 결정이 되지만, 3 km 거리에서 레이더 셀(CELL)의 공간 넓이(dimension)가 방위각 방향으로 약 79 m 이고 고각 방향으로 약 262 m 인 점을 고려하면, 4 개의 레이더 셀(CELL)의 범위는 표 1의 (c)(d)와 같이 약 157 m x 524 m 를 커버해야 한다.Next, referring to FIG. 10, in order to set the detection window W in consideration of the moving direction of the unmanned aerial vehicle, the number of radar cells (CELL) to be included is determined, and the total ROI range of the radar cell (CELL) is calculated. do. For example, when using information on the direction of movement of an unmanned aerial vehicle for a radar beam of 1.5° in the azimuth direction and 5.0° in the elevation direction, the unmanned aerial vehicle at any point may move in any direction.

During the period, it is within the range of four radar cells (CELL).

Is determined in consideration of the detection time for the target, but considering that the spatial dimension of the radar cell at a distance of 3 km is about 79 m in the azimuth direction and about 262 m in the elevation direction, four The range of the radar cell (CELL) should cover about 157 mx 524 m as shown in Table 1 (c) (d).

Next, referring to FIGS. 11 and 12, when the aspect ratio of 4:3 is based on an industrial camera using a general camera sensor, when the aspect ratio is changed and used vertically, it has a coverage of two cells in the elevation direction. The camera sensor has about 4 cell coverage in the azimuth direction (4 x 2). Accordingly, the actual detection window W has a shape as shown in FIG. 11. In particular, since it is not possible to know the exact location of the unmanned aerial vehicle within the radar cell (CELL), it may be efficient to acquire an image and perform a detection algorithm by setting an area as shown in FIG. 12 when setting the detection window (W). .

Thereafter, focal lengths that can be candidates may be calculated based on the minimum detectable Pixels on Target (PoT), and a focal length that satisfies the previously calculated coverage may be finally selected as the initial focal length. For example, a focal length of 255 mm may be required to secure an ROI of 4 times in the azimuth direction determined previously and 2 times in the elevation direction. Table 2 below shows the PoT size and coverage according to the focal length based on 3 km.

According to the embodiments of the present invention described so far, it is possible to increase the detection speed and quality of an unmanned aerial vehicle by operating together several sensors such as a radar, an optical sensor, and a depth information extraction sensor. Accordingly, it is possible to improve the recognition quality of the unmanned aerial vehicle, improve the tracking performance of the unmanned aerial vehicle, and further accurately determine whether the detected unmanned aerial vehicle is illegal.

13 is a diagram illustrating a computing system according to an embodiment of the present invention.

Referring to FIG. 13, the radar device 10, the operating device 20, and the target detection device 30 according to various embodiments of the present disclosure may be implemented as a computing system 4000.

The computer system 4000 includes at least one of a processor 410, a memory 430, a user interface input device 440, a user interface output device 450, and a storage device 460 communicating through a bus 420. can do. Computer system 4000 may also include a network interface 470 that is electrically connected to a network. The network interface 470 may transmit or receive signals with other entities through a network.

The processor 410 may be a central processing unit (CPU) or any semiconductor device that executes instructions stored in the memory 430 or the storage device 460. The processor 410 may be configured to implement the functions and methods described in FIGS. 1 to 12.

The memory 430 and the storage device 460 may include various types of volatile or nonvolatile storage media. For example, the memory may include a read only memory (ROM) 531 and a random access memory (RAM) 432. In an embodiment of the present invention, the memory 430 may be located inside or outside the processor 410, and the memory 430 may be connected to the processor 410 through various known means.

In addition, at least some of the functions of the radar device 10, the operating device 20, and the target detection device 30 according to various embodiments of the present invention may be implemented as a program or software executed in the computing system 4000, , The program or software may be stored in a computer-readable medium.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and ordinary knowledge in the technical field to which the present invention belongs, using the basic concept of the present invention defined in the following claims. Various modifications and improved forms of those who have are also within the scope of the present invention.

Claims (1)

A radar device for detecting a target using a radar signal and generating target information for the target;
A target detection device having multiple sensors and tracking the target by operating the multiple sensors using the target information; And
An operating device that receives the target information from the radar device and delivers the target information to the target detection device according to a predetermined policy
Including,
The initial focal length of the multi-sensor is based on the beam size in the azimuth and elevation directions supported by one radar beam emitted from the radar device, and calculates the entire ROI range of the radar cell, and detects the minimum possible Pixels on Target It is determined by selecting a focal length that satisfies the entire ROI range from among the candidate focal lengths calculated based on ),
The radar device updates the target information according to a predetermined period, and the target detection device adjusts the focal length of the multiple sensors by reflecting the target size, target speed, and target distance of the updated target information. system.

Images