CN112837343B - Low-altitude unmanned-machine prevention and control photoelectric early warning identification method and system based on camera array - Google Patents
Low-altitude unmanned-machine prevention and control photoelectric early warning identification method and system based on camera array Download PDFInfo
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Abstract
The invention discloses a low-altitude unmanned-control photoelectric early warning identification method and system based on a camera array. Thereby utilize the mode that distributed deployment and revolving stage photoelectricity cruise and combine to carry out unmanned aerial vehicle and detect, fix a position through two mesh cameras and acquire the distance information of target, turn into longitude and latitude and altitude information with target information for guide revolving stage photoelectricity unmanned aerial vehicle detects the accurate target of tracking module, enlarged the scope of scanning, and improved the detection rate of unmanned aerial vehicle target.
Description
Technical Field
The invention relates to the technical field of anti-unmanned aerial vehicles, in particular to a low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method and system based on a camera array.
Background
The flight target detection method has great significance in military affairs and civil affairs. The traditional flight target detection is mainly realized by means of radar, but the radar detection has the defects of blind areas, easiness in interference and the like. With the rapid development of unmanned aerial vehicle technology, various novel aircrafts emerge endlessly, and especially unmanned aerial vehicles which are popular in recent years have the characteristics of low flying height, low flying speed, small flying volume and the like, and the characteristic of low flying speed and small flying speed brings certain difficulty for the detection of unmanned aerial vehicles, and the traditional radar is difficult to identify such small targets due to the influence of ground radar clutter. In addition, in a civil aviation airport area, due to the influence of electromagnetic control, active equipment such as radars and the like are forbidden to be used in an anti-unmanned aerial vehicle system, so that the early warning system for detecting and tracking the unmanned aerial vehicle through passive equipment is very important.
Disclosure of Invention
The invention aims to overcome the technical defects and provides a low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method and system based on a camera array.
In order to achieve the technical purpose, a first aspect of the technical scheme of the invention provides a low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method based on a camera array, which comprises the following steps:
acquiring camera internal parameter information in a distributed binocular camera array, and performing distortion correction on an image acquired by a camera according to the camera internal parameter information;
converting the image acquired by the camera into a binary image by using a frame difference method, judging a connected domain in the binary image, eliminating noise or background interference, and marking the remaining suspected target connected domain as a foreground region;
matching a foreground region in an image acquired by one camera in the binocular camera set with a foreground region in another camera in the camera set respectively, calculating absolute position information of a matching target point relative to a camera mounting point according to the position information of the matching target point relative to the camera mounting point, and converting the absolute position information into longitude and latitude and height information;
and sending the longitude and latitude and height information of the matched target point to the turntable photoelectric unmanned detection tracking module, and carrying out target identification and tracking on the corresponding position by the turntable photoelectric unmanned detection tracking module according to the received longitude and latitude and height information.
The invention provides a low-altitude unmanned-control photoelectric early warning identification system based on a camera array, which comprises the following functional modules:
the internal parameter correction module is used for acquiring internal parameter information of cameras in the distributed binocular camera array and performing distortion correction on images acquired by the cameras according to the internal parameter information of the cameras;
the connected domain judging module is used for converting the image acquired by the camera into a binary image by using a frame difference method, judging the connected domain in the binary image, eliminating noise or background interference, and marking the remaining suspected target connected domain as a foreground region;
the area matching calculation module is used for matching a foreground area in an image acquired by one camera in the binocular camera set with a foreground area in the other camera in the camera set respectively, calculating absolute position information of a matching target point relative to a camera mounting point according to the position information of the matching target point relative to the camera mounting point, and converting the absolute position information into longitude and latitude and height information;
and the target identification tracking module is used for sending the longitude and latitude and height information of the matched target point to the turntable photoelectric unmanned detection tracking module, and the turntable photoelectric unmanned detection tracking module carries out target identification and tracking on the corresponding position according to the received longitude and latitude and height information.
The invention provides a server, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of the camera array-based low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method.
A fourth aspect of the present invention provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method for identifying a low-altitude unmanned aerial vehicle prevention and control photoelectric early warning based on a camera array are implemented.
Compared with the prior art, the unmanned aerial vehicle detection method has the advantages that the characteristic of low cost of the camera is utilized, the unmanned aerial vehicle detection is carried out by adopting a mode of combining distributed deployment and turntable photoelectric cruising, the distance information of the target is obtained by positioning through the binocular camera, the target information is converted into longitude and latitude and height information to guide the turntable photoelectric unmanned aerial vehicle detection tracking module to accurately track the target, the defect that the scanning range of the turntable photoelectric unmanned aerial vehicle detection tracking module is small at the same moment is overcome, the scanning range is expanded, in addition, the camera is fixedly deployed, the background change in video data is small, the small target and the target with unclear characteristics are sensitive, and the detection rate of the unmanned aerial vehicle target is improved.
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Fig. 1 is a flow chart of a low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method based on a camera array according to an embodiment of the invention;
FIG. 2 is a flowchart of steps of a low altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method based on a camera array according to an embodiment of the present invention;
FIG. 3 is a block flow diagram of a substep of step S2 of FIG. 1;
FIG. 4 is a block diagram of the flow of steps S3 of FIG. 1;
fig. 5 is a block diagram of a low-altitude unmanned aerial vehicle prevention and control photoelectric early warning recognition system based on a camera array according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1 and fig. 2, an embodiment of the present invention provides a low altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method based on a camera array, which includes the following steps:
s1, camera internal parameter information in a distributed binocular camera array is obtained, and distortion correction is carried out on images obtained by a camera according to the camera internal parameter information.
Specifically, the cameras are distributed, namely two cameras which are located at the same horizontal height and obliquely point to the sky and have a distance interval of about 1 m are marked as a camera set, and meanwhile, a plurality of camera sets of the type are deployed along the early warning edge area until the field range of the cameras can completely cover the whole early warning area.
And then enabling the camera to shoot a plurality of continuous calibration plate images, processing the calibration plate images by utilizing an OpenCV calibration interface to obtain camera internal parameter information such as a camera distortion matrix, an intrinsic matrix, a basic matrix and the like, and loading the camera internal parameter information through the OpenCV correction interface to perform distortion correction on the images acquired by the camera.
And S2, converting the image acquired by the camera into a binary image by using a frame difference method, judging a connected region in the binary image, eliminating noise or background interference, and marking the remaining suspected target connected region as a foreground region.
As shown in fig. 3, the step S2 includes the following sub-steps:
s21, processing two continuous-shot images of each camera by using a frame difference method, and storing an obtained frame difference result in a frame difference matrix;
s22, traversing the frame difference matrix, and enabling the numerical absolute value in the frame difference matrix to be larger than a set threshold value N 1 The gray value of the pixel point is set to be 255, otherwise, the gray value is set to be 0, and a binary image of a frame difference result is obtained;
s23, marking a region with the gray value of 255 in the binary image as a connected domain, taking the number of pixels with the gray value of 255 in each connected domain as the area of the connected domain, and taking the mean value of horizontal and vertical coordinates of all the pixels as the centroid of the connected domain;
s24, judging the area of each connected domain, and enabling the area to be smaller than a set threshold value N 2 And the target is regarded as noise or background interference, and the remaining suspected target connected region after the noise or background interference is eliminated is marked as a foreground region.
And S3, respectively matching a foreground region in an image acquired by one camera in the binocular camera set with a foreground region in the other camera in the camera set, calculating absolute position information of the matching target point relative to the camera mounting point according to the position information of the matching target point relative to the camera mounting point, and converting the absolute position information into longitude, latitude and height information.
As shown in fig. 4, the step S3 includes the following sub-steps:
s31, traversing a foreground region in one camera in the camera set, finding a matched foreground region in the other camera in the camera set according to the area proportion, and taking the mass centers of two foreground regions which are matched with each other as matching target points;
s32, calculating to obtain a horizontal angle and a vertical angle of the target relative to the camera by combining the coordinate of the matched target point in the image, the horizontal field angle and the vertical field angle of the camera and the horizontal imaging resolution and the vertical imaging resolution of the camera;
s33, further obtaining an absolute horizontal angle and a vertical angle of the matched target point relative to the installation point of the camera based on the absolute angle of the installation of the camera and the inclination angle of the camera relative to the horizontal ground, and calculating the distance between the matched target point and the camera and the height of the matched target point;
and S34, converting the distance, the direction and the height information of the matched target point relative to the camera into longitude and latitude and height information for guiding the detection and tracking module of the photoelectric unmanned aerial vehicle of the rotary table to accurately identify.
Specifically, traverse the foreground region R in one of the cameras in the set of cameras i Area size M i Foreground region R found in another camera in the camera group j Size of area M j When it comes to
And then, considering the two areas as matching areas, and taking the centroids of the two matching foreground areas as matching target points. In addition, when a plurality of foreground areas matched with the areas of the foreground areas exist in the other camera, the area is considered to have a plurality of matching areas, a plurality of matching target points also exist in the corresponding centroid, and the following calculation is carried out on the plurality of matching target points; and when the other camera does not have the matched foreground area, forcibly matching the foreground area of one camera in the camera group with all the unmatched foreground areas in the other camera in the camera group respectively, and performing the following calculation on all the forcibly matched target points.
Setting the horizontal and vertical field angles of the camera
And
resolution of imaging W i *H i The coordinate of the current matching target point in the image is (x) i ,y i ) And calculating to obtain the horizontal angle of the target relative to the camera
And a vertical angle
Wherein
And a vertical angle
Based on absolute angle of installation and relative level ground inclination
And
further obtaining the absolute horizontal angle of the matched target point relative to the installation point of the camera
And a vertical angle
In the same way, the absolute horizontal angle of the other camera in the camera set is obtained
And a vertical angle
Knowing that the installation height of the current camera group is h and the interval between the cameras is d, calculating the distance between the matched target point and the camera as
Matching the height of the target point to
And converting the calculated distance, direction and height information into longitude, latitude and height information for guiding the turntable photoelectric unmanned aerial vehicle detection tracking module to perform accurate identification.
And S4, sending the longitude and latitude and height information of the matched target point to the turntable photoelectric unmanned detection tracking module, and carrying out target identification and tracking on the corresponding position by the turntable photoelectric unmanned detection tracking module according to the received longitude and latitude and height information.
Specifically, when the detection and tracking module of the turntable photoelectric unmanned aerial vehicle does not receive longitude and latitude and height information of a matching target point sent by a binocular camera group, namely in a normal state, the detection and tracking module of the turntable photoelectric unmanned aerial vehicle horizontally rotates at a constant angular speed, and uses a short-focus lens to scan back and forth from bottom to top vertically after rotating a set angle, an OpenCV local threshold segmentation method is used for judging whether an area with abnormal gray scale exists in the scanned image, if the area with abnormal gray scale is not found, the set angle is continuously rotated to perform scanning judgment back and forth from top to bottom, and the process is repeated to scan a semicircular area in the air; if the gray scale abnormal area exists, calling the telephoto lens to amplify the abnormal area, identifying the amplified image, finishing the automatic scanning state and taking the identified abnormal area as an initial position when the identification result is that the unmanned aerial vehicle is in the state of the unmanned aerial vehicle, and tracking the position of the abnormal area in photoelectricity in real time by using a kcf filtering algorithm in OpenCV (open channel vision correction for vision) to realize the continuous capture of the target of the unmanned aerial vehicle by the telephoto lens; the photoelectric unmanned aerial vehicle detection tracking module of the turntable identifies the gray abnormal area of the shot image in real time through a YOLOV4 identification network and judges whether an unmanned aerial vehicle exists in the area.
When the photoelectric unmanned aerial vehicle detection tracking module of the rotary table receives a guiding instruction which is sent by a binocular camera set and contains longitude and latitude and height information of a matched target point, firstly, whether the photoelectric unmanned aerial vehicle detection tracking module of the rotary table is in a tracking state is judged, if the photoelectric unmanned aerial vehicle detection tracking module of the rotary table is in the tracking state, the guiding instruction is stored into a message queue, and the photoelectric unmanned aerial vehicle detection tracking module waits for the completion of the tracking state; if the photoelectric unmanned aerial vehicle detection tracking module of the rotary table is not in a tracking state, the guiding information in the message queue is taken out, the long-focus lens is controlled to move to the designated direction and pitch, the image of the position to which the long-focus lens belongs is shot, target recognition is carried out on the shot image through a YOLOV4 recognition network, when the recognition result is that the unmanned aerial vehicle belongs, the short-focus lens is utilized to continuously track and capture the unmanned aerial vehicle, and otherwise, the position to which the next longitude latitude and height information belongs is continuously recognized and judged.
The low-altitude unmanned-machine prevention and control photoelectric early warning and recognition method based on the camera array utilizes the characteristic of low cost of the camera, adopts a mode of combining distributed deployment and turntable photoelectric cruise to detect the unmanned aerial vehicle, obtains the distance information of the target by positioning through a binocular camera, converts the target information into longitude, latitude and height information, is used for guiding the turntable photoelectric unmanned aerial vehicle detection and tracking module to accurately track the target, avoids the defect that the scanning range of the turntable photoelectric unmanned aerial vehicle detection and tracking module is small at the same time, enlarges the scanning range, and the camera adopts fixed deployment, has small background change in video data, is sensitive to small targets and targets with unclear characteristics, and improves the detection rate of the unmanned aerial vehicle targets.
As shown in fig. 5, the embodiment of the present invention further discloses a low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification system based on a camera array, which includes the following functional modules:
the internal parameter correction module 10 is used for acquiring internal parameter information of cameras in the distributed binocular camera array and performing distortion correction on images acquired by the cameras according to the internal parameter information of the cameras;
a connected domain determining module 20, configured to convert the image obtained by the camera into a binarized image by using a frame difference method, determine a connected domain in the binarized image, eliminate noise or background interference, and mark the remaining suspected target connected domain as a foreground region;
the area matching calculation module 30 is configured to match a foreground area in an image acquired by one of the cameras in the binocular camera group with a foreground area in another of the cameras in the camera group, calculate absolute position information of a matching target point relative to a camera mounting point according to position information of the matching target point relative to the camera mounting point, and convert the absolute position information into longitude and latitude and height information;
and the target identification tracking module 40 is used for sending the longitude and latitude and height information of the matched target point to the turntable photoelectric unmanned detection tracking module, and the turntable photoelectric unmanned detection tracking module carries out target identification and tracking on the corresponding position according to the received longitude and latitude and height information.
The execution mode of the low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification system based on the camera array in this embodiment is basically the same as that of the low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method based on the camera array, and therefore, detailed description is omitted.
The server in this embodiment is a device providing computing services, and generally refers to a computer with high computing power and provided for multiple consumers to use through a network. The server of this embodiment includes: a memory including an executable program stored thereon, a processor, and a system bus, it will be understood by those skilled in the art that the terminal device structure of the present embodiment does not constitute a limitation of the terminal device, and may include more or less components than those shown, or some components in combination, or a different arrangement of components.
The memory may be used to store software programs and modules, and the processor may execute various functional applications of the terminal and data processing by operating the software programs and modules stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the terminal, etc. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The memory contains an executable program of the low-altitude unmanned-machine prevention and control photoelectric early warning identification method based on the camera array, the executable program can be divided into one or more modules/units, the one or more modules/units are stored in the memory and are executed by the processor to complete the information acquisition and implementation process, and the one or more modules/units can be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used for describing the execution process of the computer program in the server. For example, the computer program may be partitioned into an internal reference rectification module, a connected domain determination module, a region matching calculation module, and a target recognition and tracking module.
The processor is a control center of the server, connects various parts of the whole terminal device by various interfaces and lines, and performs various functions of the terminal and processes data by running or executing software programs and/or modules stored in the memory and calling data stored in the memory, thereby integrally monitoring the terminal. Alternatively, the processor may include one or more processing units; preferably, the processor may integrate an application processor, which mainly handles operating systems, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor.
The system bus is used to connect functional units in the computer, and can transmit data information, address information and control information, and the types of the functional units can be PCI bus, ISA bus, VESA bus, etc. The system bus is responsible for data and instruction interaction between the processor and the memory. Of course, the system bus may also access other devices such as network interfaces, display devices, etc.
The server at least includes a CPU, a chipset, a memory, a disk system, and the like, and other components are not described herein again.
In the embodiment of the present invention, the executable program executed by the processor included in the terminal specifically includes: a low-altitude unmanned-control photoelectric early warning and identifying method based on a camera array comprises the following steps:
acquiring camera internal parameter information in a distributed binocular camera array, and performing distortion correction on an image acquired by a camera according to the camera internal parameter information;
converting the image acquired by the camera into a binary image by using a frame difference method, judging a connected region in the binary image, eliminating noise or background interference, and marking the remaining suspected target connected region as a foreground region;
matching a foreground region in an image acquired by one camera in the binocular camera set with a foreground region in the other camera in the camera set, calculating absolute position information of a matching target point relative to a camera mounting point according to position information of the matching target point relative to the camera mounting point, and converting the absolute position information into longitude and latitude and height information;
and sending the longitude and latitude and height information of the matched target point to the turntable photoelectric unmanned detection tracking module, and carrying out target identification and tracking on the corresponding position by the turntable photoelectric unmanned detection tracking module according to the received longitude and latitude and height information.
It can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the modules, elements, and/or method steps of the various embodiments described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A low-altitude unmanned-machine prevention and control photoelectric early warning identification method based on a camera array is characterized by comprising the following steps:
acquiring camera internal parameter information in a distributed binocular camera array, and performing distortion correction on an image acquired by a camera according to the camera internal parameter information;
converting the image acquired by the camera into a binary image by using a frame difference method, judging a connected region in the binary image, eliminating noise or background interference, and marking the remaining suspected target connected region as a foreground region;
matching a foreground region in an image acquired by one camera in the binocular camera set with a foreground region in the other camera in the camera set, calculating absolute position information of a matching target point relative to a camera mounting point according to position information of the matching target point relative to the camera mounting point, and converting the absolute position information into longitude and latitude and height information; the method comprises the following steps:
traversing a foreground region in one camera in the camera set, finding a matched foreground region in the other camera in the camera set according to the area proportion, and taking the mass centers of the two foreground regions which are matched with each other as matching target points;
calculating to obtain a horizontal angle and a vertical angle of the target relative to the camera by combining the coordinates of the matched target point in the image, the horizontal field angle and the vertical field angle of the camera and the horizontal imaging resolution and the vertical imaging resolution of the camera;
further obtaining an absolute horizontal angle and a vertical angle of a matching target point relative to a camera installation point based on the camera installation absolute angle and the camera inclination angle relative to the horizontal ground, and calculating the distance between the matching target point and the camera and the height of the matching target point;
converting the distance, the direction and the height information of the matched target point relative to the camera into longitude and latitude and height information for guiding the detection and tracking module of the turntable photoelectric unmanned aerial vehicle to carry out accurate identification;
and sending the longitude and latitude and height information of the matched target point to the turntable photoelectric unmanned detection tracking module, and carrying out target identification and tracking on the corresponding position by the turntable photoelectric unmanned detection tracking module according to the received longitude and latitude and height information.
2. The camera array-based low-altitude unmanned aerial vehicle prevention and control photoelectric early warning and recognition method according to claim 1, wherein the acquiring of camera intrinsic parameter information in the distributed binocular camera array and the distortion correction of the camera acquired image according to the camera intrinsic parameter information comprises:
and processing the calibration board image by using the OpenCV calibration interface to obtain the internal parameter information of the camera, and loading the internal parameter information of the camera through the OpenCV correction interface to perform distortion correction on the image acquired by the camera.
3. The camera array-based low-altitude unmanned aerial vehicle prevention and control photoelectric early warning and identification method as claimed in claim 1, wherein the camera-acquired image is converted into a binarized image by using a frame difference method, connected regions in the binarized image are judged, noise or background interference is eliminated, and the remaining suspected target connected regions are marked as foreground regions; the method comprises the following steps:
processing two continuous-shot images of each camera by using a frame difference method, and storing an obtained frame difference result in a frame difference matrix;
traversing the frame difference matrix, and enabling the numerical value absolute value in the frame difference matrix to be larger than a set threshold value N 1 Setting the gray value of the pixel point to be 255, otherwise, setting the gray value of the pixel point to be 0, and obtaining a binary image of a frame difference result;
marking a region with a gray value of 255 in a binary image as a connected domain, taking the number of pixels with the gray value of 255 in each connected domain as the area of the connected domain, and taking the mean value of horizontal and vertical coordinates of all the pixels as the centroid of the connected domain;
judging the area of each connected domain, and enabling the area to be smaller than a set threshold value N 2 And the target is regarded as noise or background interference, and the remaining suspected target connected region after the noise or background interference is eliminated is marked as a foreground region.
4. The camera array-based low-altitude unmanned aerial vehicle prevention and control photoelectric early warning and recognition method according to claim 1, wherein the foreground region in the image acquired by one of the cameras in the binocular camera group is respectively matched with the foreground region in the other camera in the camera group, and the method further comprises the following two conditions:
when a plurality of foreground regions matched with the areas of the other camera exist in the other camera, the region is considered to have a plurality of matching regions, a plurality of matching target points also exist in the corresponding mass center, and the plurality of matching target points are calculated;
and when the other camera does not have the matched foreground area, forcibly matching the foreground area of one camera in the camera group with all the unmatched foreground areas in the other camera in the camera group respectively, and calculating all the forcibly matched target points.
5. The camera array-based low-altitude unmanned aerial vehicle prevention and control photoelectric early warning and identification method as claimed in claim 1, wherein the target identification and tracking of the corresponding position by the turntable photoelectric unmanned aerial vehicle detection and tracking module according to the received longitude and latitude and height information comprises:
the turntable photoelectric unmanned aerial vehicle detects longitude and latitude and height information received by the tracking module, controls the telephoto lens to move to a specified position and pitch, and shoots an image of the position to which the telephoto lens belongs;
and carrying out target recognition on the shot image, when the recognition result is that the unmanned aerial vehicle is used, continuously tracking and capturing the unmanned aerial vehicle by using the short-focus lens, and otherwise, continuously recognizing and judging the position of the next longitude latitude and height information.
6. The camera array-based low-altitude unmanned aerial vehicle prevention and control photoelectric early warning identification method according to claim 1, wherein the turntable photoelectric unmanned aerial vehicle detection and tracking module identifies a gray abnormal area of an image shot by the turntable photoelectric unmanned aerial vehicle detection and tracking module in real time through a YOLOV4 identification network, and judges whether an unmanned aerial vehicle exists in the area.
7. The low-altitude unmanned-machine prevention and control photoelectric early warning and recognition system based on the camera array is characterized by comprising the following functional modules:
the internal parameter correction module is used for acquiring internal parameter information of cameras in the distributed binocular camera array and carrying out distortion correction on images acquired by the cameras according to the internal parameter information of the cameras;
the connected domain judging module is used for converting the image acquired by the camera into a binary image by using a frame difference method, judging the connected domain in the binary image, eliminating noise or background interference, and marking the remaining suspected target connected domain as a foreground region;
the area matching calculation module is used for matching a foreground area in an image acquired by one camera in the binocular camera set with a foreground area in the other camera in the camera set respectively, calculating absolute position information of a matching target point relative to a camera mounting point according to the position information of the matching target point relative to the camera mounting point, and converting the absolute position information into longitude and latitude and height information; the method comprises the following steps:
traversing a foreground region in one camera in the camera set, finding a matched foreground region in the other camera in the camera set according to the area proportion, and taking the mass centers of the two foreground regions which are matched with each other as matching target points;
calculating to obtain a horizontal angle and a vertical angle of the target relative to the camera by combining the coordinate of the matched target point in the image, the horizontal field angle and the vertical field angle of the camera and the horizontal imaging resolution and the vertical imaging resolution of the camera;
further obtaining an absolute horizontal angle and a vertical angle of the matching target point relative to the camera installation point based on the absolute angle of the camera installation and the inclination angle of the camera relative to the horizontal ground, and calculating the distance between the matching target point and the camera and the height of the matching target point;
converting the distance, the direction and the height information of the matched target point relative to the camera into longitude and latitude and height information for guiding the detection and tracking module of the turntable photoelectric unmanned aerial vehicle to carry out accurate identification;
and the target identification tracking module is used for sending the longitude and latitude and height information of the matched target point to the turntable photoelectric unmanned detection tracking module, and the turntable photoelectric unmanned detection tracking module carries out target identification and tracking on the corresponding position according to the received longitude and latitude and height information.
8. A server comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program implements the steps of the camera array based low altitude unmanned aerial vehicle electro-optical early warning recognition method according to any one of claims 1 to 6.
9. A computer-readable storage medium, in which a computer program is stored, wherein the computer program, when being executed by a processor, implements the steps of the method for identifying low altitude unmanned electro-optical warning device based on camera array as claimed in any one of claims 1 to 6.
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