Method and system for remotely adjusting rotating speed of communication antenna motor

Abstract

The invention belongs to the technical field of remote adjustment, and particularly relates to a communication antenna motor rotating speed remote adjustment method and system.The method comprises the steps that an unmanned aerial vehicle collects videos and transmits the videos to a receiving end, and the receiving end determines analysis areas of two adjacent frames of images according to flight parameters of the unmanned aerial vehicle when the two adjacent frames of images are collected; according to rated parameters of the unmanned aerial vehicle, flight parameters of the unmanned aerial vehicle when each frame of image is collected and environmental data, determining a jitter degree when the unmanned aerial vehicle collects each frame of image, and determining a size of a judgment window of pixel points in each frame of image according to the jitter degree; and the adjusting module is used for obtaining the minimum value of the characteristic difference with the analysis pixel points from the judgment window as the noise degree, and adjusting the motor rotating speed of the communication antenna of the receiving end according to the sum of the noise degrees of all the analysis pixel points in the analysis areas of all the frame images in the video. According to the invention, fine adjustment of the rotating speed of the motor is realized so as to ensure optimal transmission and reception of signals.

Description

Technical Field

[0001] The present invention relates to the technical field of remote adjustment. More specifically, the present invention relates to a method and system for remotely adjusting the rotation speed of a communication antenna motor. Background Art

[0002] An unmanned aerial vehicle (UAV), that is, an unpiloted aircraft, is a flying vehicle without a pilot on board, which performs various tasks in the air through remote control or autonomous control. With the progress of technology and the expansion of application fields, UAVs are gradually applied in the civilian field, including aerial photography, agriculture, logistics, environmental monitoring, disaster relief and other aspects.

[0003] Among them, the video transmission between the UAV and the receiving end mainly relies on wireless communication technologies, including 4G network and 5G network. In the application scenarios of 4G network and 5G network, the motor plays a crucial role, especially in antenna positioning and direction adjustment. The motor enables the antenna to automatically adjust its pointing to maximize the signal reception and transmission efficiency. This automatic adjustment is very important for ensuring the reliability and stability of the communication network, especially in complex environments and extreme weather conditions. Among them, the speed of the motor will affect the response speed and tracking accuracy of the antenna. A fast motor speed can achieve fast beam switching and direction adjustment, thereby improving the communication efficiency and the continuity of signal reception, and reducing the noise in the video received by the receiving end.

[0004] Although a fast motor speed can improve the response speed and tracking accuracy of the antenna, thereby improving the communication efficiency and the continuity of signal reception to a certain extent, keeping the motor running at a high speed all the time will increase the mechanical wear of the motor and reduce the service life of the motor. Therefore, it is necessary to reasonably select the operating speed of the motor according to specific application scenarios and requirements, on the premise of ensuring the stability and performance of the system. This requires the receiving end to have the ability to more finely adjust the motor speed to ensure the optimal transmission and reception of signals. Summary of the Invention

[0005] To solve the above technical problem that the receiving end is required to have the ability to more finely adjust the motor speed to ensure the optimal transmission and reception of signals, the present invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides a method for remotely adjusting the rotation speed of a communication antenna motor, including: collecting video by a UAV and transmitting it to a receiving end, where the video includes multiple frames of images; for the receiving end, according to the flight altitude of the UAV when collecting two adjacent frames of images, determining the corresponding relationship between the sizes of the analysis regions of the two adjacent frames of images and recording it as ; according to the flight direction, flight speed and size correspondence of the drone when collecting two adjacent frames of images , determine the position coordinate correspondence of the analysis regions of two adjacent frames of images for obtaining the analysis regions of two adjacent frames of images; according to the rated parameters of the drone, the flight parameters of the drone when collecting each frame of image and the environmental data, determine the jitter degree of the drone when collecting each frame of image; adjust the preset size according to the jitter degree to obtain the size of the judgment window of the pixel points in each frame of image and denote it as ; according to the position coordinate correspondence of the analysis regions of two adjacent frames of images, obtain any analysis pixel point in the analysis region of the previous frame of image and the corresponding analysis pixel point in the analysis region of the subsequent frame of image ; take the region centered on the analysis pixel point and with a size of as the judgment window of the analysis pixel point , calculate the feature differences between each analysis pixel point in the judgment window and the analysis pixel point , and denote the smallest feature difference as the noise degree of the analysis pixel point ; adjust the motor speed of the communication antenna at the receiving end according to the sum of the noise degrees of all analysis pixel points in the analysis regions of all frames of images in the video.

[0007] In the present invention, the receiving end analyzes the received video to eliminate the jitter interference during the video collection by the drone, accurately obtains the noise degree of the transmission line between the drone and the receiving end, and then adjusts the motor speed of the communication antenna at the receiving end according to the noise degree of the transmission line, realizing the refined adjustment of the motor speed to ensure the optimal transmission and reception of signals; among them, by selecting the smallest feature difference from the feature differences between all analysis pixel points in the judgment window of the analysis pixel point and the analysis pixel point and denoting it as the noise degree of the analysis pixel point , the jitter interference caused by various reasons during the video collection by the drone is eliminated, and then the noise degree of the transmission line between the drone and the receiving end is accurately obtained.

[0008] Preferably, the size correspondence of the analysis regions of the two adjacent frames of images , is the flight altitude of the drone when collecting the previous frame of image in two adjacent frames of images, and

[0009] is the flight altitude of the drone when collecting the subsequent frame of image in two adjacent frames of images. The pixel points, and the position coordinates of the corresponding pixel points in the subsequent frame image are , The relational expression satisfied is: ; ; Among them, , are respectively the flight direction and flight speed of the drone when collecting the subsequent frame image in two adjacent frames of images, is the time interval for collecting two adjacent frames of images, represents taking the absolute value, is the floor function.

[0010] When the present invention determines the corresponding relationship of the position coordinates of the analysis regions of two adjacent frames of images, the flight speed, flight altitude and flight direction of the drone provide an important reference basis for accurately determining the analysis regions of two adjacent frames of images. By comprehensively considering these parameters, the movement and change of the actual object in the image can be predicted more accurately, thereby optimizing the effect of image analysis.

[0011] Preferably, obtaining the analysis regions of two adjacent frames of images includes: obtaining the corresponding pixel points in the subsequent frame image for each pixel point in the previous frame image according to the corresponding relationship of the position coordinates of the analysis regions of two adjacent frames of images; for any pixel point in the previous frame image, when the abscissa of the corresponding pixel point of this pixel point in the subsequent frame image is within and the ordinate is within , this pixel point is used as the analysis pixel point in the previous frame image, and are respectively the length and width of each frame of image; all the analysis pixel points in the previous frame image form the analysis region of the previous frame image; the pixel points corresponding to the four vertices in the analysis region of the previous frame image in the subsequent frame image are used as the four vertices of the subsequent frame image, and the rectangular region enclosed by the four vertices of the subsequent frame image is used as the analysis region of the subsequent frame image.

[0012] Preferably, the rated parameters of the drone include the maximum flight speed , maximum flight altitude and wind resistance of the drone, the flight parameters of the drone include flight speed and flight altitude , and the environmental data refers to wind speed , the wind speed is collected by an anemometer carried by the drone, and the wind speed refers to the wind speed at the flight altitude of the drone.

[0013] Preferably, the calculation formula for the jitter degree of the drone when collecting each frame of image is: ; In the formula, is the jitter degree of the drone when collecting this frame of image, , are respectively the flight speed and flight height of the drone when collecting this frame of image, , are respectively the maximum flight speed and maximum flight height of the drone, is the wind speed when collecting this frame of image, is the wind resistance of the drone, represents taking the maximum value, is the natural exponential function, is a preset parameter.

[0014] The present invention calculates the jitter degree of the drone when collecting each frame of image by collecting the ratio of the flight parameters and environmental data of the drone when collecting each frame of image to the rated parameters of the drone, and is used to quantify the image stability of the drone under different flight conditions, and is used to exclude jitter interference when calculating the noise degree of the image in the subsequent calculation.

[0015] Preferably, the calculation formula of the is: ; In the formula, is the jitter degree of the drone when collecting this frame of image, is a preset length, is the floor function, is the preset size, is a preset length.

[0016] Preferably, the characteristic difference between each analysis pixel point in the calculation judgment window and the analysis pixel point includes: ; In the formula, is the characteristic difference between the th analysis pixel point in the judgment window of the analysis pixel point and the analysis pixel point , , are respectively the gray value and LBP feature of the analysis pixel point , , are respectively the gray values of the th analysis pixel point in the judgment window of the analysis pixel point , is the Hamming distance.

[0017] In the present invention, the difference in the gray values of two analysis pixel points reflects the brightness change of the two analysis pixel points, while the difference in the LBP features of the two analysis pixel points reflects the local texture change of the two analysis pixel points. By combining the difference in gray values and the difference in LBP features, the feature differences between the two analysis pixel points can be more comprehensively described.

[0018] Preferably, adjusting the motor speed of the communication antenna at the receiving end includes: taking the average value of the feature differences of all analysis pixel points in the analysis area of each frame of image as the noise level of each frame of image; taking the average value of the noise levels of all frames of images in the video as the noise level of the transmission line between the drone and the receiving end; then the motor speed of the communication antenna at the receiving end after adjustment The calculation formula is: ; In the formula, is the noise level of the transmission line between the drone and the receiving end, is the motor speed of the communication antenna at the receiving end, is the noise threshold.

[0019] When the noise level of the transmission line between the drone and the receiving end in the present invention is greater than or equal to the noise threshold , increase the motor speed of the communication antenna at the receiving end to improve the communication efficiency and the continuity of signal reception, so as to ensure the optimal transmission and reception of signals; when the noise level of the transmission line between the drone and the receiving end is less than the noise threshold , no longer increase the motor speed of the communication antenna at the receiving end to avoid increasing the mechanical wear of the motor and extend the service life of the motor.

[0020] In a second aspect, the present invention provides a remote adjustment system for the motor speed of a communication antenna, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned remote adjustment method for the motor speed of a communication antenna is implemented.

[0021] By adopting the above technical solution, the above-mentioned remote adjustment method for the motor speed of a communication antenna is generated into a computer program and stored in the memory to be loaded and executed by the processor, so as to manufacture a terminal device according to the memory and the processor, which is convenient to use.

[0022] The beneficial effects of the present invention are as follows: The receiving end in the present invention analyzes the received video, eliminates the jitter interference during video acquisition by the drone, accurately obtains the noise level of the transmission line between the drone and the receiving end, and then adjusts the motor speed of the communication antenna at the receiving end according to the noise level of the transmission line, realizing the refined adjustment of the motor speed to ensure the optimal transmission and reception of signals; among them, by starting from the analysis pixel points Among all the analyzed pixel points in the judgment window and the analyzed pixel points select the smallest feature difference in the feature differences as the analyzed pixel point of the noise level, and eliminate the jitter interference caused by various reasons when the drone collects the video, so as to accurately obtain the noise level of the transmission line between the drone and the receiving end. Brief Description of the Drawings

[0023] By referring to the following detailed description with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present invention will become readily understandable. In the drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein: Figure 1 is a flowchart schematically showing a method for remotely adjusting the rotation speed of a communication antenna motor in the present invention. Detailed Embodiments

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] The following will describe in detail the specific embodiments of the present invention with reference to the accompanying drawings.

[0026] An embodiment of the present invention discloses a method for remotely adjusting the rotation speed of a communication antenna motor. Referring to Figure 1 it includes steps S1 - S4: S1. Collect video through a drone and transmit it to the receiving end.

[0027] It should be noted that the application of drones plays an important role in many fields: in the military and security fields, the videos collected by drones play an important role in reconnaissance and surveillance, border patrol and monitoring, emergency response, etc.; in the civilian field, the videos collected by drones play an important role in film and television production, tourism and sightseeing, environmental monitoring and protection, infrastructure inspection and maintenance, etc. The role of drones in collecting videos continues to expand with the development of technology and the in-depth application, providing new perspectives and solutions for various fields, greatly enriching the ways of information acquisition and application, and having broad application prospects and important social values.

[0028] Specifically, collect video through a camera carried by the drone. The video includes multiple frames of images, and the size of each frame of image is the same; record the size of each frame of image as , and They are the length and width of each frame of the image respectively.

[0029] Furthermore, in the scenario of collecting videos by drones, the drone serves as the transmitter, and its receiver can be various devices or systems, specifically depending on the application scenario and requirements. Common types of receivers include ground control stations, mobile devices, and remote servers or cloud platforms, etc.

[0030] Among them, the ground control station is the main device for drone operators to conduct flight control and mission management. The video data collected by the drone is usually transmitted to the ground control station in real time for operators to monitor and analyze. The ground control station can be a professional control device or portable devices such as laptops and tablets; in addition, mobile devices such as smartphones and tablets can also serve as receivers. By installing corresponding applications, operators can view the videos collected by the drone in real time on the mobile device. This method is convenient for quickly viewing and sharing video content on-site; secondly, in some application scenarios, the video data collected by the drone is transmitted to a remote server or cloud platform for storage, processing, and analysis. For example, in the fields of security monitoring and environmental monitoring, video data needs to be stored and intelligently analyzed for a long time. The remote server or cloud platform can provide powerful data processing capabilities and storage space.

[0031] Furthermore, the video transmission between the drone and the receiver mainly relies on wireless communication technologies, including 4G networks (the fourth-generation mobile technology) and 5G networks (the fifth-generation mobile technology).

[0032] It should be noted that in the application scenarios of 4G networks and 5G networks, the motor plays a crucial role, especially in antenna positioning and direction adjustment; the motor enables the antenna to automatically adjust its pointing to maximize the signal reception and transmission efficiency. This automatic adjustment is very important for ensuring the reliability and stability of the communication network, especially in complex environments and extreme weather conditions; among them, the speed of the motor affects the response speed and tracking accuracy of the antenna. A fast motor speed can achieve fast beam switching and direction adjustment, thereby improving communication efficiency and the continuity of signal reception, and reducing the noise in the videos received by the receiver.

[0033] It should be further noted that although a fast motor speed can improve the response speed and tracking accuracy of the antenna, thereby improving communication efficiency and the continuity of signal reception to a certain extent, continuously keeping the motor running at a high speed will increase the mechanical wear of the motor and reduce the service life of the motor. Therefore, it is necessary to reasonably select the operating speed of the motor according to the specific application scenario and requirements, on the premise of ensuring system stability and performance. This requires the receiver to have a more refined ability to adjust the motor speed to ensure the optimal transmission and reception of signals.

[0034] In the present invention, the receiving end analyzes the received video, eliminates the jitter interference during video acquisition by the unmanned aerial vehicle (UAV), accurately obtains the noise level of the transmission line between the UAV and the receiving end, and then adjusts the motor speed of the communication antenna of the receiving end according to the noise level of the transmission line, realizing fine adjustment of the motor speed to ensure optimal signal transmission and reception.

[0035] S2. Determine the analysis regions of two adjacent frames of images according to the flight parameters of the UAV when collecting the two adjacent frames of images.

[0036] Specifically, the flight parameters of the UAV include the flight direction , flight speed and flight altitude . Then, determining the analysis regions of two adjacent frames of images according to the flight parameters of the UAV when collecting the two adjacent frames of images includes: determining the size correspondence relationship of the analysis regions of two adjacent frames of images according to the flight altitude of the UAV when collecting the two adjacent frames of images; determining the position coordinate correspondence relationship of the analysis regions of two adjacent frames of images according to the flight direction and flight speed of the UAV when collecting the two adjacent frames of images and the size correspondence relationship of the analysis regions of two adjacent frames of images; and determining the analysis regions of two adjacent frames of images according to the position coordinate correspondence relationship of the analysis regions of two adjacent frames of images, that is, determining the analysis region of the previous frame of image and the analysis region of the subsequent frame of image in the two adjacent frames of images.

[0037] Among them, the size correspondence relationship of the analysis regions of two adjacent frames of images reflects the ratio of the area size of the analysis region of the previous frame of image to the area size of the analysis region of the subsequent frame of image in the two adjacent frames of images. Then, the size correspondence relationship of the analysis regions of two adjacent frames of images , is the flight altitude of the UAV when collecting the previous frame of image in the two adjacent frames of images, and is the flight altitude of the UAV when collecting the subsequent frame of image in the two adjacent frames of images.

[0038] It should be noted that as the UAV flies, the flight altitude of the UAV is constantly changing. According to the law of near-big and far-small, when the flight altitude of the UAV changes from high to low, the size of the corresponding region of the actual object in the subsequent frame of image is larger than the size of the corresponding region of the actual object in the previous frame of image; when the flight altitude of the UAV changes from low to high, the size of the corresponding region of the actual object in the subsequent frame of image is smaller than the size of the corresponding region of the actual object in the previous frame of image.

[0039] Further, for each frame of image, taking the pixel at the upper left corner of each frame of image as the origin, the horizontal direction to the right of the origin as the direction of the horizontal axis, and the vertical direction downward from the origin as the direction of the vertical axis; denoting the abscissa and ordinate of the pixel in each frame of image as and , respectively, and the abscissa ranges from to , and the ordinate .

[0040] Among them, according to the corresponding relationship between the flight direction and flight speed of the drone when collecting two adjacent frames of images and the size of the analysis area of the two adjacent frames of images, determining the corresponding relationship between the position coordinates of the analysis areas of the two adjacent frames of images, that is, determining the position coordinates of the corresponding pixels in the latter frame of image for each pixel in the former frame of image among the two adjacent frames of images; for the pixel with the position coordinate in the former frame of image, the position coordinate of the corresponding pixel in the latter frame of image is , and satisfies the relational expression: ; ; Among them, is the corresponding relationship between the sizes of the analysis areas of the two adjacent frames of images, , are the sine function and cosine function respectively, , are the flight direction and flight speed of the drone when collecting the latter frame of image among the two adjacent frames of images respectively, is the time interval for collecting the two adjacent frames of images, represents taking the absolute value, is the floor function; is the abscissa of the pixel in the former frame of image, is the ordinate of the pixel in the former frame of image, is the position coordinate of the corresponding pixel in the latter frame of image for the pixel with the position coordinate in the former frame of image, is the abscissa of the corresponding pixel in the latter frame of image for the pixel with the position coordinate in the former frame of image, is the ordinate of the corresponding pixel in the latter frame of image for the pixel with the position coordinate in the former frame of image.

[0041] It should be noted that as the drone flies, the flight direction and speed of the drone, as well as the positions and sizes of actual objects in the real scene, will continuously change in adjacent two-frame images. Therefore, according to the flight direction and speed of the drone when the latter frame of image is collected and the corresponding relationship between the sizes of the analysis regions of adjacent two-frame images, the corresponding relationship of the position coordinates of the analysis regions of adjacent two-frame images is determined.

[0042] It should be further noted that when the present invention determines the corresponding relationship of the position coordinates of the analysis regions of adjacent two-frame images, the flight speed, flight altitude, and flight direction of the drone provide an important reference basis for accurately determining the analysis regions of adjacent two-frame images. By comprehensively considering these parameters, the movement and changes of actual objects in the images can be predicted more precisely, thereby optimizing the effect of image analysis.

[0043] Furthermore, the determining of the analysis regions of adjacent two-frame images according to the corresponding relationship of the position coordinates of the analysis regions of adjacent two-frame images includes: obtaining the corresponding pixel points in the latter frame of image for each pixel point in the former frame of image according to the corresponding relationship of the position coordinates of the analysis regions of adjacent two-frame images; for any pixel point in the former frame of image, when the abscissa of the corresponding pixel point of this pixel point in the latter frame of image is within a range and the ordinate is within a range, regarding this pixel point as an analysis pixel point in the former frame of image; forming the analysis region of the former frame of image by all the analysis pixel points in the former frame of image, and the obtained analysis region is a rectangular region; regarding the corresponding pixel points of the four vertices in the analysis region of the former frame of image in the latter frame of image as the four vertices of the latter frame of image, and regarding the rectangular region surrounded by the four vertices of the latter frame of image as the analysis region of the latter frame of image.

[0044] S3. Determine the jitter degree of the drone when collecting each frame of image according to the rated parameters of the drone, the flight parameters of the drone when collecting each frame of image, and the environmental data, and determine the size of the judgment window of the pixel points in each frame of image according to the jitter degree.

[0045] Among them, the rated parameters of the drone include the maximum flight speed 、maximum flight altitude and wind resistance of the drone. The maximum flight speed of the drone refers to the highest speed that the drone can reach under windless conditions. The maximum flight altitude of the drone refers to the highest flight altitude that the drone can reach. The wind resistance of the drone refers to the highest wind speed at which the drone can maintain stable flight; the flight parameters of the drone include flight direction 、flight speed and flight altitude The environmental data refers to the wind speed The wind speed is collected by an anemometer carried by the UAV, and the wind speed refers to the wind speed at the flight altitude of the UAV.

[0046] It should be noted that the flight speed and flight altitude of the UAV have a significant impact on its stability. Among them, the flight speed affects the aerodynamic lift and thrust balance of the UAV. If the speed is too fast, the lift may exceed the design range, breaking the balance with gravity and making the UAV difficult to control; the flight altitude affects the air density and air pressure. The higher the flight altitude, the thinner the air at high altitudes, and the lift and thrust of the UAV will be affected, resulting in a decline in flight performance and a decrease in stability.

[0047] Specifically, for any frame of image, according to the rated parameters of the UAV, the flight parameters of the UAV when collecting this frame of image, and the environmental data, the jitter degree of the UAV when collecting this frame of image is determined. The calculation formula for the jitter degree of the UAV when collecting this frame of image is as follows: ; In the formula, is the jitter degree of the UAV when collecting this frame of image, is the flight speed of the UAV when collecting this frame of image, is the maximum flight speed of the UAV, is the flight altitude of the UAV when collecting this frame of image, is the maximum flight altitude of the UAV, is the wind speed when collecting this frame of image, is the wind resistance of the UAV, represents taking the maximum value, is the natural exponential function, is a preset parameter.

[0048] Among them, the specific value of the preset parameter can be set according to the actual application scenario and requirements, and the value range of the preset parameter is [0.001, 0.1]. In the present invention, the preset parameter is set to 0.01.

[0049] It should be noted that the wind resistance of the UAV refers to the highest wind speed at which the UAV can maintain stable flight. When the wind speed when collecting this frame of image is less than or equal to the wind resistance of the UAV , that is, when the wind speed borne by the UAV when collecting this frame of image does not exceed the highest wind speed at which the UAV can maintain stable flight, the UAV can maintain stable flight, then the UAV does not generate jitter when collecting this frame of image. Correspondingly , that is is a fixed value. At this time, as the flight speed and flight height of the drone increase when collecting this frame of image, the flight stability of the drone becomes worse, and the jitter degree of the drone when collecting this frame of image becomes larger; when the wind speed is greater than the wind resistance of the drone , that is, when the wind speed borne by the drone when collecting this frame of image exceeds the maximum wind speed at which the drone can maintain stable flight, the drone cannot maintain stable flight, so the drone jitters when collecting this frame of image, and the wind speed and the wind resistance of the drone difference is larger, correspondingly is larger, the flight stability of the drone is worse, and the jitter degree of the drone when collecting this frame of image is larger. Moreover, as the flight speed and flight height of the drone increase when collecting this frame of image, the flight stability of the drone is worse, and the jitter degree of the drone when collecting this frame of image is larger.

[0050] Furthermore, it should be noted that when , in the calculation formula of the jitter degree of the drone when collecting this frame of image, as decreases, the jitter degree gradually increases. This is because is a negative correlation function. Therefore, for , as the flight speed and flight height of the drone when collecting this frame of image increase, the ratio of the flight speed to the maximum flight speed of the drone and the flight height of the drone when collecting this frame of image to the maximum flight height of the drone gradually increase, gradually decreases, and the jitter degree of the drone when collecting this frame of image gradually increases; when , in the calculation formula of the jitter degree of the drone when collecting this frame of image, as increases, the jitter degree gradually increases. This is because is a negative correlation function. Therefore, for , as the flight speed and flight height of the drone when collecting this frame of image increase, the ratio of the flight speed to the maximum flight speed of the drone and the flight altitude of the drone when collecting this frame of image and the maximum flight altitude of the drone ratio gradually increases, gradually decreases, and the jitter degree of the drone when collecting this frame of image gradually increases.

[0051] It should be noted that in the present invention, by collecting the ratio of the flight parameters and environmental data of the drone when collecting each frame of image to the rated parameters of the drone, the jitter degree of the drone when collecting each frame of image is calculated, which is used to quantify the image stability of the drone under different flight conditions and is used to exclude jitter interference when calculating the noise degree of the image in the subsequent process.

[0052] Furthermore, according to the jitter degree of the drone when collecting this frame of image, the preset size is adjusted to obtain the size of the judgment window of the pixel points in this frame of image and denoted as , where the preset size is , is the preset length, then the calculation formula of is: ; In the formula, is the jitter degree of the drone when collecting this frame of image, is the preset length, is the floor function.

[0053] Among them, the specific value of the preset length can be set according to the actual application scenario and requirements, and the value range of the preset length is [3, 9] and is an odd number. In the present invention, the preset length is set to 7.

[0054] It should be noted that the greater the jitter degree of the drone when collecting this frame of image, the greater the deviation of the corresponding positions of the actual objects in the real scene in two adjacent frames of images. Therefore, the larger the size of the judgment window.

[0055] S4. Obtain the minimum value of the characteristic difference from the analysis pixel points in the judgment window as its noise degree, and adjust the motor speed of the communication antenna at the receiving end according to the noise degrees of all the analysis pixel points in the analysis regions of all the frame images in the video.

[0056] Specifically, for any analysis pixel point in the analysis region of the previous frame of image, according to the position coordinate correspondence relationship of the analysis regions of two adjacent frames of images, obtain any analysis pixel point The corresponding analysis pixel points in the analysis region of the subsequent frame image ; According to the size correspondence relationship of the analysis regions of two adjacent frame images and the size of the judgment window of the pixel points in the subsequent frame image , the region centered on the analysis pixel point with a size of is used as the judgment window of the analysis pixel point ; Calculate the feature differences between each analysis pixel point in the judgment window and the analysis pixel point , and record the smallest feature difference as the noise level of the analysis pixel point .

[0057] It should be noted that by selecting the smallest feature difference from the feature differences between all the analysis pixel points in the judgment window of the analysis pixel point and the analysis pixel point and recording it as the noise level of the analysis pixel point , the jitter interference caused by various reasons during the video acquisition by the drone is excluded, and thus the noise level of the transmission line between the drone and the receiving end is accurately obtained.

[0058] The calculation of the feature differences between each analysis pixel point in the judgment window and the analysis pixel point includes: ; In the formula, is the feature difference between the th analysis pixel point in the judgment window of the analysis pixel point and the analysis pixel point , is the gray value of the analysis pixel point , is the gray value of the th analysis pixel point in the judgment window of the analysis pixel point , is the LBP feature of the analysis pixel point , is the LBP feature of the th analysis pixel point in the judgment window of the analysis pixel point , is the Hamming distance, is to take the absolute value.

[0059] Among them, the Hamming distance is a measure to measure the difference between two binary strings, is the LBP feature of the analysis pixel point and the LBP feature of the th analysis pixel point in the judgment window of the analysis pixel point The Hamming distance of the LBP features of an analysis pixel point, Hamming distance The smaller it is, the analysis pixel point The LBP feature of and the analysis pixel point In the judgment window of, the th analysis pixel point has more similar LBP features. The analysis pixel point In the judgment window of, the th analysis pixel point and the analysis pixel point have smaller feature differences.

[0060] The LBP feature is obtained through the LBP operator (Local Binary Pattern). The LBP operator is an operator used to describe the local features of an image. The LBP operator is defined within a 3×3 neighborhood centered on a pixel point. Taking the gray value of the central pixel point as the threshold, by comparing the gray values of 8 adjacent pixel points with the gray value of the central pixel point, if the gray value of an adjacent pixel point is greater than the gray value of the central pixel point, the position of this adjacent pixel point is marked as 1, otherwise it is marked as 0; in this way, 8 adjacent pixel points within the 3×3 neighborhood of the pixel point can generate an 8-bit binary number through comparison. Arranging these 8-bit binary numbers in sequence forms a binary string, which serves as the LBP feature of the pixel point. That is to say, the LBP feature of the pixel point is in the form of a binary string.

[0061] It should be noted that in the present invention, the difference in the gray values of two analysis pixel points reflects the brightness change of the two analysis pixel points, while the difference in the LBP features of the two analysis pixel points reflects the local texture change of the two analysis pixel points. Combining the difference in gray values and the difference in LBP features can more comprehensively describe the feature differences between the two analysis pixel points.

[0062] Furthermore, taking the average value of the feature differences of all analysis pixel points in the analysis area of each frame of image as the noise level of each frame of image; taking the average value of the noise levels of all frame images in the video as the noise level of the transmission line between the drone and the receiving end; according to the noise level of the transmission line between the drone and the receiving end, adjusting the motor speed of the communication antenna at the receiving end, then the calculation formula for the motor speed of the communication antenna at the receiving end after adjustment is: ; In the formula, is the motor speed of the communication antenna at the receiving end after adjustment, is the noise level of the transmission line between the drone and the receiving end, is the motor speed of the communication antenna at the receiving end, is the noise threshold.

[0063] Among them, the noise threshold The specific value can be set according to the actual application scenario and requirements, and the noise threshold ranges from (0, 0.05], and in the present invention, the noise threshold is set to 0.02.

[0064] It should be noted that the calculated noise level of the transmission line between the drone and the receiving end reflects that when the motor speed of the communication antenna at the receiving end is equal to , the communication efficiency and signal reception continuity at the receiving end. When the noise level of the transmission line between the drone and the receiving end is greater than or equal to the noise threshold , the greater the noise level, the worse the communication efficiency and signal reception continuity at the receiving end, and the greater the adjustment degree of the motor speed of the communication antenna at the receiving end. At this time, an adjustment coefficient greater than 1 is required to increase the motor speed of the communication antenna at the receiving end. Then the motor speed of the communication antenna at the receiving end after adjustment , so as to improve the communication efficiency and signal reception continuity to ensure the optimal transmission and reception of signals. When the noise level of the transmission line between the drone and the receiving end is less than the noise threshold , it indicates that the communication efficiency and signal reception continuity at the receiving end are good. At this time, the motor speed of the communication antenna at the receiving end is no longer increased to avoid increasing the mechanical wear of the motor and prolonging the service life of the motor.

[0065] The embodiment of the present invention also discloses a remote adjustment system for the speed of a communication antenna motor, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, a remote adjustment method for the speed of a communication antenna motor according to the present invention is implemented.

[0066] The above system also includes other components well known to those skilled in the art such as a communication bus and a communication interface. Their settings and functions are known in the art, so they will not be elaborated here.

[0067] In the description of this specification, the meanings of "a plurality of" and "several" are at least two, such as two, three or more, etc., unless otherwise specifically defined.

[0068] Although this specification has shown and described multiple embodiments of the present invention, it is obvious to those skilled in the art that such embodiments are provided only by way of example. Those skilled in the art will think of many changes, alterations and alternative ways without departing from the spirit and idea of the present invention. It should be understood that in the process of practicing the present invention, alternative solutions to the embodiments of the present invention described herein can be adopted.

Claims

1. A method for remotely adjusting the speed of a communication antenna motor, characterized in that: include: Collecting video by drone and transmitting it to a receiving end, wherein the video includes multiple frames of images; For the receiving end, according to the flight altitude of the UAV when collecting two adjacent frames of images, the size correspondence of the analysis area of ​​the two adjacent frames of images is determined and recorded as ; According to the corresponding relationship between the flight direction, flight speed and size of the drone when collecting two adjacent frames of images , determining the position coordinate correspondence between the analysis areas of two adjacent image frames, so as to obtain the analysis areas of the two adjacent image frames; Determine the degree of jitter when the drone collects each frame of image based on the rated parameters of the drone, the flight parameters of the drone when collecting each frame of image, and environmental data; The preset size is adjusted according to the degree of jitter, and the size of the judgment window of the pixel points in each frame of the image is obtained and recorded as ; According to the position coordinate correspondence of the analysis area of ​​two adjacent frames of images, any analysis pixel point in the analysis area of ​​the previous frame of image is obtained. The corresponding analysis pixel point in the analysis area of ​​the next frame image ; will analyze the pixel points is centered and has a size of The area is used as the analysis pixel point The judgment window is used to calculate the difference between each analysis pixel point and the analysis pixel point in the judgment window. The smallest feature difference is recorded as the analysis pixel point The noise level; The motor speed of the communication antenna at the receiving end is adjusted according to the sum of the noise levels of all analysis pixels in the analysis area of ​​all frame images in the video.

2. A method for remotely adjusting the speed of a communication antenna motor according to claim 1, characterized in that: The corresponding relationship between the sizes of the analysis areas of the two adjacent frames of images , To collect the flight height of the UAV when the previous frame of two adjacent frames is captured, It is the flight height of the UAV when collecting the latter frame of two adjacent frames.

3. A method for remotely adjusting the speed of a communication antenna motor according to claim 1, characterized in that: In the position coordinate correspondence relationship of the analysis area of ​​the two adjacent frames of images, for the position coordinate of the previous frame of image is The pixel point of the next frame image has the following position coordinates: , The satisfied relationship is: ； ； in, , are the flight direction and speed of the drone when collecting the latter frame of two adjacent frames of images, is the time interval between two adjacent frames of images. Indicates taking the absolute value, is the floor function.

4. The method for remotely adjusting the speed of a communication antenna motor according to claim 1, characterized in that: The step of obtaining the analysis area of ​​two adjacent frames of images includes: According to the position coordinate correspondence of the analysis area of ​​two adjacent frames of images, the corresponding pixel point of each pixel point in the previous frame of image in the next frame of image is obtained; for any pixel point in the previous frame of image, when the horizontal coordinate of the pixel point corresponding to the pixel point in the next frame of image exist Within the range and the vertical coordinate exist When it is within the range, the pixel point is used as the analysis pixel point in the previous frame image. and are the length and width of each frame image respectively; all the analyzed pixels in the previous frame image form the analysis area of ​​the previous frame image; the pixels corresponding to the four vertices in the analysis area of ​​the previous frame image in the next frame image are used as the four vertices of the next frame image, and the rectangular area surrounded by the four vertices of the next frame image is used as the analysis area of ​​the next frame image.

5. The method for remotely adjusting the speed of a communication antenna motor according to claim 1, characterized in that: The rated parameters of the drone include the maximum flight speed of the drone , Maximum flight altitude and wind resistance The flight parameters of the UAV include flight speed and flight altitude , the environmental data refers to wind speed The wind speed is collected by an anemometer carried by the drone, and the wind speed refers to the wind speed at the drone's flight altitude.

6. A method for remotely adjusting the speed of a communication antenna motor according to claim 5, characterized in that: The calculation formula for the jitter degree when the drone collects each frame of image is: ； In the formula, The jitter degree when the drone collects the frame image. , are the flight speed and altitude of the drone when the frame image was collected, , are the maximum flight speed and maximum flight altitude of the UAV, respectively. is the wind speed when the frame image is collected, For the wind resistance of the drone, Indicates taking the maximum value, is the natural exponential function, are preset parameters.

7. A method for remotely adjusting the speed of a communication antenna motor according to claim 1, characterized in that: Said The calculation formula is: ； In the formula, The jitter degree when the drone collects the frame image. is the preset length, is the floor function, is the preset size, The preset length.

8. The method for remotely adjusting the speed of a communication antenna motor according to claim 1, characterized in that: The calculation and judgment window is composed of each analysis pixel point and the analysis pixel point The characteristic differences include: ； In the formula, To analyze the pixels In the judgment window Analysis pixels and analysis pixels The characteristic differences, , Analyze pixels separately Gray value and LBP features, , Analyze pixels separately In the judgment window The gray value of the analyzed pixel, is the Hamming distance.

9. A method for remotely adjusting the speed of a communication antenna motor according to claim 1, characterized in that: The adjusting of the motor speed of the communication antenna of the receiving end includes: The average value of the feature differences of all analyzed pixels in the analysis area of ​​each frame image is used as the noise level of each frame image; the average value of the noise level of all frame images in the video is used as the noise level of the transmission line between the drone and the receiving end; the motor speed after the communication antenna of the receiving end is adjusted The calculation formula is: ； In the formula, is the noise level of the transmission line between the drone and the receiving end, is the motor speed of the communication antenna at the receiving end, is the noise threshold.

10. A remote speed adjustment system for a communication antenna motor, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a method for remotely adjusting the speed of a communication antenna motor according to any one of claims 1 to 9 is implemented.

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