CN110806757B - Unmanned aerial vehicle system based on 5G network remote control - Google Patents
Unmanned aerial vehicle system based on 5G network remote control Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
Abstract
The invention discloses an unmanned aerial vehicle system based on 5G network remote control, which comprises an unmanned aerial vehicle, 5G CPE equipment, a server and a handheld control terminal, wherein the unmanned aerial vehicle is connected with the 5G CPE equipment through the server; the invention comprehensively considers the environment condition, the flight condition and the signal intensity condition together, establishes a feedback processing mechanism, and provides different solution schemes in a targeted manner, namely combines the unmanned aerial vehicle technology with the 5G network communication technology and the processing mode thereof, adopts a dual promotion type solution, and promotes the communication stability and the anti-interference capability together according to the 5G and the analysis process; and when a feedback processing mechanism is established, information is collected to form a data set, and when the same situation is met next time, corresponding suggestions are directly provided, so that the purposes of efficient intelligent learning and concise optimization are realized under the condition of ensuring the communication stability, and the overall data processing fluency and data processing effect are improved.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle systems, in particular to an unmanned aerial vehicle system based on 5G network remote control.
Background
Most of the traditional unmanned aerial vehicles communicate in an image transmission or data transmission mode, and part of the traditional unmanned aerial vehicles use 3G and 4G networks or a mode of combining the 3G and the 4G networks, but the traditional unmanned aerial vehicles use the image transmission or the data transmission mode and are limited to the problems of short communication distance and weak communication capacity outside the supporting visual range; the 3G and 4G network modes cannot meet the requirements of the unmanned aerial vehicle on communication stability, real-time performance and bandwidth, and often cause the problems of control failure, real-time image interruption or blurring and state feedback lag of the unmanned aerial vehicle; the combination of the two modes greatly increases the overall complexity of the system;
with the development and popularization of the 5G network technology and the characteristics of high stability, high bandwidth, high transmission speed, low possibility of interference and the like of the 5G network, the full support is provided for the communication of the unmanned aerial vehicle, and meanwhile, the guarantee is provided for the communication and the control outside the visual range of the unmanned aerial vehicle;
in order to solve the above-mentioned drawbacks, a technical solution is now provided.
Disclosure of Invention
The invention aims to provide an unmanned aerial vehicle system based on 5G network remote control, which comprehensively considers the environment condition, the flight condition and the signal intensity condition together and establishes a feedback processing mechanism to provide different solution schemes in a targeted manner, namely, the unmanned aerial vehicle technology is combined with the 5G network communication technology and the processing mode thereof, and a dual promotion type solution is adopted to improve the communication stability and the anti-interference capability together according to the 5G and the analysis process; and when a feedback processing mechanism is established, information is collected to form a data set, and when the same situation is met next time, corresponding suggestions are directly provided, so that the purposes of efficient intelligent learning and concise optimization are realized under the condition of ensuring the communication stability, and the overall data processing fluency and data processing effect are improved.
The technical problems to be solved by the invention are as follows:
how to solve through an effective mode, to using the mode of image transmission or data transmission, confine to the short, weak problem of communication ability outside supporting the line of sight to the communication distance, and 3G, the mode of 4G network can not satisfy unmanned vehicles again, to the requirement of communication stability, real-time and bandwidth, and the combination of two kinds of modes then greatly increased the problem of the whole complexity of system again.
The purpose of the invention can be realized by the following technical scheme:
an unmanned aerial vehicle system based on 5G network remote control comprises an unmanned aerial vehicle, 5G CPE equipment, a server and a handheld control terminal;
the unmanned aerial vehicle is used for carrying 5G CPE equipment and has the functions of real-time state monitoring, image shooting and the like, the 5G CPE equipment is used for providing a 5G network, a communication link of the unmanned aerial vehicle is formed by connecting the 5G CPE equipment with the 5G network, and the model of the 5G CPE equipment is 5G CPE PRO H112-370;
the server is used for transferring and communicating the handheld control terminal and the unmanned aerial vehicle, transferring a command of the handheld control terminal to the unmanned aerial vehicle, sending information fed back by the unmanned aerial vehicle to the handheld control terminal and recording an operation log of the time;
the handheld control terminal is used for controlling the unmanned aerial vehicle;
the unmanned aerial vehicle is internally provided with a data acquisition module, a data analysis module, a signal generation module, a data calling module, a controller and a data display module;
the data acquisition module is used for acquiring flight information and signal intensity data of the unmanned aerial vehicle and surrounding environment information in real time and transmitting the flight information and the signal intensity data and the surrounding environment information to the data analysis module;
the data analysis module performs real-time flight condition analysis operation on the data to obtain a flight coefficient A, an environment coefficient B and a flight condition coefficient C, and transmits the flight coefficient A, the environment coefficient B and the flight condition coefficient C to the signal generation module;
the signal generating module compares the flight coefficient A with respective preset ranges, when the flight coefficient A is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, the flight coefficient A is used for generating an L1 signal, an L2 signal and an L3 signal, when the environment coefficient B is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, the environment coefficient B is used for generating a K1 signal, a K2 signal and a K3 signal, when the flight condition coefficient C is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, the flight condition coefficient C is used for generating a J1 signal, a J2 signal and a J3 signal, the signals are combined to obtain a final signal set, and the final signal set is fed back to the data adjusting module, namely when the L1 signal, the K2 signal and the J3 signal exist, the three are combined to obtain a final L1K2J3 signal set;
the data calling module is used for recording and storing solution solutions corresponding to various signal sets in real time and obtaining the solution solutions through manual input, network search acquisition, network search and the like;
the signal generating module transmits the solution scheme corresponding to the signal set to the data display module through the controller;
the signal generation module is also used for collecting the total occurrence frequency of various signal sets and the solution solutions corresponding to the signal sets in real time, when the total occurrence frequency exceeds a set performance threshold value, the signal sets and the solution solutions corresponding to the signal sets generate the performance signals, and when the signal generation module receives the same signal sets in the performance signals, the solution solutions corresponding to the signal sets are directly sent to the handheld control terminal;
the data display module sends the solution scheme to the handheld control terminal according to the solution scheme, the solution scheme is displayed by the handheld control terminal, and the handheld control terminal and the data display module are electrically connected.
Furthermore, the 5G CPE equipment is adaptively connected with the 4G network and the 5G network, provides an RJ45 interface for external connection with the WIFI network, and has a network routing function.
Furthermore, the handheld control terminal is connected with a 4G network and a 5G network for transmission and consists of a touch screen and a control handle; the touch screen is used for displaying the posture and the image of the unmanned aerial vehicle and controlling the unmanned aerial vehicle according to touch operation; the control handle is used for controlling the unmanned aerial vehicle and consists of the control handle configured by the unmanned aerial vehicle and a flat plate or a mobile phone inserted with an SIM.
Further, the flight information comprises load data, transverse vertical distance data and angle data, the angle data can be obtained through calculation according to vertical height distance data, a linear distance between the unmanned aerial vehicle and the handheld control terminal and a trigonometric function formula, the load data, the transverse vertical distance data and the signal intensity data can be obtained through acquisition according to sensors and other modes, the environment information comprises illumination intensity data, wind speed data and temperature data, and the three data can be obtained through acquisition according to sensors and other modes.
Further, the specific steps of the flight condition analysis operation are as follows:
the method comprises the following steps: acquiring flight information and signal intensity data of the unmanned aerial vehicle and surrounding environment information in real time, respectively marking load data, transverse vertical distance data and angle data as Q, W and E, respectively marking illumination intensity data, wind speed data and temperature data as R, T and Y, and respectively marking signal intensity data as U;
step two: first according to the formula
Obtaining real-time flight coefficients A, wherein q, w and e are flight correction factors, q is larger than e and is larger than w, and q + w + e =3.5985; then according to the formula
Obtaining real-time environment coefficients B, wherein r and t are environment correction factors, r is larger than t and r + t =3.1258, when Y is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, Y is respectively endowed with calibration positive values P1, P2 and P3, and P1 is smaller than P3 and smaller than P2; and finally, according to a formula C = A + B + U, obtaining a real-time flight condition coefficient C, wherein a, B and U are all weight coefficients, a is larger than U and is larger than B, and a + B + U =4.6981.
The invention has the beneficial effects that:
when the handheld control terminal controls the unmanned aerial vehicle, a corresponding control instruction is sent to the server through the 5G network, the server is sent to the 5G CPE through the 5G network, the 5G CPE transmits a data packet containing the control instruction to the unmanned aerial vehicle according to a network routing function, the unmanned aerial vehicle immediately starts to respond to the control instruction after receiving the data packet containing the control instruction in real time, and sends the real-time attitude and the real-time image of the unmanned aerial vehicle to the server through the 5G CPE, and the server forwards the real-time attitude and the real-time image to the handheld control terminal through the 5G network and displays the real-time attitude and the real-time image according to the handheld control terminal;
the unmanned aerial vehicle can acquire flight information, signal intensity data and surrounding environment information in real time, wherein the flight information comprises load data, transverse vertical distance data and angle data, the environment information comprises illumination intensity data, wind speed data and temperature data, flight condition analysis operation is carried out on the flight information, namely the load data, the transverse vertical distance data and the angle data, the illumination intensity data, the wind speed data and the temperature data as well as the signal intensity data are calibrated, subjected to internal correction analysis and overall weighting processing to obtain a flight coefficient A, an environment coefficient B and a flight condition coefficient C, comparison signals are obtained through preset comparison and combined to generate various signal sets, corresponding solution schemes are obtained according to the comparison signals to be sent to a handheld control terminal for display, the total occurrence times of the various signal sets are compared with a set performance threshold value to generate corresponding performance signals according to the comparison signals, and when the same signal sets in the performance signals are received, the solution schemes corresponding to the solution schemes are directly sent to the handheld control terminal;
the environment condition, the flight condition and the signal intensity condition are comprehensively considered together, and a feedback processing mechanism is established to provide different solution schemes in a targeted manner, namely an unmanned aerial vehicle technology is combined with a 5G network communication technology and a processing mode thereof, a dual-promotion solution is adopted, and the communication stability and the anti-interference capability of the unmanned aerial vehicle are promoted together with the analysis process according to 5G; and when a feedback processing mechanism is established, information is collected to form a data set, and when the same condition is met next time, corresponding suggestions are directly provided, so that the purposes of efficient intelligent learning and concise optimization are realized under the condition of ensuring the communication stability, and the integral data processing fluency and data processing effect are improved.
Drawings
For the understanding of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
FIG. 1 is a block diagram of the system of the present invention;
FIG. 2 is a communication link diagram of the present invention;
FIG. 3 is a block diagram of the internal modules of the unmanned aerial vehicle of the present invention.
Detailed Description
As shown in fig. 1-3, an unmanned aerial vehicle system based on 5G network remote control includes an unmanned aerial vehicle, a 5G CPE device, a server, and a handheld control terminal;
the unmanned aerial vehicle is used for carrying 5G CPE equipment and has the functions of real-time state monitoring, image shooting and the like, the 5G CPE equipment is used for providing a 5G network, a communication link of the unmanned aerial vehicle is formed by connecting the 5G CPE equipment with the 5G network, the model of the 5G CPE equipment is 5G CPE PRO H112-370, the 5G CPE equipment is in self-adaptive connection with the 4G network and the 5G network, an RJ45 interface is externally provided for the 5G CPE equipment to be connected with a WIFI network, and the 5G CPE equipment has a network routing function;
the server is used for transferring and communicating the handheld control terminal and the unmanned aerial vehicle, transferring a command of the handheld control terminal to the unmanned aerial vehicle, sending information fed back by the unmanned aerial vehicle to the handheld control terminal and recording an operation log of the time;
the handheld control terminal is used for controlling the unmanned aerial vehicle, is connected with the 4G network and the 5G network and transmits, and consists of a touch screen and a control handle; the touch screen is used for displaying the gesture and the image of the unmanned aerial vehicle and controlling the unmanned aerial vehicle according to touch operation; the control handle is used for controlling the unmanned aerial vehicle and consists of the control handle configured by the unmanned aerial vehicle and a flat plate or a mobile phone inserted with an SIM (subscriber identity module);
the unmanned aerial vehicle is internally provided with a data acquisition module, a data analysis module, a signal generation module, a data calling module, a controller and a data display module;
the data acquisition module is used for acquiring flight information and signal intensity data of the unmanned aerial vehicle in real time and surrounding environment information and transmitting the flight information and the signal intensity data to the data analysis module together, the flight information comprises load data, transverse vertical distance data and angle data, the angle data can be obtained by calculation according to vertical height distance data, a linear distance between the unmanned aerial vehicle and the handheld control terminal and a trigonometric function formula, the load data, the transverse vertical distance data and the signal intensity data can be obtained by sensors and the like, the environment information comprises illumination intensity data, wind speed data and temperature data, and the three information can be obtained by sensors and the like;
the data analysis module performs real-time flight condition analysis operation on the flight condition, and the specific steps are as follows:
the method comprises the following steps: acquiring flight information and signal intensity data of the unmanned aerial vehicle and surrounding environment information in real time, respectively marking load data, transverse vertical distance data and angle data as Q, W and E, respectively marking illumination intensity data, wind speed data and temperature data as R, T and Y, and respectively marking signal intensity data as U;
step two: first according to the formula
Obtaining real-time flight coefficients A, wherein q, w and e are flight correction factors, q is larger than e and is larger than w, and q + w + e =3.5985; then according to the formula
Obtaining real-time environment coefficients B, wherein r and t are environment correction factors, r is larger than t and r + t =3.1258, when Y is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, Y is respectively endowed with calibration positive values P1, P2 and P3, and P1 is smaller than P3 and smaller than P2; finally, according to a formula C = A + B + U, a, B and U are all weight coefficients, a is larger than B, and a + B + U =4.6981;
obtaining a flight coefficient A, an environment coefficient B and a flight condition coefficient C, and transmitting the flight coefficient A, the environment coefficient B and the flight condition coefficient C to the signal generation module;
the signal generating module compares the flight coefficient A with respective preset ranges, when the flight coefficient A is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, the flight coefficient A is used for generating an L1 signal, an L2 signal and an L3 signal, when the environment coefficient B is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, the environment coefficient B is used for generating a K1 signal, a K2 signal and a K3 signal, when the flight condition coefficient C is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, the flight condition coefficient C is used for generating a J1 signal, a J2 signal and a J3 signal, the signals are combined to obtain a final signal set, and the final signal set is fed back to the data adjusting module, namely when the L1 signal, the K2 signal and the J3 signal exist, the three are combined to obtain a final L1K2J3 signal set;
the data calling module is used for recording and storing the solution solutions corresponding to various signal sets in real time and obtaining the solution solutions through modes of manual input, network search acquisition, network search and the like;
the signal generating module transmits the solution scheme corresponding to the signal set to the data display module through the controller;
the signal generation module is also used for collecting the total occurrence times of various signal sets and the solution solutions corresponding to the signal sets in real time, when the total occurrence times exceeds a set performance threshold value, the signal sets and the solution solutions corresponding to the signal sets generate the performance signals together, and when the signal generation module receives the same signal sets in the performance signals, the solution solutions corresponding to the signal sets are directly sent to the handheld control terminal;
the data display module sends the solution scheme to the handheld control terminal according to the solution scheme, the handheld control terminal displays the solution scheme, and the handheld control terminal and the data display module are electrically connected with each other.
The working principle is as follows: the 5G CPE equipment is mounted on the unmanned aerial vehicle, the unmanned aerial vehicle is connected with a 5G network through the 5G CPE equipment, the handheld control terminal is also connected with the 5G network, namely, a control instruction is sent to the server, and the server forwards the control instruction to the unmanned aerial vehicle so as to achieve the function of controlling the unmanned aerial vehicle;
when the handheld control terminal controls the unmanned aerial vehicle, a corresponding control instruction is sent to the server through the 5G network, the server is sent to 5G CPE equipment through the 5G network, the 5G CPE equipment transmits a data packet containing the control instruction to the unmanned aerial vehicle according to a network routing function, the unmanned aerial vehicle immediately starts to respond to the control instruction after receiving the data packet containing the control instruction in real time, and sends the real-time attitude and image of the unmanned aerial vehicle to the server through the 5G CPE equipment, the server forwards the real-time attitude and image to the handheld control terminal through the 5G network, and displays the real-time attitude and image according to the handheld control terminal;
the unmanned aerial vehicle can acquire flight information, signal intensity data and surrounding environment information in real time, wherein the flight information comprises load data, transverse vertical distance data and angle data, the environment information comprises illumination intensity data, wind speed data and temperature data, flight condition analysis operation is carried out on the flight information, namely the load data, the transverse vertical distance data and the angle data, the illumination intensity data, the wind speed data and the temperature data as well as the signal intensity data are calibrated, subjected to internal correction analysis and overall weighting processing to obtain a flight coefficient A, an environment coefficient B and a flight condition coefficient C, comparison signals are obtained through preset comparison and combined to generate various signal sets, corresponding solution schemes are obtained according to the comparison signals to be sent to a handheld control terminal for display, the total occurrence times of the various signal sets are compared with a set performance threshold value to generate corresponding performance signals according to the comparison signals, and when the same signal sets in the performance signals are received, the solution schemes corresponding to the solution schemes are directly sent to the handheld control terminal;
the environment condition, the flight condition and the signal intensity condition are comprehensively considered together, and a feedback processing mechanism is established to provide different solution schemes in a targeted manner, namely an unmanned aerial vehicle technology is combined with a 5G network communication technology and a processing mode thereof, a dual-promotion solution is adopted, and the communication stability and the anti-interference capability of the unmanned aerial vehicle are promoted together with the analysis process according to 5G; and when a feedback processing mechanism is established, information is collected to form a data set, and when the same condition is met next time, corresponding suggestions are directly provided, so that the purposes of efficient intelligent learning and concise optimization are realized under the condition of ensuring the communication stability, and the integral data processing fluency and data processing effect are improved.
The foregoing is merely illustrative and explanatory of the present invention and various modifications, additions or substitutions may be made to the specific embodiments described by those skilled in the art without departing from the scope of the invention as defined in the accompanying claims.
Claims (4)
1. An unmanned aerial vehicle system based on 5G network remote control is characterized by comprising an unmanned aerial vehicle, 5G CPE equipment, a server and a handheld control terminal;
the unmanned aerial vehicle is used for carrying 5G CPE equipment, the 5G CPE equipment is used for providing a 5G network, and a communication link of the unmanned aerial vehicle is formed by connecting the 5G CPE equipment with the 5G network;
the server is used for transferring and communicating the handheld control terminal and the unmanned aerial vehicle, transferring a command of the handheld control terminal to the unmanned aerial vehicle, sending information fed back by the unmanned aerial vehicle to the handheld control terminal and recording an operation log;
the handheld control terminal is used for controlling the unmanned aerial vehicle;
the unmanned aerial vehicle is internally provided with a data acquisition module, a data analysis module, a signal generation module, a data calling module, a controller and a data display module;
the data acquisition module is used for acquiring flight information and signal intensity data of the unmanned aerial vehicle and surrounding environment information in real time and transmitting the flight information and the signal intensity data and the surrounding environment information to the data analysis module;
the data analysis module performs real-time flight condition analysis operation on the data to obtain a flight coefficient A, an environment coefficient B and a flight condition coefficient C, and transmits the flight coefficient A, the environment coefficient B and the flight condition coefficient C to the signal generation module;
the signal generating module compares the flight coefficient A with respective preset ranges, when the flight coefficient A is larger than the maximum value of the preset range, is within the preset range and is smaller than the minimum value of the preset range, the flight coefficient A generates an L1 signal, an L2 signal and an L3 signal, when the environmental coefficient B is larger than the maximum value of the preset range, is within the preset range and is smaller than the minimum value of the preset range, the environmental coefficient B generates a K1 signal, a K2 signal and a K3 signal, when the flight condition coefficient C is larger than the maximum value of the preset range, is within the preset range and is smaller than the minimum value of the preset range, the flight condition coefficient C generates a J1 signal, a J2 signal and a J3 signal, and combines all types of signals to obtain a final signal set which is fed back to the data adjusting module;
the data calling module calls a corresponding solution scheme according to the signal set received in real time and feeds the solution scheme back to the signal generating module, and the data calling module is used for recording and storing the solution schemes corresponding to various signal sets in real time;
the signal generating module transmits the solution scheme corresponding to the signal set to the data display module through the controller;
the signal generation module is also used for collecting the total occurrence times of various signal sets and the solution solutions corresponding to the signal sets in real time, when the total occurrence times exceeds a set performance threshold value, the signal sets and the solution solutions corresponding to the signal sets generate the performance signals together, and when the signal generation module receives the same signal sets in the performance signals, the solution solutions corresponding to the signal sets are directly sent to the handheld control terminal;
the data display module sends the solution scheme to the handheld control terminal according to the solution scheme, and the solution scheme is displayed by the handheld control terminal;
the flight condition analysis operation comprises the following specific steps:
the method comprises the following steps: acquiring flight information and signal intensity data of the unmanned aerial vehicle and surrounding environment information in real time, respectively marking load data, transverse vertical distance data and angle data as Q, W and E, respectively marking illumination intensity data, wind speed data and temperature data as R, T and Y, and respectively marking signal intensity data as U;
step two: first according to the formula
Obtaining real-time flight coefficients A, wherein q, w and e are flight correction factors, q is larger than e and is larger than w, and q + w + e =3.5985; then according to the formula
Obtaining real-time environment coefficients B, wherein r and t are environment correction factors, r is larger than t and r + t =3.1258, when Y is larger than the maximum value of the preset range, is positioned in the preset range and is smaller than the minimum value of the preset range, Y is respectively endowed with calibration positive values P1, P2 and P3, and P1 is smaller than P3 and smaller than P2; and finally, according to a formula C = A + B + U, obtaining a real-time flight condition coefficient C, wherein a, B and U are all weight coefficients, a is larger than U and is larger than B, and a + B + U =4.6981.
2. The unmanned aerial vehicle system based on 5G network remote control of claim 1, wherein the 5G CPE device is adaptively connected with a 4G network and a 5G network, and externally provides an RJ45 interface for connection with a WIFI network.
3. The unmanned aerial vehicle system based on 5G network remote control of claim 1, wherein the hand-held control terminal is connected with 4G network and 5G network for transmission, and is composed of a touch screen and a control handle; the touch screen is used for displaying the posture and the image of the unmanned aerial vehicle and controlling the unmanned aerial vehicle according to touch operation; the control handle is used for controlling the unmanned aerial vehicle.
4. The unmanned aerial vehicle system based on 5G network remote control of claim 1, wherein the flight information comprises load data, transverse vertical distance data and angle data, and the environmental information comprises light intensity data, wind speed data and temperature data.
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