Flight communication system of unmanned aerial vehicle with single Beidou module and flight control method thereof

Abstract

The invention provides a flight communication system of a single Beidou module unmanned aerial vehicle and a flight control method thereof, relates to the field of unmanned aerial vehicle communication, and comprises a flight communication scheme and communication maintenance measures. By setting communication stability guarantee measures and a communication safety protection scheme, the operation stability and safety of the communication system can be effectively improved, normal operation of the unmanned aerial vehicle in the aspect of communication can be guaranteed, communication content can be effectively compressed and optimized by setting a communication optimization strategy, and the communication safety of the unmanned aerial vehicle is improved. Meanwhile, in cooperation with transmission scheduling optimization, key safety information, real-time control instruction response and the like of the unmanned aerial vehicle can be well arranged to be transmitted in a high-priority time period to ensure timely delivery, the communication transmission efficiency is ensured, and through the organic combination of a neural network algorithm and a PID control algorithm, the safety of the unmanned aerial vehicle is improved. The unmanned aerial vehicle can deal with various complex flight conditions more intelligently and accurately, and the efficiency and accuracy of route correction are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle communication, and in particular to a flight communication system of a single Beidou module unmanned aerial vehicle and a flight control method thereof. Background Art

[0002] With the rapid development of science and technology, UAV technology has become increasingly mature and has been widely used in many fields. In order to improve the flight efficiency and safety of UAVs, the short message communication function is integrated into the UAV flight control based on the Beidou positioning system. Through short message communication, the UAV can transmit key information in real time, thereby optimizing flight missions, improving emergency response capabilities, and ensuring the safety and controllability of the flight process. At the same time, the Beidou satellite navigation system, as a global satellite navigation system independently developed by my country, has high precision, high reliability and global coverage capabilities. The introduction of Beidou positioning in the UAV flight control system can significantly improve the navigation accuracy and flight stability of the UAV.

[0003] At present, there are still deficiencies in integrating short message communication functions into UAV flight control based on the Beidou positioning system, such as communication stability, data transmission efficiency and security. For example, UAVs may encounter various interference factors during flight, such as electromagnetic interference and weather influences, which may affect the stability of short message communication; at the same time, since the distance between the UAV and the ground control station may be far and the communication environment is complex and changeable, how to ensure the efficiency of data transmission is a key issue; and the UAV communication system faces various security threats, such as hacker attacks and data leaks. Summary of the invention

[0004] (I) Technical problems solved: In view of the shortcomings of the prior art, the present invention provides a flight communication system and a flight control method for a single Beidou module UAV, which solves the problems of integrating the short message communication function into the flight control of UAVs based on the Beidou positioning system, such as communication stability, data transmission efficiency and security. For example, the UAV may encounter various interference factors during flight, such as electromagnetic interference and weather influence, which may affect the stability of short message communication. At the same time, since the distance between the UAV and the ground control station may be far and the communication environment is complex and changeable, how to ensure the efficiency of data transmission is a key issue. In addition, the UAV communication system faces various security threats, such as hacker attacks and data leakage.

[0005] (II) Technical Solution: To achieve the above objectives, the present invention is implemented through the following technical solution: a single Beidou module UAV flight communication system, including a flight communication solution and communication maintenance measures, the flight communication solution includes Beidou short message transmission basis, data transmission optimization strategy and multi-communication mode coordination, the communication maintenance measures include communication stability guarantee measures and communication security protection solutions; The communication stability assurance measures include hardware enhancement measures, software optimization means and environmental adaptability strategies. The hardware enhancement measures are mainly achieved through antenna performance optimization and module reliability improvement. The software optimization means are mainly achieved through improvements in communication protocol robustness and data processing fault tolerance mechanisms. The environmental adaptability strategies are mainly achieved through real-time environmental monitoring and early warning and dynamic adjustment of flight plans. The communication security protection scheme includes a signal encryption and authentication system and a system security protection barrier. The signal encryption and authentication system is mainly implemented by deploying encryption algorithms and building an identity authentication framework, and the system security protection barrier is mainly implemented by software security reinforcement and redundant design assurance.

[0006] Furthermore, the antenna performance is optimized mainly through continuous research and selection of more advanced Beidou communication antennas. For complex flight environments or long-distance mission requirements, antennas with higher gain, wider bandwidth and stronger anti-interference capabilities are used. The module reliability is improved mainly through the selection of high-quality, industrial-grade Beidou communication modules, which have built-in high-sensitivity receiving chips and stable transmission power components to ensure stable signal reception and transmission under harsh conditions such as complex electromagnetic environments and signal shielding.

[0007] Furthermore, the improvement of the robustness of the communication protocol is mainly achieved by deeply optimizing the Beidou communication protocol, reasonably configuring the data frame format in the protocol, and adding sufficient check bits (such as CRC check) for error detection and correction. The data processing fault-tolerant mechanism is mainly achieved by embedding powerful data caching and pre-sending functions in the UAV and ground control station software. The UAV side sets a data cache area to store the data to be sent according to priority. When the quality of the communication link is good, part of the data is sent in batches in advance to reduce transmission delays.

[0008] Furthermore, the real-time environmental monitoring and early warning is mainly achieved by equipping the drone with multiple types of environmental sensors to monitor weather conditions (wind speed, wind direction, temperature, humidity, air pressure, etc.) and electromagnetic environment (electromagnetic interference intensity, spectrum distribution, etc.) in real time. The dynamic adjustment of the flight plan is mainly achieved by combining data resources such as weather forecasts and geographic information systems (GIS) to predict environmental changes on the drone's flight path in advance during the flight mission planning stage.

[0009] Furthermore, the encryption algorithm deployment is to fully adopt high-intensity encryption algorithms in the Beidou communication data transmission process, such as AES (Advanced Encryption Standard) in the symmetric encryption algorithm, and allocate unique key pairs for the drone and the ground control station. Before sending sensitive data (such as high-precision mapping data, military application location information, etc.), the data is encrypted into ciphertext through the AES algorithm, and the receiving end uses the same key to decrypt to ensure data confidentiality.

[0010] Furthermore, the identity authentication framework is constructed by establishing a two-way identity authentication mechanism based on digital signature technology. The drone and the ground control station each generate and keep a private key and a public key, and use the private key to sign the data when sending data. When the recipient receives the data, the other party's public key is used to verify the signature and confirm the legitimacy of the identity of the other party in communication, which can effectively prevent illegal devices from accessing the communication link.

[0011] Furthermore, the software security reinforcement is achieved by regularly scanning and repairing security vulnerabilities in the UAV flight control system and ground control station software, focusing on the communication protocol stack and data processing module, and promptly patching known vulnerabilities such as buffer overflow and code injection.

[0012] Furthermore, the redundant design ensures that, at the hardware level, if space and cost permit, the drone can be equipped with multiple Beidou communication antennas and modules to build a redundant communication system.

[0013] The control method of the single Beidou module UAV flight includes the following steps: Step 1: Preparation process for the drone before flight; Equipment pre-inspection: Before each flight mission, the operator conducts a comprehensive inspection of the drone and Beidou module to verify whether the antenna connection is stable and whether there are any signs of looseness or damage; confirm that the module power supply is normal and whether the voltage and current are within the rated range; Positioning calibration operation: Use known high-precision positioning points to calibrate the Beidou module, place the drone at a precisely measured geographical location, start the calibration program through the ground control station, adjust the Beidou module's satellite signal reception parameters (such as gain, offset, etc.), so that the positioning data accurately matches the known coordinates to improve positioning accuracy; Flight plan setting and uploading: The operator plans the flight route, sets the flight altitude, speed and task parameters (such as the amount of pesticide spraying in agricultural plant protection, the surveying accuracy in geographic surveying, etc.) in detail in the ground control station software according to the mission requirements. After the setting is completed, the flight plan data is transmitted to the drone through the Beidou communication link. The drone flight control system receives and stores it, and then executes the mission accordingly during the flight; Step 2: Control strategy during the flight of the drone; Precise position control: The ground control station receives the UAV position information fed back by the Beidou module in real time, and compares and analyzes it with the preset flight route. Once the UAV is found to deviate from the route, the control system formed by the proportional-integral-differential (PID) control algorithm combined with the neural network algorithm is immediately used to realize intelligent calculation and correction instructions; Stable altitude and speed control: Also based on the Beidou module data, the ground control station then sends altitude and speed control instructions according to the mission characteristics (such as stable altitude and appropriate speed for aerial photography, specific flight speed for agricultural plant protection to ensure uniform spraying of pesticides, etc.); Step 3: Response mechanism for emergencies during drone flight; Signal loss emergency response: If the Beidou module signal is interrupted during flight, the drone flight control system automatically switches to the preset safety mode; System failure safety protection: When the UAV's own system fails (such as motor failure, flight control system abnormality, etc.), the flight control system quickly sends detailed fault information to the ground control station through the Beidou communication link, including the fault type, occurrence time and possible impact.

[0014] Furthermore, the proportional-integral-derivative (PID) control algorithm is combined with a neural network algorithm to first build a system architecture, then use a neural network model for training, and then perform real-time control to correct the drone's route during the flight of the drone, and finally continuously optimize and adaptively adjust the system.

[0015] (III) Beneficial effects: The present invention provides a flight communication system and a flight control method for a single Beidou module UAV, which have the following beneficial effects: In this scheme, by setting up communication stability assurance measures and communication security protection schemes, the stability and security of the communication system operation can be effectively improved, which is conducive to ensuring the normal operation of the drone in terms of communication.

[0016] In this scheme, by setting up a communication optimization strategy, the communication content can be effectively compressed and optimized. At the same time, in conjunction with the transmission scheduling optimization, the key safety information of the drone, real-time control command response, etc. can be well arranged for transmission during high-priority periods to ensure timely delivery and ensure the efficiency of communication transmission.

[0017] In this solution, by setting up an organic combination of the neural network algorithm and the PID control algorithm, the UAV can respond to various complex flight conditions more intelligently and accurately, and effectively improve the efficiency and accuracy of route correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a schematic diagram of the solution architecture of the single Beidou module UAV flight communication system proposed by the present invention; Figure 2 This is a schematic diagram of the architecture of the single Beidou module UAV flight control method proposed in the present invention; Figure 3 This is a schematic diagram of the maintenance measures architecture of the single Beidou module UAV flight communication system proposed in the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Example: Figures 1 to 3 As shown, the embodiment of the present invention provides a single Beidou module UAV flight communication system, including a flight communication solution and communication maintenance measures. The flight communication solution includes Beidou short message transmission basis, data transmission optimization strategy and multi-communication mode coordination. The communication maintenance measures include communication stability guarantee measures and communication security protection solutions. The signal transceiver principle of Beidou short message transmission: the Beidou communication module on the drone receives and transmits signals in a specific Beidou frequency band (such as B1 band 1561.098MHz) to interact with Beidou satellites. When sending data, the module encodes and modulates the collected drone status information (such as position, speed, attitude, sensor data, etc.) according to the Beidou short message communication protocol, converts it into a signal format suitable for satellite communication link transmission, and sends it to the Beidou satellite via the antenna. The satellite then forwards the data to the ground control station; when receiving instructions, it performs demodulation and decoding operations in reverse to execute the control instructions sent by the ground control station; The data format specification of Beidou short message transmission is that the data sent by the drone consists of a message header, a message body and a check bit. The message header contains identification information such as the source, purpose, and type of the data, which facilitates the ground control station to quickly identify the nature of the data; the message body carries specific drone status data; the check bit is generated using algorithms such as cyclic redundancy check (CRC) to detect data errors during transmission and ensure data integrity; Data screening and compression during data transmission optimization. Given the limited length of Beidou short messages (up to about 140 bytes for civil use), drones intelligently screen and compress the large amount of information collected before sending data, giving priority to packaging key safety and mission-critical information such as location, status, and fault alarms. For secondary sensor data (such as some low-frequency change data in environmental monitoring), the sampling frequency is appropriately reduced or data simplification processing technology is used, such as differential encoding, to simplify the location data, so as to transmit the most valuable data within the limited message length; Data transmission scheduling optimization uses time-division multiplexing technology to divide transmission priorities according to the urgency and importance of data, and arranges the transmission of key safety information and real-time control command responses of drones in high-priority periods to ensure timely delivery; routine environmental monitoring, mission progress reports and other data are arranged in low-priority periods, and pre-transmission strategies are used in combination with mission plans and data change rules. For example, when a drone flies on a fixed route, the location prediction data corresponding to the next route is sent in advance to reduce the pressure of real-time transmission and improve transmission efficiency; The application of complementary communication modes when multiple communication modes are coordinated, integrating Beidou communication and other communication modes (such as 4G / 5G, Wi-Fi, etc.) in the UAV system, giving priority to enabling 4G / 5G communication in areas with good ground communication network coverage such as cities and suburbs, and using its high bandwidth advantage to transmit large-capacity data in real time, such as high-definition video streams, large-scale geographic mapping data, etc.; when the UAV enters remote mountainous areas, deserts and other areas without ground communication networks, it seamlessly switches to Beidou communication to ensure basic position reporting, control command reception and key data transmission functions to ensure mission continuity; Intelligent switching mechanism when multiple communication modes are coordinated. By designing an intelligent communication link switching strategy, before switching the communication mode, the UAV and the ground control station test and verify the new link through two-way communication to ensure that the communication quality after switching meets the mission requirements. During the switching process, the data that has not been transmitted is cached and backed up to prevent data loss, so as to achieve a smooth transition between different communication modes and improve the overall communication flexibility and reliability of the system. Communication stability assurance measures include hardware enhancement measures, software optimization methods and environmental adaptability strategies. Hardware enhancement measures are mainly achieved through antenna performance optimization and module reliability improvement. Software optimization methods are mainly achieved through improvements in communication protocol robustness and data processing fault-tolerant mechanisms. Environmental adaptability strategies are mainly achieved through real-time environmental monitoring and early warning and dynamic adjustment of flight plans. Antenna performance optimization is mainly achieved through continuous research and selection of more advanced Beidou communication antennas. For complex flight environments or long-distance mission requirements, antennas with higher gain, wider bandwidth and stronger anti-interference capabilities are used. The antenna installation status is checked regularly to ensure that it is stable and without displacement, and the protective coating is intact to prevent performance from being affected by flight wear, corrosion and other factors. In antenna design, multi-band integration technology is explored so that the antenna can adapt to the Beidou frequency band and other auxiliary communication frequency bands (such as 4G / 5G) at the same time, broadening the data transmission channels and enhancing communication stability; The reliability of the module is mainly improved by selecting high-quality, industrial-grade Beidou communication modules, which have built-in high-sensitivity receiving chips and stable transmitting power components to ensure stable signal reception and transmission under harsh conditions such as complex electromagnetic environments and signal blocking. The module is electromagnetically shielded and a metal shielding cover is installed around it or it is encapsulated with electromagnetic shielding materials to block external electromagnetic interference. At the same time, the module power supply is finely filtered to remove power supply noise to ensure stable module communication performance.

[0021] The improvement of communication protocol robustness is mainly achieved through in-depth optimization of Beidou communication protocol, reasonable configuration of data frame format in the protocol, adding sufficient check bits (such as CRC check) for error detection and correction. When the receiving end finds a check error, it automatically sends a retransmission request according to the protocol rules to ensure data accuracy. According to the signal strength and interference conditions in different flight environments, the communication baud rate, data bit, stop bit and other parameters are dynamically adjusted. The baud rate is reduced in areas with weak signals to reduce transmission errors and improve communication reliability. The data processing fault-tolerant mechanism is mainly achieved by embedding powerful data caching and pre-sending functions in the UAV and ground control station software. The UAV side sets up a data cache area to store the data to be sent according to priority. When the communication link quality is good, some data is sent in batches in advance to reduce transmission delays. At the same time, data error detection and correction algorithms are fully adopted. In addition to CRC verification, forward error correction (FEC) coding technology is introduced. For data with high real-time requirements but slightly lower accuracy requirements, an FEC scheme with high coding efficiency and less redundancy is selected. When the signal interference is strong, the coding redundancy is enhanced to improve the data recovery capability and ensure stable communication.

[0022] Real-time environmental monitoring and early warning are mainly achieved by equipping drones with multiple types of environmental sensors to monitor weather conditions (wind speed, wind direction, temperature, humidity, air pressure, etc.) and electromagnetic environment (electromagnetic interference intensity, spectrum distribution, etc.) in real time. The sensor data is transmitted to the flight control system and ground control station in real time. Once changes in environmental factors that may affect the stability of Beidou communication (such as strong winds causing antenna pointing deviations, increased electromagnetic interference, etc.) are detected, early warning information will be issued in a timely manner to provide a basis for operators to adjust flight plans or take emergency communication measures; Dynamic adjustment of flight plans is mainly achieved by combining data resources such as weather forecasts and geographic information systems (GIS) to predict environmental changes on the UAV's flight path in advance during the flight mission planning stage; If you are expected to fly over valleys, areas with tall buildings and other areas with severe signal obstruction or encounter bad weather, modify the flight plan in advance at the ground control station to avoid the risk area; if you cannot avoid it, activate the backup communication plan in advance (such as lowering the flight altitude, adjusting the antenna angle, switching the communication mode, etc.) to ensure a stable communication link; The communication security protection solution includes a signal encryption and authentication system and a system security protection barrier. The signal encryption and authentication system is mainly implemented by deploying encryption algorithms and building an identity authentication framework, while the system security protection barrier is mainly implemented by software security reinforcement and redundant design assurance. Encryption algorithm deployment means that high-strength encryption algorithms are fully adopted during the Beidou communication data transmission process, such as AES (Advanced Encryption Standard) in the symmetric encryption algorithm, and unique key pairs are assigned to the UAV and the ground control station. Before sending sensitive data (such as high-precision mapping data, military application location information, etc.), the data is encrypted into ciphertext through the AES algorithm, and the receiving end uses the same key to decrypt to ensure data confidentiality. For key management, according to the system scale and security requirements, the key distribution center (KDC) or public key infrastructure (PKI) is selected, and the keys are updated regularly to prevent key leakage from causing security risks.

[0023] The identity authentication framework is constructed by establishing a two-way identity authentication mechanism based on digital signature technology. The UAV and the ground control station each generate and keep private keys and public keys. When sending data, they use private keys to sign the data. When the receiver receives the data, it uses the other party's public key to verify the signature and confirm the legitimacy of the other party's identity. It can effectively prevent illegal devices from accessing the communication link. The authentication information is transmitted through the Beidou short message security field or the custom security protocol header to ensure that the authentication process is safe and reliable.

[0024] Software security reinforcement is achieved by regularly scanning and repairing security vulnerabilities in the UAV flight control system and ground control station software, focusing on the communication protocol stack and data processing module, and promptly patching known vulnerabilities such as buffer overflow and code injection; A software firewall is deployed at the front end of the ground control station software, and strict access rules are set based on authorized IP addresses, device identification, etc., allowing only legitimate devices to communicate with the drone; fine-grained permission management is performed on software users to ensure that only authorized operators can send key control instructions to prevent illegal operations from causing safety accidents.

[0025] Redundant design protection means that at the hardware level, if space and cost permit, the drone can be equipped with multiple Beidou communication antennas and modules to build a redundant communication system. Under normal circumstances, the main antenna and module work. Once a certain antenna has signal obstruction, damage or module failure, the backup equipment automatically switches to access to maintain uninterrupted communication. At the communication link level, redundant backup of Beidou communication and other communication methods (such as 4G / 5G, Wi-Fi) is achieved. When Beidou communication is interfered with, attacked or unstable, it quickly switches to the backup link. Combined with the intelligent switching mechanism, it ensures the continuity and stability of data transmission and control command delivery, and comprehensively improves system security.

[0026] The control method of the single Beidou module UAV flight includes the following steps: Step 1: Preparation process for the drone before flight; Equipment pre-inspection: Before each flight mission, the operator conducts a comprehensive inspection of the UAV and Beidou module to verify whether the antenna connection is stable and whether there is any sign of looseness or damage; confirm that the module power supply is normal and whether the voltage and current are within the rated range, and then send a test command through the ground control station software to check whether the Beidou module can respond normally and ensure that it is in a working state; Positioning calibration operation: Use known high-precision positioning points to calibrate the Beidou module, place the drone at a precisely measured geographical location, start the calibration program through the ground control station, adjust the Beidou module's satellite signal reception parameters (such as gain, offset, etc.) to accurately match the positioning data with the known coordinates to improve positioning accuracy, and jointly calibrate other sensors such as the magnetic compass and barometer to ensure that the flight status information after the fusion of each sensor data is accurate; Flight plan setting and uploading: The operator plans the flight route, sets the flight altitude, speed and task parameters (such as the amount of pesticide spraying in agricultural plant protection, the surveying accuracy in geographic surveying, etc.) in detail in the ground control station software according to the mission requirements. After the setting is completed, the flight plan data is transmitted to the drone through the Beidou communication link. The drone flight control system receives and stores it, and then executes the mission accordingly during the flight; Step 2: Control strategy during the flight of the drone; Precise position control: The ground control station receives the UAV position information fed back by the Beidou module in real time, and compares and analyzes it with the preset flight route. Once the UAV is found to deviate from the route, the control system formed by the proportional-integral-differential (PID) control algorithm combined with the neural network algorithm is immediately used to realize intelligent calculation and correction instructions. The control amount is accurately adjusted according to factors such as the deviation between the current position of the UAV and the target position, the deviation change rate, etc., and the command is sent through the Beidou communication link to drive the UAV to adjust its flight attitude so that it can quickly return to the preset route to ensure the accuracy of route tracking; Stable height and speed control: Also based on the Beidou module data, the ground control station then sends height and speed control instructions according to the mission characteristics (such as stable height and appropriate speed for aerial photography, specific flight speed for agricultural plant protection to ensure uniform spraying of pesticides, etc.). After receiving the instructions, the UAV flight control system adjusts the motor speed or flight attitude to achieve precise control of height and speed. For example, when lowering the flight altitude, the flight control system coordinates the motor to reduce the speed and smoothly descend to the target altitude. Step 3: Response mechanism for emergencies during drone flight; Signal loss emergency response: If the Beidou module signal is interrupted during flight, the drone flight control system automatically switches to the preset safety mode. If the signal is not restored within a certain period of time, according to the pre-set strategy, the drone can hover at the current position and wait for the signal to be restored, or start the automatic return program, relying on sensors such as the inertial measurement unit (IMU) to maintain attitude stability to prevent loss of control and crash. At the same time, the drone continues to try to search for satellite signals again. Once restored, it will report the status to the ground control station in time and continue the mission or return according to instructions; System failure safety protection: When the drone's own system fails (such as motor failure, flight control system abnormality, etc.), the flight control system quickly sends detailed fault information to the ground control station through the Beidou communication link, including the fault type, occurrence time and possible impact. At the same time, the drone immediately activates the fault safety mechanism, such as executing the emergency landing procedure to select a suitable landing location (open, away from crowded areas); or automatically cuts off the power supply in extreme cases to minimize the risk of accidents.

[0027] The proportional-integral-derivative (PID) control algorithm is combined with the neural network algorithm to first build the system architecture, then use the neural network model for training, then perform real-time control to correct the drone's route during flight, and finally continuously optimize and adaptively adjust the system; Building the system architecture includes data acquisition module, constructing neural network model and integrating PID controller; The data acquisition module refers to the various sensors carried by the drone, including but not limited to the Beidou positioning module to obtain high-precision location information (longitude, latitude, altitude), the inertial measurement unit (IMU) to measure the acceleration and angular velocity of the drone, and the barometer to assist in measuring altitude changes. The data collected in real time by these sensors forms the basis for subsequent algorithm processing; When building a neural network model, you need to choose a suitable neural network architecture, such as a multi-layer perceptron (MLP) or a radial basis function neural network (RBFNN). The input layer of the neural network receives raw data from the sensor, and the neurons in the hidden layer perform feature extraction and nonlinear transformation. The output layer generates adjustment suggestions for the PID control parameters. For example, for a simple MLP, the number of input layer nodes corresponds to the dimension of the sensor data, and its hidden layer can be set to 1-3 layers. The number of nodes in each layer is adjusted according to actual needs and computing resources, and the output layer usually has 3 nodes, corresponding to the adjustment values ​​of the proportional gain, integral gain, and differential gain of the PID algorithm; Integrated PID controller: The traditional PID controller is the key part of the execution control. It receives the adjusted PID parameters output by the neural network and the error information between the current position and the target position, calculates the control signal according to the PID control algorithm, and drives the UAV to adjust its flight attitude. Training a neural network model includes data preparation and model training; Data preparation refers to collecting a large amount of flight data of drones under different flight conditions at the ground control station, including sensor data under various environmental interferences (such as wind of different strengths, airflow and signal shielding caused by complex terrain, etc.), corresponding position error data, and the PID parameter values ​​that are manually debugged or empirically verified as optimal at this time. These data are divided into training set, validation set and test set, generally in the ratio of 70%, 15% and 15%; Model training is to train the neural network using the training set data. The training process uses the back propagation algorithm and takes the mean square error (MSE) as the loss function to measure the deviation between the PID parameter adjustment value output by the neural network and the actual optimal value. In each training iteration, the weight of the neural network is updated according to the loss function, so that the neural network gradually learns how to accurately adjust the PID parameters under different flight conditions to achieve the optimal route correction effect. For example, in a training batch, the input includes sensor data under strong wind interference, and the neural network outputs a set of PID parameter adjustment values, which are compared with the known optimal parameters to calculate the MSE. The weights of each layer of the neural network are adjusted through the back propagation algorithm to reduce the MSE. The training process continues for multiple epochs (rounds) until the loss on the validation set no longer decreases significantly, indicating that the model has basically converged; Real-time control of the flight process includes real-time data acquisition and preprocessing, online adjustment of PID parameters by neural network, and generation and execution of PID control signals; Real-time data acquisition and preprocessing: During the flight of the drone, the data acquisition module continuously acquires sensor data and performs preprocessing, such as removing noise (using filtering algorithms) and normalizing the data to make the data range meet the input requirements of the neural network. For example, the position data is normalized to the [0, 1] interval, and the acceleration and angular velocity data are normalized accordingly according to their reasonable ranges to ensure that the neural network can efficiently process the data. The neural network adjusts the PID parameters online. The pre-processed sensor data is input into the neural network in real time. The neural network quickly outputs adjustment suggestions for the PID parameters according to the current flight status. For example, when it detects that the drone encounters strong side winds, the neural network recognizes this interference pattern and increases the proportional gain accordingly. To quickly respond to errors while appropriately adjusting the integral gain and differential gain Optimize the control effect so that the drone can resist wind interference in time and maintain a stable route; PID control signal generation and execution: The PID parameters adjusted by the neural network are input into the PID controller together with the current position error, and the control signal is calculated according to the discrete PID formula. Taking the x-axis direction as an example, if the current drone position coordinate is ( , , ), the target waypoint coordinates are ( , , ), then the position error in the x-axis direction , combined with the neural network adjusted , , , according to the formula: Calculate the control signal Similarly, the y-axis and z-axis direction control signals can be obtained , ,These control signals are sent to the flight control system, which changes the flight attitude of the drone by adjusting the motor speed and other methods to correct the route deviation; System optimization and adaptive adjustment include online learning and updating, performance evaluation and parameter adjustment; Online learning and updating: To make the system better adapt to the ever-changing flight environment, the neural network can be set up for online learning. New flight data is collected regularly during the flight, and these data are added to the training set. The neural network is incrementally trained and the weights are updated so that it can continuously learn new interference patterns and the corresponding optimal PID parameter adjustment strategies. Performance evaluation and parameter adjustment: The flight performance of the UAV is monitored in real time at the ground control station, including indicators such as route tracking accuracy, stability and response speed. Based on these indicators, some hyperparameters of the neural network and PID controller (such as the learning rate of the neural network, the number of hidden layer nodes, the initial parameter range of the PID controller, etc.) are manually or automatically fine-tuned to further optimize the system performance and ensure that the UAV always maintains high-precision route control capabilities in complex and changing environments.

[0028] Through the organic combination of neural network algorithm and PID control algorithm, UAVs can respond to various complex flight conditions more intelligently and accurately, effectively improve the efficiency and accuracy of route correction, and provide solid guarantee for the widespread application of UAVs in many fields such as geographic surveying and mapping, agricultural plant protection, and inspection.

[0029] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The communication system for single Beidou module UAV flight is characterized by: It includes flight communication scheme and communication maintenance measures. The flight communication scheme includes Beidou short message transmission basis, data transmission optimization strategy and multi-communication mode coordination. The communication maintenance measures include communication stability guarantee measures and communication security protection scheme; The communication stability assurance measures include hardware enhancement measures, software optimization means and environmental adaptability strategies. The hardware enhancement measures are mainly achieved through antenna performance optimization and module reliability improvement. The software optimization means are mainly achieved through improvements in communication protocol robustness and data processing fault tolerance mechanisms. The environmental adaptability strategies are mainly achieved through real-time environmental monitoring and early warning and dynamic adjustment of flight plans. The communication security protection scheme includes a signal encryption and authentication system and a system security protection barrier. The signal encryption and authentication system is mainly implemented by deploying encryption algorithms and building an identity authentication framework, and the system security protection barrier is mainly implemented by software security reinforcement and redundant design assurance.

2. The single Beidou module UAV flight communication system according to claim 1, characterized in that: The antenna performance is optimized through continuous research and selection of more advanced Beidou communication antennas. For complex flight environments or long-distance mission requirements, antennas with higher gain, wider bandwidth and stronger anti-interference capabilities are used. The module reliability is improved mainly by selecting Beidou communication modules, which have built-in receiving chips and stable transmission power components to ensure stable signal reception and transmission under complex electromagnetic environments and harsh conditions of signal blocking.

3. The single Beidou module UAV flight communication system according to claim 2, characterized in that: The improvement of the robustness of the communication protocol is mainly achieved by deeply optimizing the Beidou communication protocol, reasonably configuring the data frame format in the protocol, and adding sufficient check bits for error detection and correction. The data processing fault-tolerant mechanism is mainly achieved by embedding powerful data caching and pre-sending functions in the UAV and ground control station software. The UAV side sets a data cache area to store the data to be sent according to priority. When the quality of the communication link is good, part of the data is sent in batches in advance to reduce transmission delay.

4. The single Beidou module UAV flight communication system according to claim 3, characterized in that: The real-time environmental monitoring and early warning is mainly achieved by equipping the drone with multiple types of environmental sensors to monitor weather conditions and electromagnetic environment in real time. The dynamic adjustment of the flight plan is mainly achieved by combining weather forecasts and geographic information system data resources to predict environmental changes on the drone's flight path in advance during the flight mission planning stage.

5. The single Beidou module UAV flight communication system according to claim 4, characterized in that: The encryption algorithm deployment is to fully adopt high-intensity encryption algorithms during the Beidou communication data transmission process, such as AES in the symmetric encryption algorithm, to assign unique key pairs to the drone and the ground control station, and to encrypt the data into ciphertext using the AES algorithm before sending sensitive data. The receiving end uses the same key to decrypt the data to ensure data confidentiality.

6. The single Beidou module UAV flight communication system according to claim 5, characterized in that: The identity authentication framework is constructed by establishing a two-way identity authentication mechanism based on digital signature technology. The drone and the ground control station each generate and keep a private key and a public key. When sending data, the private key is used to sign the data. When the recipient receives the data, the other party's public key is used to verify the signature and confirm the legitimacy of the identity of the other party in communication, which can effectively prevent illegal devices from accessing the communication link.

7. The single Beidou module UAV flight communication system according to claim 6, characterized in that: The software security reinforcement is achieved by regularly scanning and repairing security vulnerabilities in the UAV flight control system and ground control station software, focusing on the communication protocol stack and data processing module, and promptly patching known vulnerabilities of buffer overflow and code injection.

8. The single Beidou module UAV flight communication system according to claim 7, characterized in that: The redundant design guarantee is to equip the drone with multiple Beidou communication antennas and modules to build a redundant communication system at the hardware level if space and cost permit.

9. The control method of the single Beidou module UAV flight communication system according to claim 8, characterized in that: The following steps are involved: Step 1: Preparation process for the drone before flight; Equipment pre-inspection: Before each flight mission, the operator conducts a comprehensive inspection of the drone and Beidou module to verify whether the antenna connection is stable and whether there are any signs of looseness or damage; confirm that the module power supply is normal and whether the voltage and current are within the rated range; Positioning calibration operation: Use known high-precision positioning points to calibrate the Beidou module, place the drone at a precisely measured geographical location, start the calibration program through the ground control station, adjust the satellite signal reception parameters of the Beidou module, so that the positioning data accurately matches the known coordinates to improve positioning accuracy; Flight plan setting and uploading: The operator plans the flight route, sets the flight altitude, speed and task parameters in detail in the ground control station software according to the mission requirements. After the setting is completed, the flight plan data is transmitted to the drone through the Beidou communication link. The drone flight control system receives and stores it, and then executes the mission accordingly during the flight; Step 2: Control strategy during the flight of the drone; Precise position control: The ground control station receives the UAV position information fed back by the Beidou module in real time, and compares and analyzes it with the preset flight route. Once the UAV is found to deviate from the route, the control system formed by the proportional-integral-differential PID control algorithm combined with the neural network algorithm is immediately used to realize intelligent calculation and correction instructions; Altitude and speed stability control: also based on Beidou module data, the ground control station then sends altitude and speed control instructions according to mission characteristics; Step 3: Response mechanism for emergencies during drone flight; Signal loss emergency response: If the Beidou module signal is interrupted during flight, the drone flight control system automatically switches to the preset safety mode; System failure safety protection: When the drone's own system fails, the flight control system quickly sends detailed fault information to the ground control station through the Beidou communication link, including the fault type, occurrence time and possible impact.

10. The control method of the single Beidou module UAV flight communication system according to claim 9, characterized in that: The proportional-integral-differential PID control algorithm is combined with a neural network algorithm to first build a system architecture, then use a neural network model for training, and then perform real-time control to correct the drone's route during the flight of the drone, and finally continuously optimize and adaptively adjust the system.

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