An air-ground cooperative unmanned aerial vehicle multi-mode wireless communication protocol adaptive switching system

Abstract

The application provides a kind of air-ground coordinated unmanned aerial vehicle multi-mode wireless communication protocol adaptive switching system, belongs to unmanned aerial vehicle air-ground coordinated communication technical field;The application acquires the multi-dimensional parameters of communication link state, unmanned aerial vehicle flight attitude and ground terminal load in real time by differentiating frequency, dynamically allocates the weight of each parameter using weighted entropy method and quantitatively evaluates the quality of multi-protocol communication, adaptively generates switching threshold interval according to differentiated service type, task priority and electromagnetic interference scene, intelligently selects the optimal communication protocol;A hierarchical switching mechanism is adopted, with seamless soft switching as the main and emergency hard switching as the auxiliary, and based on gradient descent algorithm, the closed-loop iterative optimization of model weight and decision threshold is completed, and a multi-scenario adaptive parameter database is constructed.The application realizes intelligent evaluation, accurate decision, seamless switching and closed-loop optimization of multi-mode communication protocol, and improves the stability, real-time performance and scene adaptability of unmanned aerial vehicle air-ground coordinated communication.

Description

Technical Field

[0001] This invention provides an adaptive switching system for multiple wireless communication protocols of air-to-ground cooperative UAVs, belonging to the field of UAV air-to-ground cooperative communication technology. Background Technology

[0002] With the rapid development of UAV-based air-to-ground collaborative operation technology, UAVs have been widely used in many fields such as power line inspection, environmental monitoring, emergency rescue, and aerial surveying. The core guarantee for UAV-based air-to-ground collaborative operations is the air-to-ground wireless communication link. The stability, real-time performance, and bandwidth adaptability of the communication directly determine the safety and efficiency of UAV operations.

[0003] Currently, most traditional UAV air-to-ground communication systems employ a single communication protocol or a multi-protocol communication method with fixed switching logic, resulting in numerous technical shortcomings. Firstly, they suffer from poor communication standard adaptability. Existing communication modules mostly support only 4G / 5G, WiFi, or LoRa communication, failing to meet diverse operational needs such as short-range high-speed transmission, long-range low-power communication, and emergency communication in extreme scenarios. Secondly, their protocol switching mechanisms are rigid, often employing fixed thresholds and weights for evaluation. This fails to adapt to dynamic changes in UAV flight attitude, airspace electromagnetic interference, terminal load, and service type, easily leading to communication link stuttering, packet loss, and excessive latency jitter. Thirdly, their switching reliability is low. Traditional hard switching methods easily cause brief communication link interruptions, resulting in data loss and transmission timing errors, failing to meet the high-reliability service requirements such as low-latency control and high-definition image transmission. Fourthly, they lack a closed-loop optimization mechanism, failing to iteratively optimize the evaluation model and switching strategy based on real-time link operation data. This results in consistently poor scenario adaptability, with a high risk of communication failure in high-speed maneuvering, strong electromagnetic interference, and ultra-long-distance operation scenarios. Meanwhile, existing technologies generally employ fixed-frequency parameter acquisition mechanisms, which cannot dynamically adapt to factors such as operating distance, flight altitude, and electromagnetic interference intensity. This easily leads to data redundancy or missing critical status information, resulting in distorted communication quality assessment results and delayed protocol switching decisions. Furthermore, existing switching strategies often focus only on a single communication link indicator, failing to differentiate based on service type and task priority. High-priority control services are easily squeezed out by low-priority transmission services, resulting in insufficient reliability and specificity of overall air-to-ground collaborative communication, making it difficult to adapt to complex and ever-changing large-scale UAV collaborative operation scenarios. Additionally, existing technologies often use fixed acquisition frequencies for communication status parameter acquisition, failing to match the differentiated operating scenarios of UAVs at varying distances, altitudes, and complex interference levels. This leads to data redundancy or missing critical status information, further reducing the accuracy of protocol assessment and switching. Moreover, conventional communication switching strategies only consider single link communication indicators, without combining UAV task priorities and service attributes for differentiated adaptation. This easily results in high-priority tasks having their communication resources squeezed out and low-priority services excessively consuming bandwidth, severely impacting the overall reliability of air-to-ground collaborative operations.

[0004] To address the aforementioned shortcomings of existing technologies, there is an urgent need to design an adaptive switching system for multi-mode wireless communication protocols of air-to-ground collaborative UAVs that can dynamically evaluate multiple parameters, make intelligent decisions, seamlessly switch between modes, and possess closed-loop iterative optimization capabilities, in order to adapt to the air-to-ground collaborative communication needs of UAVs in all scenarios. Summary of the Invention

[0005] This invention aims to solve the technical problems of rigid switching of air-to-ground communication protocols for existing UAVs, poor scene adaptability, low switching reliability, and lack of adaptive optimization capabilities. It provides an adaptive switching system for multiple wireless communication protocols for air-to-ground collaborative UAVs, which realizes intelligent evaluation, accurate decision-making, seamless switching and closed-loop optimization of multiple communication protocols, and comprehensively improves the stability, real-time performance and scene adaptability of UAV air-to-ground collaborative communication.

[0006] To address the aforementioned problems, the present invention proposes the following technical solution: an adaptive switching method for multi-mode wireless communication protocols for air-to-ground cooperative UAVs, applied to an air-to-ground cooperative communication system. The air-to-ground cooperative communication system includes a ground control terminal, several cooperative UAV nodes, and a multi-mode wireless communication module. The multi-mode wireless communication module is compatible with at least four wireless communication protocols: 4G / 5G, WiFi, LoRa, and BeiDou short message. The method includes the following steps: S1. Real-time parameter acquisition: Real-time acquisition of multi-dimensional status parameters of the air-ground cooperative communication link. The multi-dimensional status parameters include the signal-to-noise ratio of the communication link, signal attenuation value, communication bandwidth margin, delay jitter value, packet loss rate, UAV flight position and attitude parameters, and ground terminal communication load parameters. S2. Quantitative evaluation of communication quality: Construct a multi-protocol communication quality evaluation model, normalize and preprocess the collected multi-dimensional state parameters and remove abnormal interference data, dynamically assign weights to each state parameter based on the weighted entropy weighting method, and calculate the comprehensive communication quality score corresponding to each candidate wireless communication protocol in real time. S3. Optimal Protocol Intelligent Decision: Based on the priority of UAV air-ground collaborative operation tasks, the type of real-time data transmission service, and the current airspace electromagnetic interference scenario, an adaptive communication protocol switching decision threshold range is generated. The comprehensive communication quality score of each candidate wireless communication protocol is matched with the switching decision threshold range to select the optimal adapted communication protocol in the current scenario. S4. Hierarchical Adaptive Link Switching: Determine whether the current working communication protocol is consistent with the optimal adapted communication protocol. If they are consistent, maintain the normal operation of the current air-to-ground communication link. If they are inconsistent, prioritize the execution of the seamless soft handover process to complete the reconfiguration of communication protocol parameters, link handshake verification, and data buffering and retransmission, thereby achieving uninterrupted switching of the air-to-ground communication link. S5. Closed-loop iterative optimization and control: After the protocol switch is completed, the real-time operating status of the new communication link is continuously monitored. Based on the link operation feedback data, the parameter weights and switching decision thresholds of the multi-protocol communication quality assessment model are dynamically updated iteratively to form a scenario-adaptive closed-loop control mechanism.

[0007] Furthermore, in step S1, the UAV flight position and attitude parameters include the UAV's real-time flight altitude, flight speed, horizontal offset distance relative to the ground terminal, pitch angle, and roll angle; the ground terminal communication load parameters include the terminal's real-time channel occupancy rate, number of concurrent connections, and data forwarding latency. Different parameter acquisition frequencies are configured according to different airspace operation scenarios. Specifically, the parameter acquisition frequency for close-range low-altitude collaborative operation scenarios is set to 100Hz-200Hz, while the parameter acquisition frequency for long-range high-altitude operation scenarios and complex strong electromagnetic interference scenarios is set to 300Hz-500Hz.

[0008] Furthermore, in step S2, the normalization preprocessing of the collected multidimensional state parameters and the removal of abnormal interference data specifically include: The range standardization algorithm is used to uniformly map multidimensional state parameters of different dimensions and orders of magnitude to the standard numerical range of [0,1] to achieve parameter standardization. The 3σ gross error discrimination criterion is used to identify and remove invalid data caused by spatial electromagnetic interference, instantaneous failure of communication module, and abnormal sensor acquisition, so as to ensure the validity and accuracy of the parameters input to the multi-protocol communication quality assessment model. The method of dynamically assigning weights to each state parameter based on weighted entropy includes: calculating the corresponding information entropy based on the real-time data variation of each state parameter; the smaller the information entropy value of a parameter, the higher the degree of influence of the parameter on the current communication quality, and the larger the corresponding weight coefficient; and updating the weights of each parameter in real time to eliminate the defects of poor scenario adaptability and low evaluation accuracy of the fixed weight evaluation method.

[0009] Furthermore, in step S3, the real-time data transmission service types are divided into low-latency control services, high-bandwidth image transmission services, long-distance emergency communication services, and low-power inspection services. For different service types, dedicated switching decision threshold ranges are preset and adaptively fine-tuned. Specifically, low-latency control services are prioritized to match link latency and latency jitter parameter thresholds; high-bandwidth image transmission services are prioritized to match communication bandwidth and packet loss rate parameter thresholds; long-distance emergency communication services are prioritized to match signal coverage strength and link stability parameter thresholds; and low-power inspection services are prioritized to match module power consumption and signal attenuation parameter thresholds.

[0010] Furthermore, in step S4, the seamless soft handover process specifically includes: Without disconnecting the current communication link, the communication module corresponding to the optimal adapted communication protocol is pre-activated to complete the target channel pre-scanning, communication key pre-verification and link parameter pre-configuration, and to build a parallel data cache channel for the old and new communication links. During the handover process, the real-time service data of air-to-ground interaction is cached to the parallel data cache channel. After the handshake of the new communication link is established, the cached data is transmitted. The communication clocks of the UAV node and the ground control terminal are synchronously calibrated to eliminate the time delay deviation caused by the protocol switch and avoid data packet loss, service interruption and data timing disorder.

[0011] Furthermore, step S4 is also configured with an emergency hard handover mechanism, which includes: real-time monitoring of the current communication link operation status; when a sudden interruption of the communication link is detected, the signal attenuation exceeds the preset limit threshold, or the soft handover fails due to strong electromagnetic interference across the entire domain, the seamless soft handover process is immediately terminated, the preset emergency communication protocol fast handover logic is triggered, and the air-to-ground communication link is rapidly reconstructed to ensure the continuity of air-to-ground collaborative communication in extreme scenarios.

[0012] Furthermore, in step S5, the closed-loop iterative optimization control mechanism specifically includes: The system periodically collects communication link data during the stable operation phase after protocol switching, compares the differences in latency, bandwidth, packet loss rate, and stability of the link before and after switching, and iteratively optimizes the weight allocation coefficients and scene switching decision thresholds of the multi-protocol communication quality assessment model based on the gradient descent algorithm. It also establishes a multi-scenario parameter database that includes complex airspace, strong electromagnetic interference, high-speed UAV maneuvering, and ultra-long-distance transmission, and achieves accurate adaptive switching of communication protocols under different operating environments based on scenario matching.

[0013] An adaptive switching system for multiple wireless communication protocols of an air-to-ground cooperative UAV is provided for executing the aforementioned adaptive switching method for multiple wireless communication protocols of an air-to-ground cooperative UAV. The system includes: The parameter acquisition module is used to collect multi-dimensional status parameters of the air-to-ground cooperative communication link, UAV flight attitude and position parameters, and ground terminal communication load parameters in real time. The quality assessment module has a built-in multi-protocol communication quality assessment model, which is used to perform standardized preprocessing of collected multi-dimensional parameters, outlier data removal, dynamic weight allocation, and calculation of comprehensive quality scores for each communication protocol. The decision analysis module is used to adaptively generate a switching decision threshold range based on the priority of the task, the type of service transmission, and the airspace interference scenario, and to match and filter the optimal compatible communication protocol. The link switching module is connected to the quality assessment module and the decision analysis module respectively, and is used to perform seamless soft handover and emergency hard handover in extreme scenarios to achieve uninterrupted and highly reliable handover of air-to-ground communication protocols. The iterative control module is used to monitor the operating status of the communication link in real time after the handover, and to iteratively optimize the model parameters and handover decision threshold based on the link feedback data to achieve scenario adaptive optimization.

[0014] Furthermore, the multi-mode wireless communication module integrates 4G / 5G broadband communication, WiFi short-range high-speed communication, LoRa low-power long-range communication, and Beidou short message emergency communication functions. It can automatically complete the parameter configuration, channel adaptation, link establishment, and rapid switching of multiple communication protocols according to the control instructions of the decision analysis module.

[0015] Furthermore, the system also includes a data cache synchronization module, which is communicatively connected to the link switching module. This module is used to temporarily cache real-time air-to-ground interactive business data during the communication protocol switching process, synchronously calibrate the communication timing between the UAV and the ground control terminal, and prevent data loss, transmission lag, and timing offset faults during the switching process.

[0016] Due to the adoption of the above technical solution, the beneficial effects of the air-to-ground cooperative UAV multi-standard wireless communication protocol adaptive switching system of the present invention are as follows: 1. Multi-parameter dynamic acquisition and accurate evaluation: This invention acquires multi-dimensional parameters of communication link, UAV attitude, and ground terminal load. Combined with differentiated acquisition frequency, it ensures data validity through range standardization and 3σ error elimination algorithm. The weighted entropy weight method is used to dynamically allocate parameter weights, which solves the problems of low accuracy and poor scene adaptability of traditional fixed weight evaluation, and greatly improves the accuracy of communication quality evaluation.

[0017] 2. Scenario-based intelligent decision-making adaptation: Dedicated threshold ranges are configured for four mainstream drone transmission services. The decision-making criteria are adaptively adjusted based on task priority and electromagnetic interference scenarios. It can accurately match the adaptation scenarios of WiFi, 4G / 5G, LoRa, and Beidou short message, and realize personalized and intelligent decision-making for protocol switching.

[0018] 3. High reliability guarantee of hierarchical handover: The hierarchical handover mechanism adopts seamless soft handover as the main method and emergency hard handover as the auxiliary method. It achieves zero-interruption handover in normal scenarios through parallel data caching and clock synchronization, and solves communication failure problems caused by extreme interference and sudden link interruption through emergency hard handover mechanism, so as to comprehensively guarantee the continuity of air-to-ground communication.

[0019] 4. Closed-loop iterative adaptive optimization: Based on the gradient descent algorithm, the model parameters and switching thresholds are continuously iteratively optimized, a multi-scenario database is built, and the system performance is autonomously upgraded. It can adapt to complex dynamic scenarios such as high-speed maneuvering of UAVs, ultra-long distance, and strong electromagnetic interference, and the long-term operational stability is continuously improved. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a block diagram of the overall system architecture of an adaptive switching system for multi-mode wireless communication protocols for air-to-ground cooperative unmanned aerial vehicles (UAVs) according to the present invention. Figure 2 This is a flowchart illustrating an embodiment of the adaptive switching method for air-ground cooperative communication protocols of the present invention, which is a multi-mode wireless communication protocol adaptive switching system for air-ground cooperative unmanned aerial vehicles. Figure 3 This is a schematic diagram of the hierarchical adaptive link switching process of an embodiment of the air-ground cooperative UAV multi-mode wireless communication protocol adaptive switching system of the present invention; Figure 4 This is a schematic diagram of the dynamic iterative process of the weight of the multi-protocol communication quality assessment model in an embodiment of the adaptive switching system of multi-mode wireless communication protocols for air-ground cooperative UAVs according to the present invention. Figure 5 This is a block diagram of the adaptive decision threshold matching logic for multi-mode wireless communication protocols in an embodiment of the air-ground cooperative UAV multi-mode wireless communication protocol adaptive switching system of the present invention. Detailed Implementation

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1: Adaptive switching in low-altitude, short-range, low-power inspection scenarios This embodiment is applied to routine urban low-altitude and park close-range inspection operations using drones. The operating altitude is 50-200m, the horizontal offset distance of the drone relative to the ground terminal is ≤1km, there is no strong electromagnetic interference, and the core business is low-power inspection, which continuously collects environmental data and equipment status data at low speed. It has high requirements for communication power consumption and signal attenuation indicators, but low requirements for instantaneous bandwidth.

[0023] In this embodiment, the system performs the adaptive switching process as follows: S1. Real-time parameter acquisition: This scenario is a close-range low-altitude collaborative operation scenario. The parameter acquisition frequency is set to 150Hz. Attitude parameters such as UAV flight altitude, low-speed flight speed, and close-range horizontal offset distance are acquired in real time. At the same time, multi-dimensional parameters such as link signal attenuation value, module power consumption, channel occupancy rate, and packet loss rate are also acquired.

[0024] S2. Quantitative Evaluation of Communication Quality: All collected parameters are uniformly mapped to the [0,1] interval using the range standardization algorithm. Abnormal data generated by instantaneous sensor jitter during the inspection process are eliminated using the 3σ coarse error discrimination criterion. The information entropy of each parameter is calculated based on the weighted entropy method. In this scenario, the parameter variation of module power consumption and signal attenuation value is higher and the information entropy is smaller. The system automatically assigns higher weights to them and weakens the weights of parameters such as bandwidth and latency. Finally, the comprehensive score of four protocols, namely WiFi, 4G / 5G, LoRa and Beidou short message, is calculated. Among them, the LoRa protocol has the best score due to its low power consumption and low signal attenuation characteristics.

[0025] S3, Optimal Protocol Intelligent Decision: The system identifies the current service as a low-power inspection service, adaptively matches the threshold range specific to low-power services, prioritizes the verification of module power consumption and signal attenuation parameters, determines that the LoRa protocol is fully adapted to the current short-range, low-power, and stable inspection scenario, and identifies LoRa as the optimal communication protocol.

[0026] S4. Hierarchical Adaptive Link Switching: If the initial communication protocol of the current drone is WiFi short-range communication, the system determines that the protocol is incompatible and initiates a seamless soft switchover process. It pre-activates the LoRa communication module, completes channel pre-scanning, key pre-verification, and parameter configuration, and builds a parallel cache channel for the old and new links, caching real-time inspection data. Data transmission resumes after the LoRa link handshake is established, and the communication clock is calibrated synchronously. There are no data interruptions or packet loss issues throughout the process. This scenario has no sudden interference and does not require triggering an emergency hard switchover mechanism.

[0027] S5. Closed-loop iterative optimization and control: Continuously monitor the LoRa link operation status, collect power consumption, attenuation, and packet loss data during stable operation, compare the operation indicators of the WiFi link before switching, fine-tune the parameter weights and switching thresholds in low-power scenarios based on the gradient descent algorithm, update the adaptation parameters of near-range low-altitude inspection scenarios in the scenario database, and optimize the accuracy of subsequent protocol switching in the same scenario.

[0028] This embodiment realizes adaptive and precise switching of the LoRa protocol in low-altitude, close-range inspection scenarios, significantly reducing the power consumption of UAV inspection communication, extending the UAV's endurance operation time, and ensuring the long-term stability of routine inspection communication.

[0029] Example 2: Adaptive switching of high-altitude long-distance high-definition image transmission scenarios This embodiment is applied to scenarios such as high-altitude aerial photography, large-scale surveying and mapping, and long-distance inspection of power lines using drones. The operating altitude is 200-1000m, the horizontal offset distance of the drone relative to the ground terminal is 3-10km, the flight speed is relatively fast, and the core business is high-bandwidth image transmission, which requires real-time transmission of 4K high-definition video and aerial image data, and has extremely high requirements for communication bandwidth, packet loss rate, and link stability.

[0030] In this embodiment, the system performs the adaptive switching process as follows: S1. Real-time parameter acquisition: This scenario is a long-distance high-altitude operation scenario. The parameter acquisition frequency is set to 400Hz. The high-frequency acquisition of attitude parameters such as the high-speed flight speed, altitude, long-distance horizontal offset distance, and pitch angle of the UAV is carried out. At the same time, core parameters such as communication bandwidth margin, packet loss rate, signal-to-noise ratio, latency jitter, and ground terminal channel occupancy rate are collected in real time to accurately capture the dynamic changes of the link under high-speed maneuvering conditions.

[0031] S2. Quantitative evaluation of communication quality: Standardize and preprocess the multi-dimensional parameters collected at high frequency to remove instantaneous abnormal data caused by sudden changes in the maneuvering attitude of the UAV; dynamically allocate weights based on the weighted entropy method. In this scenario, the communication bandwidth margin, packet loss rate, and link signal-to-noise ratio parameters have the greatest variability and the lowest information entropy. The system assigns core weights to them and weakens the weight of power consumption parameters. The comprehensive scores of the four types of protocols are calculated respectively. The 4G / 5G broadband communication protocol has the best score due to its large bandwidth and low packet loss rate characteristics.

[0032] S3, Optimal Protocol Intelligent Decision: The system identifies the current service as a high-bandwidth image transmission service, calls the dedicated switching threshold range, prioritizes matching communication bandwidth, packet loss rate, and link stability parameters, compares the performance of each protocol, determines that the 4G / 5G protocol can meet the bandwidth requirements of real-time transmission of high-definition images, and selects 4G / 5G as the optimal adaptation protocol.

[0033] S4. Hierarchical Adaptive Link Switching: If the drone initially uses the LoRa low-power communication protocol, the system initiates seamless soft switching, pre-activates the 4G / 5G communication module, completes broadband channel pre-configuration and link handshake preparation, and caches high-definition image data streams through parallel buffer channels to avoid image frame loss and stuttering during switching, thus completing uninterrupted link switching and ensuring real-time, clear transmission of aerial video. For minor link fluctuations caused by the drone's high-speed maneuvers, the system continuously maintains dynamic link adaptation without hard switching trigger conditions.

[0034] S5. Closed-loop iterative optimization and control: Collect core indicators such as bandwidth utilization, image transmission frame rate, and packet loss rate after 4G / 5G link switching, compare the difference with the LoRa link indicators before switching, and iteratively optimize the weight coefficient and switching threshold of high-bandwidth service scenarios through gradient descent algorithm, improve the database parameters of high-altitude, long-distance, and high-speed maneuvering scenarios, and improve the protocol adaptation accuracy under complex maneuvering conditions.

[0035] This embodiment effectively solves the problems of insufficient bandwidth, image transmission lag, and severe packet loss in traditional long-distance aerial photography scenarios, achieves accurate protocol adaptation for high-bandwidth services, and ensures high-definition data transmission quality for high-altitude surveying and long-distance inspection.

[0036] Example 3: Adaptive switching of emergency rescue scenarios during strong electromagnetic interference This embodiment is applied to extreme operational scenarios such as emergency rescue in mountainous areas, strong electromagnetic interference in complex factory areas, and severe airspace signal obstruction. The drone operates at a distance of 5-15km, and there is strong electromagnetic interference throughout the airspace. Conventional civilian communication signals are severely attenuated. The core business is long-distance emergency communication. The primary requirement is to ensure the continuity of the communication link. The requirements for signal coverage, anti-interference ability, and link stability are extremely high, while the requirements for transmission bandwidth and latency are moderately relaxed.

[0037] In this embodiment, the system performs the adaptive switching process as follows: S1. Real-time parameter acquisition: This scenario is a complex and strong electromagnetic interference scenario. The parameter acquisition frequency is set to 500Hz. The link signal attenuation value, electromagnetic interference intensity, communication delay, packet loss rate, UAV long-distance position parameters and ground terminal load parameters are collected at an ultra-high frequency to capture the abnormal state of the link under extreme scenarios.

[0038] S2. Quantitative Assessment of Communication Quality: The parameters collected by UHF are standardized, and a large number of transient abnormal data caused by electromagnetic interference are eliminated in batches using the 3σ criterion to ensure effective parameter input. Based on the weighted entropy method, signal coverage strength, signal attenuation value, and link stability are used as core weight parameters, while the weight of bandwidth and power consumption parameters is weakened. The assessment results show that WiFi and 4G / 5G protocols are severely affected by electromagnetic interference and have extremely low scores. The BeiDou short message protocol has significant advantages in anti-interference and ultra-long-distance coverage and has the highest comprehensive score.

[0039] S3. Optimal Protocol Intelligent Decision: The system identifies the current scenario as a long-distance emergency communication service with strong electromagnetic interference, adaptively matches the threshold range specific to the emergency service, prioritizes the verification of signal coverage and link stability parameters, and determines that BeiDou short message is the only optimal adaptation protocol under the current extreme scenario.

[0040] S4. Hierarchical Adaptive Link Switching: The initial working protocol of the UAV is 4G / 5G. The system initiates a seamless soft handover process. However, due to strong electromagnetic interference across the entire domain, the 4G / 5G link continues to deteriorate and the soft handover handshake verification fails. The system monitors the soft handover failure in real time and the signal attenuation exceeds the limit threshold. It immediately terminates the soft handover, triggers the emergency hard handover mechanism, and rapidly starts the BeiDou short message emergency communication protocol to quickly reconstruct the air-to-ground communication link, ensuring the continuous transmission of emergency rescue instructions and location information and avoiding complete communication interruption.

[0041] S5. Closed-loop iterative optimization and control: Record the switching data and link operation data under this strong electromagnetic interference scenario, compare the differences in the effects of soft and hard switching, iteratively optimize the switching threshold and model weights in extreme interference scenarios, supplement the database samples for strong electromagnetic and ultra-long-distance emergency scenarios, and improve the reliability of emergency switching of the system in extreme and severe scenarios.

[0042] This embodiment solves the problem of conventional communication protocols failing in extreme electromagnetic interference scenarios through a hierarchical switching mechanism. Relying on the emergency communication capabilities of BeiDou short messages, it ensures uninterrupted air-to-ground communication in emergency rescue scenarios, greatly improving the survivability and operational reliability of UAVs in extreme operating scenarios.

[0043] The present invention and its embodiments have been described above. This description is not restrictive. In short, if a person skilled in the art is inspired by this description and designs a similar structure and embodiment without departing from the spirit of the present invention, such design should fall within the protection scope of the present invention.

Claims

1. A method for adaptive switching of multiple wireless communication protocols for air-to-ground cooperative unmanned aerial vehicles (UAVs), characterized in that, The method is applied to an air-to-ground cooperative communication system, which includes a ground control terminal, several cooperative UAV nodes, and a multi-standard wireless communication module. The multi-standard wireless communication module is compatible with at least four wireless communication protocols: 4G / 5G, WiFi, LoRa, and BeiDou short message. The method includes the following steps: S1. Real-time parameter acquisition: Real-time acquisition of multi-dimensional status parameters of the air-ground cooperative communication link. The multi-dimensional status parameters include the signal-to-noise ratio of the communication link, signal attenuation value, communication bandwidth margin, delay jitter value, packet loss rate, UAV flight position and attitude parameters, and ground terminal communication load parameters. S2. Quantitative evaluation of communication quality: Construct a multi-protocol communication quality evaluation model, normalize and preprocess the collected multi-dimensional state parameters and remove abnormal interference data, dynamically assign weights to each state parameter based on the weighted entropy weighting method, and calculate the comprehensive communication quality score corresponding to each candidate wireless communication protocol in real time. S3. Optimal Protocol Intelligent Decision: Based on the priority of UAV air-ground collaborative operation tasks, the type of real-time data transmission service, and the current airspace electromagnetic interference scenario, an adaptive communication protocol switching decision threshold range is generated. The comprehensive communication quality score of each candidate wireless communication protocol is matched with the switching decision threshold range to select the optimal adapted communication protocol in the current scenario. S4. Hierarchical adaptive link switching: Determine whether the current working communication protocol is consistent with the optimal adapted communication protocol. If they are consistent, maintain the normal operation of the current air-to-ground communication link. If there is a discrepancy, the seamless soft handover process will be executed first to complete the reconfiguration of communication protocol parameters, link handshake verification and data buffering and retransmission, so as to achieve uninterrupted handover of air-to-ground communication links. S5. Closed-loop iterative optimization and control: After the protocol switch is completed, the real-time operating status of the new communication link is continuously monitored. Based on the link operation feedback data, the parameter weights and switching decision thresholds of the multi-protocol communication quality assessment model are dynamically updated iteratively to form a scenario-adaptive closed-loop control mechanism.

2. The adaptive switching method for multi-mode wireless communication protocols of an air-to-ground cooperative UAV according to claim 1, characterized in that, In step S1, the UAV flight position and attitude parameters include the UAV's real-time flight altitude, flight speed, horizontal offset distance relative to the ground terminal, pitch angle, and roll angle; the ground terminal communication load parameters include the terminal's real-time channel occupancy rate, number of concurrent connections, and data forwarding latency. Different parameter acquisition frequencies are configured according to different airspace operation scenarios. Specifically, the parameter acquisition frequency for close-range low-altitude collaborative operation scenarios is set to 100Hz-200Hz, while the parameter acquisition frequency for long-range high-altitude operation scenarios and complex strong electromagnetic interference scenarios is set to 300Hz-500Hz.

3. The adaptive switching method for multi-mode wireless communication protocols of an air-to-ground cooperative UAV according to claim 1, characterized in that, In step S2, the normalization preprocessing of the collected multidimensional state parameters and the removal of abnormal interference data specifically include: The range standardization algorithm is used to uniformly map multidimensional state parameters of different dimensions and orders of magnitude to the standard numerical range of [0,1] to achieve parameter standardization. The 3σ gross error discrimination criterion is used to identify and remove invalid data caused by spatial electromagnetic interference, instantaneous failure of communication module, and abnormal sensor acquisition, so as to ensure the validity and accuracy of the parameters input to the multi-protocol communication quality assessment model. The method of dynamically assigning weights to each state parameter based on weighted entropy includes: calculating the corresponding information entropy based on the real-time data variation of each state parameter; the smaller the information entropy value of a parameter, the higher the degree of influence of the parameter on the current communication quality, and the larger the corresponding weight coefficient; and updating the weights of each parameter in real time to eliminate the defects of poor scenario adaptability and low evaluation accuracy of the fixed weight evaluation method.

4. The adaptive switching method for multi-mode wireless communication protocols of an air-to-ground cooperative UAV according to claim 1, characterized in that, In step S3, the real-time data transmission service types are divided into low-latency control services, high-bandwidth image transmission services, long-distance emergency communication services, and low-power inspection services. For different service types, dedicated switching decision threshold ranges are preset and adaptively fine-tuned. Specifically, low-latency control services are prioritized to match link latency and latency jitter parameter thresholds; high-bandwidth image transmission services are prioritized to match communication bandwidth and packet loss rate parameter thresholds; long-distance emergency communication services are prioritized to match signal coverage strength and link stability parameter thresholds; and low-power inspection services are prioritized to match module power consumption and signal attenuation parameter thresholds.

5. The adaptive switching method for multi-mode wireless communication protocols of an air-to-ground cooperative UAV according to claim 1, characterized in that, In step S4, the seamless soft handover process specifically includes: Without disconnecting the current communication link, the communication module corresponding to the optimal adapted communication protocol is pre-activated to complete the target channel pre-scanning, communication key pre-verification and link parameter pre-configuration, and to build a parallel data cache channel for the old and new communication links. During the handover process, the real-time service data of air-to-ground interaction is cached to the parallel data cache channel. After the handshake of the new communication link is established, the cached data is transmitted. The communication clocks of the UAV node and the ground control terminal are synchronously calibrated to eliminate the time delay deviation caused by the protocol switch and avoid data packet loss, service interruption and data timing disorder.

6. The adaptive switching method for multi-mode wireless communication protocols of an air-to-ground cooperative UAV according to claim 1, characterized in that, Step S4 is also configured with an emergency hard handover mechanism, which includes: real-time monitoring of the current communication link operation status; when a sudden interruption of the communication link is detected, the signal attenuation exceeds the preset limit threshold, or the soft handover fails due to strong electromagnetic interference across the entire domain, the seamless soft handover process is immediately terminated, the preset emergency communication protocol fast handover logic is triggered, and the air-to-ground communication link is rapidly reconstructed to ensure the continuity of air-to-ground collaborative communication in extreme scenarios.

7. The adaptive switching method for multi-mode wireless communication protocols of an air-to-ground cooperative UAV according to claim 1, characterized in that, In step S5, the closed-loop iterative optimization and control mechanism specifically includes: The system periodically collects communication link data during the stable operation phase after protocol switching, compares the differences in latency, bandwidth, packet loss rate, and stability of the link before and after switching, and iteratively optimizes the weight allocation coefficients and scene switching decision thresholds of the multi-protocol communication quality assessment model based on the gradient descent algorithm. It also establishes a multi-scenario parameter database that includes complex airspace, strong electromagnetic interference, high-speed UAV maneuvering, and ultra-long-distance transmission, and achieves accurate adaptive switching of communication protocols under different operating environments based on scenario matching.

8. An adaptive switching system for multi-mode wireless communication protocols for air-to-ground cooperative unmanned aerial vehicles (UAVs), characterized in that, The system is used to execute the adaptive switching method for multi-mode wireless communication protocols of an air-to-ground cooperative unmanned aerial vehicle as described in any one of claims 1-7, the system comprising: The parameter acquisition module is used to collect multi-dimensional status parameters of the air-to-ground cooperative communication link, UAV flight position and attitude parameters, and ground terminal communication load parameters in real time. The quality assessment module has a built-in multi-protocol communication quality assessment model, which is used to perform standardized preprocessing of collected multi-dimensional parameters, outlier data removal, dynamic weight allocation, and calculation of comprehensive quality scores for each communication protocol. The decision analysis module is used to adaptively generate a switching decision threshold range based on the priority of the task, the type of service transmission, and the airspace interference scenario, and to match and filter the optimal adaptive communication protocol. The link switching module is connected to the quality assessment module and the decision analysis module respectively, and is used to perform seamless soft handover and emergency hard handover in extreme scenarios to achieve uninterrupted and highly reliable handover of air-to-ground communication protocols. The iterative control module is used to monitor the operating status of the communication link in real time after the handover, and to iteratively optimize the model parameters and handover decision threshold based on the link feedback data to achieve scenario adaptive optimization.

9. The adaptive switching system for multi-mode wireless communication protocols of air-to-ground cooperative UAVs according to claim 8, characterized in that, The multi-mode wireless communication module integrates 4G / 5G broadband communication, WiFi short-range high-speed communication, LoRa low-power long-range communication, and Beidou short message emergency communication functions. It can automatically complete the parameter configuration, channel adaptation, link establishment, and rapid switching of multiple communication protocols according to the control instructions of the decision analysis module.

10. The adaptive switching system for multi-mode wireless communication protocols of air-to-ground cooperative UAVs according to claim 8, characterized in that, The system also includes a data cache synchronization module, which is communicatively connected to the link switching module. This module is used to temporarily cache real-time air-to-ground interactive business data during the communication protocol switching process, synchronously calibrate the communication timing between the UAV and the ground control terminal, and prevent data loss, transmission lag, and timing offset faults during the switching process.

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