Unmanned aerial vehicle communication base station screening method and system based on location awareness and medium

Abstract

The invention provides an unmanned aerial vehicle communication base station screening method, system and device based on position awareness and a medium, and the method comprises the steps: positioning an unmanned aerial vehicle in real time through a GNSS, and obtaining the three-dimensional position information; according to the three-dimensional position information, candidate base stations in a current position visible range are retrieved in an airspace communication map database; scoring the candidate base stations by adopting a scoring function, and comparing the candidate base station with the highest score with the currently connected base station to screen out a target base station; and controlling the unmanned aerial vehicle to connect the base station to the target base station so as to solve the problems that the communication base station of the unmanned aerial vehicle does not maintain a communication map, a communication quality model in an airspace cannot be established according to historical measurement or geographic features, and the system lacks continuous optimization capability and adaptive capability.

Description

Technical Field

[0001] This invention relates to the fields of unmanned aerial vehicle (UAV) communication technology and wireless network management technology, and in particular to a method, system, device and medium for screening UAV communication base stations based on location awareness. Background Technology

[0002] With the increasing application of drones in industries such as railway inspection, power line inspection, traffic monitoring, oil pipeline inspection, and environmental monitoring, higher demands are being placed on the communication continuity and link stability of drones flying at medium and high altitudes. Currently, the mainstream drone communication methods mainly rely on terrestrial cellular communication networks such as 4G / 5G or satellite links. However, because traditional cellular base station antennas generally adopt a downtilt design, the coverage center is concentrated in the ground area. When drones fly in airspace above 300 meters, they are often at the edge of coverage where signals from multiple base stations interfere with each other. This leads to large fluctuations in signal quality, frequent connection switching, and problems such as communication interruptions or "ping-pong switching." If attempts are made to achieve air coverage by adjusting the base station's transmission direction, it will cause the main beams of multiple base stations to overlap at high altitudes, resulting in multiple selectable base stations in the same area, further exacerbating signal interference and switching chaos.

[0003] Especially in high-speed, uncontrollable, or cross-regional drone patrol missions, traditional passive network selection strategies that rely on real-time signal strength assessment are no longer sufficient to meet the demands for stable communication. Therefore, there is an urgent need for a communication base station selection method that combines the drone's spatial position awareness capabilities with prediction of its future trajectory and intelligent decision-making based on an airspace base station coverage model, thereby achieving a high-altitude communication solution with stable links and controllable handover.

[0004] In existing technologies, communication between drones and ground control systems primarily relies on cellular mobile communication networks such as 4G, 5G, or satellite links. The currently prevalent communication connection and handover mechanisms are mainly based on real-time detection of surrounding signal strength within the communication module, automatically selecting cells and switching base stations according to preset thresholds. While this approach can meet basic communication needs for traditional ground users or low-altitude, slow-moving aircraft, it suffers from the following significant drawbacks in high-altitude drones, such as those operating at altitudes greater than 300 meters and moving rapidly:

[0005] 1. Communication decisions rely on instantaneous signal strength values ​​and lack spatial global awareness capabilities.

[0006] The drone communication module selects base stations based solely on the currently measured signal strength, unable to identify its own position in the three-dimensional airspace or predict the communication quality trend of future flight segments, leading to blind decision-making.

[0007] 2. Frequent "ping-pong handover" phenomena indicate unstable communication links.

[0008] At high altitudes, the antenna signals of multiple base stations overlap and overlap, causing drastic changes in signal strength. Traditional modules constantly switch between multiple base stations with similar signal strength, resulting in communication interruptions, packet loss, video stuttering, and other problems.

[0009] 3. Ignoring the characteristics of drones—high flight speed and long trajectory—makes it impossible to plan communication links in advance.

[0010] Traditional solutions do not incorporate trajectory prediction mechanisms, cannot predict weak signal coverage areas or blind spots in advance, and cannot provide pre-switching or connection planning support for communication links.

[0011] 4. Lacking the ability to model spatial communication knowledge, the system cannot continuously learn and optimize.

[0012] Therefore, there is an urgent need to propose a location-aware UAV communication base station selection method to solve the problems of existing UAV communication base stations not maintaining communication maps, not being able to establish airspace communication quality models based on historical measurements or geographical features, and lacking continuous optimization and adaptive capabilities. Summary of the Invention

[0013] To overcome the problems existing in related technologies, this disclosure provides a method, system, device and medium for screening communication base stations for UAVs based on location awareness, in order to solve the technical problems in related technologies where UAVs do not maintain communication maps, cannot establish communication quality models in the airspace based on historical measurements or geographical features, and the system lacks continuous optimization and adaptive capabilities.

[0014] This specification provides one or more embodiments of a location-aware UAV communication base station screening method, including the following steps:

[0015] The UAV is located in real time using GNSS to obtain three-dimensional position information;

[0016] Based on the three-dimensional location information, candidate base stations within the visible range of the current location are retrieved from the airspace communication map database;

[0017] The candidate base stations are scored using a scoring function, and the candidate base station with the highest score is compared with the currently connected base station to select the target base station;

[0018] Control the drone to connect the base station to the target base station.

[0019] Preferably, before retrieving candidate base stations within the visible range of the current location in the airspace communication map database based on the three-dimensional location information, the method further includes the following steps:

[0020] Obtain historical flight paths, and determine whether the current flight path is a historical flight path based on the three-dimensional position information and the mission flight path;

[0021] If the current flight route is a historical route, retrieve the historical route information;

[0022] Control the drone's flight based on the historical flight path.

[0023] Preferably, the method further includes the following steps:

[0024] The system records the communication quality and base station switching actions during the drone's flight in real time and packages them for transmission to the real-time airspace communication map database.

[0025] Preferably, the step of scoring the candidate base stations using a scoring function and comparing the candidate base station with the currently connected base station to select the target base station specifically includes the following steps:

[0026] The candidate base stations are scored using a scoring function;

[0027] Determine whether the score difference between the candidate base station with the highest score and the currently connected base station exceeds a threshold;

[0028] Predict whether the minimum dwell time of the candidate base station with the highest score meets the minimum lower limit;

[0029] Candidate base stations whose score difference exceeds the threshold and whose minimum dwell time meets the minimum lower limit are selected as target base stations.

[0030] This specification provides one or more embodiments of a location-aware UAV communication base station screening system, including an airborne module and a ground-aided module. The airborne module includes a GNSS positioning unit, a base station scoring unit, and a communication control unit. The ground-aided module includes an airspace communication map data unit.

[0031] The GNSS positioning unit is used to locate the UAV in real time via GNSS and obtain three-dimensional position information;

[0032] The airspace communication map data unit is used to retrieve candidate base stations within the visible range of the current location in the airspace communication map database based on the three-dimensional location information.

[0033] The base station scoring unit is used to score the candidate base stations using a scoring function, and compare the candidate base station with the highest score with the currently connected base station to select the target base station.

[0034] The communication control unit is used to control the drone to connect the base station to the target base station.

[0035] Preferably, the ground assistance module further includes a map distribution module and a historical data learning module;

[0036] The map distribution module is used to obtain historical flight routes from the historical data learning module and determine whether the current flight route is a historical flight route based on the three-dimensional location information and the mission flight route.

[0037] The historical data learning module is used to retrieve historical route information and send it to the communication control unit if the current flight route is a historical route.

[0038] The communication control unit is used to control the drone's flight based on the historical flight path.

[0039] Preferably, the historical data learning module is also used to record the communication quality and base station switching actions during the drone's flight in real time, and package and send them to the real-time airspace communication map database.

[0040] Preferably, the base station scoring unit is specifically configured as follows:

[0041] The candidate base stations are scored using a scoring function;

[0042] Determine whether the score difference between the candidate base station with the highest score and the currently connected base station exceeds a threshold;

[0043] Predict whether the minimum dwell time of the candidate base station with the highest score meets the minimum lower limit;

[0044] Candidate base stations whose score difference exceeds the threshold and whose minimum dwell time meets the minimum lower limit are selected as target base stations.

[0045] This specification provides one or more embodiments of a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the location-aware UAV communication base station screening method described above.

[0046] This specification provides one or more embodiments of a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the location-aware UAV communication base station screening method described above.

[0047] This disclosure provides a method, system, device, and medium for selecting UAV communication base stations based on location awareness. Its advantages include: real-time GNSS positioning of the UAV to obtain three-dimensional position information, including the UAV's longitude, latitude, and altitude coordinates, ensuring the timeliness and accuracy of the position information and providing crucial altitude-dimensional information for subsequent "visible range" determination. This solves the communication environment uncertainty caused by the constantly changing position of the UAV during dynamic flight. Based on the three-dimensional position information, candidate base stations within the visible range of the current location are retrieved from the airspace communication map database, enabling rapid selection of candidate base stations and ensuring their physical communication capability, thus reducing computational load. A scoring function is used to score the candidate base stations, comparing the highest-scoring candidate base station with the currently connected base station to select the target base station. The scoring function quantifies base station performance, ensuring the selection of the base station with the strongest signal and lowest load, improving communication quality. Comparison with the current base station avoids signaling overhead and connection jitter caused by frequent switching, saving energy. The scoring mechanism adaptively adjusts to ensure the UAV always connects to the best available base station, improving system reliability. Controlling the UAV to connect to the target base station achieves dynamic optimization of the communication link, ensuring continuous high-quality communication for the UAV. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 A flowchart illustrating a location-aware UAV communication base station screening method provided for one or more embodiments of this specification;

[0050] Figure 2 A flowchart illustrating the location-aware UAV communication base station selection process provided in one or more embodiments of this specification;

[0051] Figure 3 A schematic diagram of a location-aware UAV communication base station screening system provided for one or more embodiments of this specification;

[0052] Figure 4 This is a schematic diagram of the structure of a computer device provided for one or more embodiments of this specification. Detailed Implementation

[0053] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this invention.

[0054] The present invention will now be described in detail with reference to specific embodiments and accompanying drawings.

[0055] Method Implementation Examples

[0056] According to embodiments of the present invention, a method for screening unmanned aerial vehicle (UAV) communication base stations based on location awareness is provided, such as... Figure 1 The diagram shown is a flowchart illustrating the location-aware UAV communication base station screening method provided in this embodiment. The location-aware UAV communication base station screening method according to this embodiment includes the following steps:

[0057] S110. Before takeoff, the flight control system loads the flight path and retrieves historical communication score layers from the airspace communication map database, automatically identifying two weak signal segments. During flight, the system uses GNSS (Global Navigation Satellite System) to locate the UAV in real time, updates its position, and acquires three-dimensional position information, including longitude, latitude, and altitude.

[0058] S120. Based on the three-dimensional location information, search the airspace communication map database for candidate base stations within the visible range of the current location. Traditional communication modules passively select base stations based solely on signal strength, lacking spatial awareness capabilities. This invention combines latitude and longitude with flight altitude to achieve accurate network selection based on actual airspace location, significantly reducing misselection.

[0059] S130. The candidate base stations are scored using a scoring function. The candidate base station with the highest score is compared with the currently connected base station to select the target base station. When selecting the base station, multiple factors such as geographical distance, channel parameters, historical signal quality, and heading direction are comprehensively considered. This breaks through the traditional static comparison method that relies on RSSI / RSRP and has predictive and anti-interference capabilities.

[0060] S140. Control the drone to connect the base station to the target base station.

[0061] The method provided in this embodiment uses GNSS to locate the UAV in real time and obtain three-dimensional position information. It can acquire the UAV's longitude, latitude, and altitude coordinates in real time, ensuring the timeliness and accuracy of the position information. This provides a crucial altitude dimension basis for subsequent "visible range" determination, solving the communication environment uncertainty problem caused by the constantly changing position of the UAV during dynamic flight. Based on the three-dimensional position information, it retrieves candidate base stations within the visible range of the current location from the airspace communication map database, quickly filtering out candidate base stations and ensuring they have physical communication capabilities, thus reducing computational load. The candidate base stations are scored using a scoring function, and the highest-scoring candidate base station is compared with the currently connected base station to select the target base station. The scoring function quantifies base station performance, ensuring the selection of the base station with the strongest signal and lowest load, improving communication quality. Comparison with the current base station avoids signaling overhead and connection jitter caused by frequent switching, saving energy. The scoring mechanism adaptively adjusts to ensure the UAV always connects to the best available base station, improving system reliability. Controlling the UAV to connect to the target base station achieves dynamic optimization of the communication link, ensuring continuous high-quality communication for the UAV.

[0062] In one embodiment, before step S120, which involves retrieving candidate base stations within the visible range of the current location from the spatial communication map database based on the three-dimensional location information, the following step is further included:

[0063] The historical flight path is obtained from the historical data learning module, and the current flight path is determined to be a historical flight path based on the three-dimensional position information and the mission flight path.

[0064] If the current flight route is a historical route, retrieve the historical route information and load the historical scoring layer to provide route warnings.

[0065] Control the drone's flight based on the historical flight path.

[0066] The method provided in this embodiment can quickly identify whether the current route is a historical route by associating three-dimensional location information with the mission route. With the help of the historical scoring layer, it can provide early warning of possible communication problems in the route, help the UAV to prepare for communication in advance, and control the flight based on the flight data of the historical route, which can reduce the decision-making error of the UAV on the familiar route and improve flight safety and efficiency.

[0067] In one embodiment, the following steps are also included:

[0068] The communication quality and base station switching actions during the UAV flight are recorded in real time after switching or while maintaining the connection, and packaged and sent to the real-time airspace communication map database to optimize the subsequent mission scoring model and map modeling, and update the new flight mission route to the historical data learning module.

[0069] In one embodiment, the step of scoring the candidate base stations using a scoring function and comparing the candidate base station with the currently connected base station to select the target base station specifically includes the following steps:

[0070] The candidate base stations are scored using a scoring function, wherein the scoring function employs a multi-factor decision algorithm:

[0071] F(x)=α·S+β·D+γ·T+δ·H;

[0072] in:

[0073] S represents the real-time signal strength score;

[0074] D represents the three-dimensional distance score to each candidate base station;

[0075] T represents the estimated coverage duration of the base station in the predicted trajectory;

[0076] H represents the historical communication performance score;

[0077] α, β, γ, and δ are weighting coefficients that are dynamically configured according to the task type.

[0078] Each factor is normalized according to the 0–1 interval, and the scoring result F(x) is also a standardized score, which facilitates horizontal comparison under different communication scenarios.

[0079] Table 1. Communication scoring weight configuration table for typical task scenarios.

[0080]

[0081]

[0082] The algorithm normalizes each factor to construct a standard scoring matrix and updates the candidate base station scoring list at fixed intervals using a sliding window approach. The system sets a scoring difference threshold ε and determines whether the scoring difference between the highest-scoring candidate base station and the currently connected base station exceeds the threshold ε.

[0083] Table 2 Communication Scoring Period and Handover Threshold Configuration Table

[0084] Types of drones Evaluation cycle Threshold ε High-speed fixed-wing aircraft (≥25m / s) 2–5 seconds 0.10–0.20 Medium-speed cruising (10–25 m / s) 5–10 seconds 0.05–0.10 Low-speed multirotor (≤10m / s) 10–15 seconds 0.03–0.05 Static patrol / hover ≥15 seconds or event triggered 0.03–0.05

[0085] Predict whether the minimum dwell time of the candidate base station with the highest score meets the minimum lower limit, that is, whether the trajectory coverage of the drone continuously flying within the range of the candidate base station meets the minimum duration.

[0086] Candidate base stations whose score difference exceeds the threshold ε and whose minimum dwell time meets the minimum limit will be selected as target base stations. A link handover process will be initiated to ensure that the handover action is both timely and robust, and to avoid frequent handovers caused by short-term signal fluctuations.

[0087] The method provided in this embodiment provides an objective and comprehensive basis for base station selection by quantitatively scoring multiple dimensions such as signal strength, bandwidth, and latency. By setting thresholds to filter out minor score differences, it reduces unnecessary base station switching caused by small performance fluctuations, lowers the risk of communication interruption during switching, and predicts in advance the duration of the drone's stay within the coverage area of ​​the target base station, avoiding frequent switching due to rapid departure after connection. This ensures that the target base station has significantly better communication performance than the current base station and can support a stable and continuous connection, ultimately achieving a substantial improvement in communication quality and a dual guarantee of link stability, thus optimizing the communication experience of drones in highly dynamic scenarios.

[0088] The technical solution will be further illustrated below through specific implementation examples:

[0089] like Figure 2 The diagram shows a flowchart of a location-aware UAV communication base station selection process. In each flight cycle, it first determines whether the route is repeated. If so, a historical scoring layer is loaded for route warning. Then, combining GNSS real-time positioning and the ground base station candidate list, a scoring function F(x) is used to score each candidate base station. Based on the score difference, it is determined whether to perform link switching. After switching or maintaining the connection, the current communication quality data is recorded and transmitted back to optimize the subsequent task scoring model.

[0090] System Implementation Examples

[0091] According to embodiments of the present invention, a location-aware UAV communication base station screening system is provided, such as... Figure 3 The diagram shown is a structural schematic of the UAV communication base station screening system based on location awareness provided in this embodiment. The UAV communication base station screening system based on location awareness according to this embodiment includes an airborne module 31 and a ground auxiliary module 32. The airborne module 31 includes a GNSS positioning unit 311, a base station scoring unit 312 and a communication control unit 313. The ground auxiliary module 32 includes an airspace communication map data unit 321.

[0092] The GNSS positioning unit 311 is used to locate the UAV in real time via GNSS and obtain three-dimensional position information.

[0093] The airspace communication map data unit 321 is used to retrieve candidate base stations within the visible range of the current location in the airspace communication map database based on the three-dimensional location information.

[0094] The base station scoring unit 312 is used to score the candidate base stations using a scoring function, and compare the candidate base station with the currently connected base station to select the target base station.

[0095] The communication control unit 313 is used to control the drone to connect the base station to the target base station.

[0096] The system provided in this embodiment uses a GNSS positioning unit 311 to locate the UAV in real time via GNSS, acquiring three-dimensional position information. This allows for real-time acquisition of the UAV's longitude, latitude, and altitude coordinates, ensuring the timeliness and accuracy of the position information. This provides crucial information on altitude dimension for subsequent "visible range" determination, resolving the uncertainty in the communication environment caused by the constantly changing position of the UAV during dynamic flight. The airspace communication map data unit 321 retrieves candidate base stations within the current visible range from the airspace communication map database based on the three-dimensional position information. This allows for rapid selection of candidate base stations, ensuring they have physical communication capabilities and reducing the risk of errors. The computational load is as follows: The base station scoring unit 312 scores the candidate base stations using a scoring function, compares the candidate base station with the currently connected base station to select the target base station, quantifies the base station performance through the scoring function, ensures that the base station with the strongest signal and lowest load is selected, improves communication quality, avoids signaling overhead and connection jitter caused by frequent switching by comparing with the current base station, saves energy, and the scoring mechanism is adaptively adjusted to ensure that the UAV always connects to the best available base station, improving system reliability; The communication control unit 313 controls the UAV to connect the base station to the target base station, realizes dynamic optimization of the communication link, and ensures that the UAV can continuously conduct high-quality communication.

[0097] In one embodiment, the ground assistance module 32 further includes a map distribution module and a historical data learning module.

[0098] The map distribution module is used to obtain historical flight routes from the historical data learning module and determine whether the current flight route is a historical flight route based on the three-dimensional location information and the mission flight route.

[0099] The historical data learning module is used to retrieve historical route information and send it to the communication control unit 313 if the current flight route is a historical route.

[0100] The communication control unit 313 is used to control the flight of the UAV according to the historical flight path.

[0101] The system provided in this embodiment can quickly identify whether the current route is a historical route by associating three-dimensional location information with the mission route. With the help of the historical scoring layer, it can provide early warning of possible communication problems in the route, helping the UAV to prepare for communication in advance. Controlling the flight based on the flight data of the historical route can reduce the decision-making error of the UAV on the familiar route and improve flight safety and efficiency.

[0102] In one embodiment, the historical data learning module is also used to record the communication quality and base station switching actions during the UAV flight in real time, and package and send them to the real-time airspace communication map database to optimize the subsequent task scoring model and map modeling, and update the new flight mission route to the historical data learning module.

[0103] In one embodiment, the base station scoring unit 312 is specifically configured as follows:

[0104] The candidate base stations are scored using a scoring function.

[0105] Determine whether the score difference between the candidate base station with the highest score and the currently connected base station exceeds a threshold.

[0106] Predict whether the minimum dwell time of the candidate base station with the highest score meets the minimum lower limit.

[0107] Candidate base stations whose score difference exceeds the threshold and whose minimum dwell time meets the minimum lower limit are selected as target base stations.

[0108] The system provided in this embodiment provides an objective and comprehensive basis for base station selection by quantitatively scoring multiple indicators such as signal strength, bandwidth, and latency. By setting thresholds to filter out minor score differences, it reduces unnecessary base station switching caused by small performance fluctuations, lowers the risk of communication interruption during switching, and predicts in advance the duration of the drone's stay within the coverage area of ​​the target base station, avoiding frequent switching due to rapid departure after connection. This ensures that the target base station has significantly better communication performance than the current base station and can support a stable and continuous connection, ultimately achieving a substantial improvement in communication quality and a dual guarantee of link stability, thus optimizing the communication experience of drones in highly dynamic scenarios.

[0109] The embodiments of the present invention are system embodiments corresponding to the above method embodiments. The specific operations of each module processing step can be understood by referring to the description of the method embodiments, and will not be repeated here.

[0110] like Figure 4As shown, the present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it implements the location-aware UAV communication base station screening method in the above embodiments, or when the computer program is executed by a processor, it implements the location-aware UAV communication base station screening method in the above embodiments.

[0111] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0112] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for apparatus or system embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The apparatus and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and the contents not described in detail in the specification of the present invention are known to those skilled in the art.

Claims

1. A method for screening unmanned aerial vehicle (UAV) communication base stations based on location awareness, characterized in that, The following steps are involved: The UAV is located in real time using GNSS to obtain three-dimensional position information; Based on the three-dimensional location information, candidate base stations within the visible range of the current location are retrieved from the airspace communication map database; The candidate base stations are scored using a scoring function, and the candidate base station with the highest score is compared with the currently connected base station to select the target base station; Control the drone to connect the base station to the target base station.

2. The method for screening UAV communication base stations based on location awareness as described in claim 1, characterized in that, Before retrieving candidate base stations within the visible range of the current location from the airspace communication map database based on the three-dimensional location information, the following steps are also included: Obtain historical flight paths, and determine whether the current flight path is a historical flight path based on the three-dimensional position information and the mission flight path; If the current flight route is a historical route, retrieve the historical route information; Control the drone's flight based on the historical flight path.

3. The location-aware UAV communication base station screening method as described in claim 2, characterized in that, It also includes the following steps: The system records the communication quality and base station switching actions during the drone's flight in real time and packages them for transmission to the real-time airspace communication map database.

4. The method for screening UAV communication base stations based on location awareness as described in claim 1, characterized in that, The process of scoring the candidate base stations using a scoring function and comparing the candidate base station with the currently connected base station to select the target base station includes the following steps: The candidate base stations are scored using a scoring function; Determine whether the score difference between the candidate base station with the highest score and the currently connected base station exceeds a threshold; Predict whether the minimum dwell time of the candidate base station with the highest score meets the minimum lower limit; Candidate base stations whose score difference exceeds the threshold and whose minimum dwell time meets the minimum lower limit are selected as target base stations.

5. A location-aware UAV communication base station screening system, characterized in that, It includes an airborne module and a ground-aided module. The airborne module includes a GNSS positioning unit, a base station scoring unit, and a communication control unit. The ground-aided module includes an airspace communication map data unit. The GNSS positioning unit is used to locate the UAV in real time via GNSS and obtain three-dimensional position information; The airspace communication map data unit is used to retrieve candidate base stations within the visible range of the current location in the airspace communication map database based on the three-dimensional location information. The base station scoring unit is used to score the candidate base stations using a scoring function, and compare the candidate base station with the highest score with the currently connected base station to select the target base station. The communication control unit is used to control the drone to connect the base station to the target base station.

6. The location-aware UAV communication base station screening system as described in claim 5, characterized in that, The ground support module also includes a map distribution module and a historical data learning module; The map distribution module is used to obtain historical flight routes from the historical data learning module and determine whether the current flight route is a historical flight route based on the three-dimensional location information and the mission flight route. The historical data learning module is used to retrieve historical route information and send it to the communication control unit if the current flight route is a historical route. The communication control unit is used to control the drone's flight based on the historical flight path.

7. The location-aware UAV communication base station screening system as described in claim 6, characterized in that, The historical data learning module is also used to record the communication quality and base station switching actions during the drone's flight in real time, and package and send them to the real-time airspace communication map database.

8. The location-aware UAV communication base station screening system as described in claim 5, characterized in that, The base station scoring unit is specifically configured as follows: The candidate base stations are scored using a scoring function; Determine whether the score difference between the candidate base station with the highest score and the currently connected base station exceeds a threshold; Predict whether the minimum dwell time of the candidate base station with the highest score meets the minimum lower limit; Candidate base stations whose score difference exceeds the threshold and whose minimum dwell time meets the minimum lower limit are selected as target base stations.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the location-aware UAV communication base station screening method as described in any one of claims 1 to 4.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the location-aware UAV communication base station screening method as described in any one of claims 1 to 4.

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