A method and system for secure access and dynamic supervision of low altitude traffic control

Abstract

The application discloses a kind of safety access and dynamic supervision method and system for low altitude traffic control, it is related to low altitude flight dynamic authorization technical field, it is difficult to solve the technical problem that dynamic flight authorization is carried out to unmanned aerial vehicle according to the flight intention of unmanned aerial vehicle in low altitude control;The first access factor of unmanned aerial vehicle is determined according to historical flight data in the application, and the area and route of unmanned aerial vehicle in this flight are set in combination with model;Real-time position and height are used to determine the safety flight factor of unmanned aerial vehicle at each time in this flight, and the habit factor of unmanned aerial vehicle in the flight time of current application is determined based on flight time;The second access factor is obtained by updating the first access factor based on safety flight factor and habit factor, and the flight permission of current unmanned aerial vehicle at current time is set based on the second access factor;The application can reduce the occurrence probability of mismatch between static authorization and dynamic supervision in traditional low altitude control.

Description

Technical Field

[0001] This invention belongs to the field of low-altitude traffic control and relates to low-altitude flight dynamic authorization technology, specifically a method and system for safe access and dynamic monitoring of low-altitude traffic control. Background Technology

[0002] Safe access and dynamic monitoring of low-altitude air traffic control are crucial components of aviation safety. With the increasing prevalence of low-altitude aircraft such as drones, low-altitude air traffic control faces new challenges. Existing methods for safe access and dynamic monitoring have several shortcomings, such as inadequate access control mechanisms and limited monitoring tools, failing to meet practical needs.

[0003] Currently, most methods and systems for secure access and dynamic monitoring of low-altitude traffic control struggle to dynamically authorize drones based on their flight intentions. When drones exhibit a tendency to violate regulations, management can only choose to "ignore" or prohibit flight, making it difficult to dynamically restrict flight areas in the early stages of drone violations. This increases the probability of a mismatch between static authorization and dynamic monitoring in traditional low-altitude control.

[0004] Therefore, this invention discloses a method and system for safe access and dynamic monitoring of low-altitude traffic control, which solves the above-mentioned technical problems. Summary of the Invention

[0005] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes a method and system for safe access and dynamic monitoring in low-altitude traffic control, which addresses the technical problem of difficulty in dynamically authorizing drones to fly based on their flight intentions during low-altitude traffic control. This invention determines a first access factor by analyzing historical drone flight data and sets the area and route for the current flight based on the drone model; it acquires the drone's position and altitude in real time and calculates a safe flight factor; it determines the drone's habitual factor within the currently requested flight time based on the flight time; it dynamically updates the first access factor to a second access factor by combining the safe factor and the habitual factor, and grants the drone flight permission for the current time based on the second access factor, thus solving the aforementioned problem.

[0006] To achieve the above objectives, a first aspect of the present invention provides a method for safe access and dynamic monitoring of low-altitude traffic control, comprising: Obtain the drone's identification code, model, and historical flight data; the historical flight data includes the number of historical violations and the total historical flight time. The first access factor of the UAV is determined based on historical flight data, and the flight area and flight route of the UAV in this flight are set based on the model and the first access factor. The system acquires the position and altitude of the UAV within the flight area and flight route, determines the safe flight factor of the UAV at each time point during the current flight based on the position and altitude, and determines the habit factor of the UAV within the currently requested flight time based on the flight time. The system updates the first access factor based on the safe flight factor and the habit factor to obtain the second access factor, and sets the flight permissions of the current UAV at the current time based on the second access factor.

[0007] Preferably, obtaining the UAV's identification code, model, and historical flight data includes: The identification code of the drone used in this flight is obtained through the user account, and the drone model and total historical flight time are extracted from the database based on the identification code. Based on the identification code, the database is used to extract the number of violations by the drone during flight before a preset time, such as sudden hovering, deviation from the predetermined flight path, and illegal entry into the no-fly zone, and the number of violations during flight within a preset time, such as sudden hovering, deviation from the predetermined flight path, and illegal entry into the no-fly zone. The violation number one is multiplied by a fixed ratio to obtain a reference number one, and the reference number one is added to the violation number two to obtain the historical number of violations. The fixed ratio and the preset time are obtained by manual setting.

[0008] Preferably, determining the first access factor of the UAV based on historical flight data includes: Extract the historical violation count (GC). When the historical violation count (GC) is greater than the default threshold, set the first access factor to the minimum value of the standard access range. The default threshold and the standard access range are manually set. When the number of historical violations GC is not greater than the violation threshold, the total historical flight time ZC is extracted, and the first access factor WZ1 is determined based on the number of historical violations GC and the total historical flight time ZC. The first access factor WZ1 satisfies formula (1): (1); Where ZBW is the median value of the standard access range, BZC is the manually set standard total flight time, and BGC is the average number of historical violations recorded in the database for each drone. and The proportional adjustment coefficient is set manually, and ; When the first access factor WZ1 is less than the minimum value of the standard access range, the first access factor WZ1 is updated using the minimum value of the standard access range; when the first access factor WZ1 is greater than the maximum value of the standard access range, the first access factor WZ1 is updated using the maximum value of the standard access range.

[0009] It should be noted that the standard access range is a standard range used to define the first access factor, in order to prevent the first access factor from being too large or too small from affecting subsequent analyses.

[0010] Preferably, the step of setting the flight area and flight route of the UAV for this flight based on the model and the first access factor includes: Extract the drone model and the user's requested flight area and flight route. If there are restrictions on the drone model within the expected flight area, the user is notified to replan the flight area. If there are restrictions on the drone model within the expected flight route, the user is notified to replan the flight route. When there are no restrictions preventing the flight of the corresponding UAV model within the expected flight area and along the expected flight route, determine whether the first access factor WZ1 is less than the access factor threshold; if yes, determine the safety distance based on formula (2). No, determine the safety distance based on formula (3). The access factor threshold is a manually selected percentile value within the standard access range. Formula (2): (2); Formula (3): (3); in, This represents the fixed safe distance for no-fly zones, where i is the no-fly zone number; BWZ1 is the percentile value of the manually set standard access range. The proportional adjustment coefficient is set manually, and The range of values ​​for is (0,2]; The safe distance from the center point of each no-fly zone The area within is set as the restricted area of ​​the current drone. The area within the expected flight area after removing each restricted area is marked as the flight area. The route within the expected flight path after removing each restricted area is marked as the flight path.

[0011] It should be noted that the first access factor WZ1, after being limited by the standard access range, takes a value greater than 0.

[0012] Preferably, obtaining the position and altitude of the UAV within the flight area and the flight path includes: When a drone enters a flight area or flight route, the time requested by the user for flight is divided into several time periods based on a fixed duration; the fixed duration and fixed frequency GL are both manually set. When the time is in the first time period, the position and altitude of the UAV in the flight area and flight path are obtained based on a fixed frequency GL. When the time is not at the start time of the first time period, extract the position and altitude of each time period before the current time period; determine whether there is a situation where the position or altitude exceeds the flight area and flight route; if yes, obtain the total number of times the position or altitude exceeds the flight area and flight route ZS1, determine the dynamic frequency DL of the UAV in the current time period based on the total number of times ZS1, and obtain the position and altitude of the UAV when flying within the flight area or flight route via GPS based on the dynamic frequency DL; if no, obtain the position and altitude of the UAV when flying within the flight area or flight route via GPS based on the fixed frequency GL. The dynamic frequency DL satisfies formula (4): (4); Among them, BCS is the number of times the manually set standard is exceeded.

[0013] It should be noted that the Standard Exceedance Count (BCS) is the mode of the total number of times each drone exceeded its flight area and flight path in historical data.

[0014] Preferably, the determination of the safe flight factors of the UAV at various times during this flight based on position and altitude includes: Extract the position and altitude of the UAV in the flight area and flight path, and obtain the total number of times ZS2 of the UAV entering the restricted area at the given position and altitude in real time; When the total number of flights ZS2 exceeds the number of flights threshold CZ, the safe flight factor of the drone's current flight is marked as 0; the number of flights threshold is set manually. When the total number of attempts ZS2 does not exceed the number of attempts threshold CZ, the safe flight factor AZ of the UAV at the current time is determined based on the total number of attempts ZS2; the safe flight factor AZ satisfies formula (5): (5); in, The amplitude adjustment factor is set manually, and The value range is (0,2).

[0015] Preferably, the habitual factor for determining the UAV's flight time within the currently applied flight time based on flight time includes: Extract the number of flights at each time point within a certain number of historical days, and mark the time points where the number of flights exceeds the flight count threshold as target time points; the flight count threshold and the preset ratio YB are both obtained manually. Extract the time when the user applies for flight, obtain the proportion ZB of the target time point in the applied flight time, and when the proportion ZB exceeds the preset proportion YB, set the habit factor GZ of the drone in the current applied flight time to 1. When the percentage ZB does not exceed the preset percentage YB, the habit factor GZ is obtained based on the formula GZ=ZB / YB.

[0016] Preferably, the step of updating the first access factor based on the safe flight factor and the habit factor to obtain the second access factor includes: Extract the safe flight factor AZ, the habit factor GZ, and the first access factor WZ1, and determine the second access factor WZ2 based on the safe flight factor AZ, the habit factor GZ, and the first access factor WZ1; the second access factor WZ2 satisfies formula (6): (6); in, and All are proportional adjustment coefficients greater than 0, and , .

[0017] Preferably, setting the flight permissions of the current drone at the current time based on the second access factor includes: Extract the second access factor WZ2. When the second access factor WZ2 is greater than the first permission threshold, no restriction is imposed on the flight permission of the current drone at the current time. Both the first and second permission thresholds are manually set, and the first permission threshold is greater than the second permission threshold. When the second access factor WZ2 is less than permission threshold one and greater than permission threshold two, the safe distance of each no-fly zone is extracted. Based on the formula Obtain the second safe distance for this flight The second safe distance from the center point of each no-fly zone. The area within is set as the restricted area of ​​the current drone. The area within the expected flight area after removing each restricted area is marked as the flight area. The route within the expected flight path after removing each restricted area is marked as the flight path. When the second access factor WZ2 is less than the permission threshold of two, the drone is prohibited from flying in the current flight area and flight route.

[0018] A second aspect of the present invention provides a secure access and dynamic monitoring system for low-altitude traffic control, comprising: a security analysis module, and a data collection module and a dynamic authorization module connected to the security analysis module; The data collection module is used to acquire the drone's identification code, model, and historical flight data; the historical flight data includes the number of historical violations and the total historical flight time. The safety analysis module is used to determine the first access factor of the UAV based on historical flight data, and to set the flight area and flight route of the UAV for this flight based on the model and the first access factor. The dynamic authorization module is used to obtain the position and altitude of the UAV within the flight area and flight route, determine the safe flight factor of the UAV at each time during the current flight based on the position and altitude, determine the habit factor of the UAV within the currently applied flight time based on the flight time, update the first access factor based on the safe flight factor and the habit factor to obtain the second access factor, and set the flight permission of the current UAV at the current time based on the second access factor.

[0019] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention solves the technical problem of dynamically authorizing drones based on their flight intentions during low-altitude air traffic control by acquiring the drone's identification code, model, and historical flight data; determining a first access factor based on the historical flight data; setting the drone's flight area and route for the current flight based on the model and the first access factor; acquiring the drone's position and altitude within the flight area and route; determining a safe flight factor for the drone at various times during the current flight based on the position and altitude; determining a habitual factor for the drone within the currently requested flight time based on the flight time; updating the first access factor based on the safe flight factor and the habitual factor to obtain a second access factor; and setting the current drone's flight permissions for the current time based on the second access factor. This invention reduces the probability of mismatch between static authorization and dynamic monitoring in traditional low-altitude air traffic control.

[0020] 2. This invention combines key indicators such as the number of historical violations and total historical flight time with manually set parameters to construct an evaluation system that reflects the creditworthiness of drone flights. The first access factor is set based on the number of historical violations. When the number of historical violations exceeds the default threshold, access is directly restricted to the minimum of the standard range, effectively curbing the potential threat of high-risk drones. Simultaneously, for drones with higher compliance rates, the system dynamically calculates the first access factor using a formula, avoiding rigid "one-size-fits-all" management and adjusting the access range according to the relative proportion of flight time and the number of violations, achieving differentiated control. This flexibility ensures that safety management covers high-risk scenarios without excessively restricting compliant users, thus balancing safety and efficiency. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or 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 of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the operation steps of the present invention; Figure 2 This is a schematic diagram illustrating the operational steps for obtaining the habit factor according to the present invention; Figure 3 This is a schematic diagram of the system modules of the present invention. Detailed Implementation

[0023] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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.

[0024] Please see Figure 1 The first aspect of this invention provides a method for secure access and dynamic monitoring of low-altitude traffic control. A second aspect of this invention provides a method for secure access and dynamic monitoring of low-altitude traffic control, comprising: Obtain the drone's identification code, model, and historical flight data; the historical flight data includes the number of historical violations and the total historical flight time. The first access factor of the UAV is determined based on historical flight data, and the flight area and flight route of the UAV in this flight are set based on the model and the first access factor. The system acquires the position and altitude of the UAV within the flight area and flight route, determines the safe flight factor of the UAV at each time point during the current flight based on the position and altitude, and determines the habit factor of the UAV within the currently requested flight time based on the flight time. The system updates the first access factor based on the safe flight factor and the habit factor to obtain the second access factor, and sets the flight permissions of the current UAV at the current time based on the second access factor.

[0025] This application obtains the drone's identification code, model, and historical flight data, including: The identification code of the drone used in this flight is obtained through the user account, and the drone model and total historical flight time are extracted from the database based on the identification code. Based on the identification code, the database is used to extract the number of violations by the drone during flight before a preset time, such as sudden hovering, deviation from the predetermined route, and illegal entry into the no-fly zone, as well as the number of violations during flight within a preset time. The number of violations is then multiplied by a fixed ratio to obtain the reference number, and the reference number is then added to the number of violations to obtain the historical number of violations. The fixed ratio and the preset time are manually set.

[0026] It should be noted that the fixed ratio can be set to [0,1], which is used to reduce the impact of violations that are older than the current time on the current data analysis. For example, if the importance of violations is consistent across different historical time periods, the fixed ratio is set to 1; if violations that are older than the current time are not considered, the fixed ratio is set to 0.

[0027] It should be noted that the preset time can be the most recent year or the most recent six months.

[0028] The first access factor for the UAV determined in this application based on historical flight data includes: Extract historical violation counts (GC). When the historical violation counts (GC) exceed the default threshold, set the first access factor to the minimum value of the standard access range. The default threshold and the standard access range are manually set. When the number of historical violations GC is not greater than the violation threshold, extract the total historical flight time ZC, and determine the first access factor WZ1 based on the number of historical violations GC and the total historical flight time ZC. The first access factor WZ1 satisfies formula (1): (1); Where ZBW is the median value of the standard access range, BZC is the manually set standard total flight time, and BGC is the average number of historical violations recorded in the database for each drone. and The proportional adjustment coefficient is set manually, and ; When the first access factor WZ1 is less than the minimum value of the standard access range, the first access factor WZ1 is updated using the minimum value of the standard access range; when the first access factor WZ1 is greater than the maximum value of the standard access range, the first access factor WZ1 is updated using the maximum value of the standard access range.

[0029] It is worth noting that this invention combines key indicators such as the number of historical violations and the total historical flight time with manually set parameters to construct an evaluation system that reflects the creditworthiness of drone flights. Among them, the setting of the first access factor is based on the number of historical violations. When the number of historical violations exceeds the default threshold, the access permission is directly restricted to the minimum value of the standard range, which can effectively curb the potential threat of high-risk drones. For example, if a drone repeatedly violates airspace restrictions or operating procedures, the system will immediately reduce its access permission to prevent it from participating in high-risk tasks. At the same time, for drones with high compliance, the system dynamically calculates the first access factor WZ1 through formula (1), which avoids rigid "one-size-fits-all" management and can adjust the access range according to the relative proportion of flight time and number of violations to achieve differentiated control. This flexibility ensures that safety management can cover high-risk scenarios without excessively restricting compliant users, thereby balancing safety and efficiency.

[0030] It should be noted that the proportionality coefficient and Adjustability, such as The value is 0.5. The value is 0.5; The value is 0.6. The value is set to 0.4, allowing managers to adjust the weight according to actual needs. For example, in scenarios prioritizing flight safety, the weight of flight duration can be adjusted, or the weight of the number of violations can be increased in the control of violations. This adjustability provides a technical foundation for long-term risk prevention and control, while also providing data support for system iteration and optimization.

[0031] It should be noted that the default threshold can be set to 20; the standard total flight time (BZC) can be set to 200 days.

[0032] This application sets the flight area and flight route of the UAV for this flight based on the model and the first access factor, including: Extract the drone model and the user's requested flight area and flight route. If there are restrictions on the drone model within the expected flight area, the user is notified to replan the flight area; if there are restrictions on the drone model within the expected flight route, the user is notified to replan the flight route. When there are no restrictions preventing the flight of the corresponding UAV model within the expected flight area and along the expected flight route, determine whether the first access factor WZ1 is less than the access factor threshold; if yes, determine the safe distance based on formula (2). No, determine the safety distance based on formula (3). The access factor threshold is a manually selected percentile value within the standard access range. Formula (2): (2); Formula (3): (3); in, This represents the fixed safe distance for no-fly zones, where i is the no-fly zone number; BWZ1 is the percentile value of the manually set standard access range. The proportional adjustment coefficient is set manually, and The range of values ​​for is (0,2]; The safe distance from the center point of each no-fly zone The area within is set as the restricted area of ​​the current drone. The area within the expected flight area after removing each restricted area is marked as the flight area. The route within the expected flight path after removing each restricted area is marked as the flight path.

[0033] It is worth noting that the present invention achieves dynamic adaptability of flight planning through intelligent judgment of access factor threshold; in high access factor scenarios, the system will automatically use formula (3) to generate a more relaxed restriction area, while in low access factor scenarios, it will use formula (2) to simplify the calculation of safe distance to generate a more strict restriction area. The present invention can restrict the flight area of ​​low credit drones while reducing interference with the flight plan of high credit drones.

[0034] It should be noted that the fixed safety distance is set manually based on the type of no-fly zone within the expected flight area and near the expected flight path; the expected flight area and near the expected flight path can be 5000 meters; no-fly zones include airports, military bases, and critical infrastructure. For example, the fixed safe distance set for airports is 5,000 meters, for military bases it is 2,000 meters, and for critical infrastructure it is 500 meters.

[0035] It should be noted that the percentile value BWZ1 of the standard access range is the value at a specific percentile within the standard access range. If the data in the standard access range is sorted in ascending order, and the manually set percentile is 60%, then the data at the 60th position is the percentile value BWZ1 of the standard access range. If there is no data at the 60th position of the standard access range, then the data closest to the 60th position is used as the percentile value of the standard access range.

[0036] It should be noted that the proportional adjustment coefficient It is a coefficient used to adjust the fixed safe distance of the no-fly zone, and it is obtained by analyzing the distance between each drone and the no-fly zone in historical data.

[0037] It should be noted that the safe distance in a no-fly zone is a value used to limit the distance between the drone and the no-fly zone. When there are multiple no-fly zones within the expected flight area, the set flight area must satisfy the restriction areas of multiple no-fly zones; for example: there are two restricted areas corresponding to two no-fly zones within the expected flight area QA1: restricted area B1 and restricted area B2; If there is no overlap between restricted area B1 and restricted area B2, then the area of ​​the expected flight area A1 after removing restricted area B1 and restricted area B2 will be marked as the flight area. If there is an overlapping area between restricted area B1 and restricted area B2, the area of ​​the expected flight area QA1, excluding the area of ​​the integrated area of ​​restricted area B1 and restricted area B2, will be marked as the flight area. If there are multiple no-fly zones within the expected flight route, the restricted areas of the flight route must satisfy all of the multiple no-fly zones; for example: if there are two restricted areas corresponding to the two no-fly zones within the expected flight route LA1: restricted area B3 and restricted area B4; If there is no overlap between restricted areas B3 and B4, the replanned route after removing restricted areas B3 and B4 from the expected flight route LA1 will be marked as the flight route. If there is an overlapping area between restricted area B3 and restricted area B4, the replanned route LA1 after removing the areas of restricted area B3 and restricted area B4 will be marked as the flight route; the replanning can be carried out by the user or the administrator.

[0038] This application obtains the position and altitude of the UAV within the flight area and the flight path, including: When a drone enters a flight area or flight route, the time requested by the user for flight is divided into several time periods based on a fixed duration; the fixed duration and fixed frequency GL are both manually set. When the time is in the first time period, the position and altitude of the UAV in the flight area and flight path are obtained based on a fixed frequency GL. When the time is not at the start time of the first time period, extract the position and altitude of each time period before the current time period; determine whether there are situations where the position or altitude exceeds the flight area and flight path; if yes, obtain the total number of times the position or altitude exceeds the flight area and flight path ZS1, determine the dynamic frequency DL of the UAV in the current time period based on the total number ZS1, and obtain the position and altitude of the UAV when flying within the flight area or flight path via GPS based on the dynamic frequency DL; if no, obtain the position and altitude of the UAV when flying within the flight area or flight path via GPS based on the fixed frequency GL. The dynamic frequency DL satisfies formula (4): (4); Among them, BCS is the number of times the manually set standard is exceeded.

[0039] It is worth noting that this invention achieves a balance between resource efficiency, security, and adaptability through techniques such as dynamic frequency adjustment, time segmentation management, and historical data comparison. Its core value lies in the organic combination of "fixed rules" and "dynamic response," which avoids the limited resource data resulting from traditional fixed-frequency monitoring and overcomes the uncertainties of purely dynamic monitoring, providing a reliable guarantee for the safe and efficient operation of UAVs in complex environments.

[0040] It is worth noting that the present invention, through the design of formula (4), enables the system to flexibly adjust the data acquisition frequency in different scenarios; when the UAV does not exceed the flight area, maintaining a fixed frequency GL can ensure the continuity of basic data; and when the number of times the out-of-flight ZS1 is detected to increase, the dynamic frequency DL will increase accordingly, thereby improving the ability to acquire data.

[0041] It should be noted that the fixed duration can be 5 minutes, 10 minutes or 20 minutes; the fixed frequency GL can be 30 times / minute, 60 times / minute or 100 times / minute.

[0042] This application determines the safe flight factors of the UAV at various times during this flight based on its position and altitude, including: Extract the position and altitude of the drone in the flight area and flight path, and obtain the total number of times the drone entered the restricted area in real time, ZS2. When the total number of flights ZS2 exceeds the number of flights threshold CZ, the safe flight factor of the drone's current flight is marked as 0; the number of flights threshold is set manually. When the total number of attempts ZS2 does not exceed the number of attempts threshold CZ, the safe flight factor AZ of the UAV at the current time is determined based on the total number of attempts ZS2; the safe flight factor AZ satisfies formula (5): (5); in, The amplitude adjustment factor is set manually, and The value range is (0,2).

[0043] It should be noted that the safe flight factor AZ is not a fixed value, but changes in real time based on the number of times the drone enters the restricted area. When the total number of times ZS2 does not exceed the threshold CZ, the safe flight factor AZ is smoothly reduced using formula (5), rather than abruptly decreasing to zero. This design avoids the "one-size-fits-all" problem that may be caused by traditional fixed thresholds. For example, if the drone deviates slightly from the flight path but does not trigger an emergency stop, the system can still allow it to continue flying, but by reducing the safe flight factor AZ value, the operator is alerted to the potential risk.

[0044] It should be noted that the introduction of the natural logarithm function ln in formula (5) can effectively suppress the impact of ZS2 fluctuations on AZ. For example, when the total number of times ZS2 approaches the number of times threshold CZ, the growth rate of ln(ZS2 / CZ+1) will gradually slow down, making the downward trend of the safe flight factor AZ more gradual, thus avoiding flight mission interruption due to minor violations. This characteristic is particularly suitable for UAV operations in complex terrain or dynamic environments.

[0045] It should be noted that, This is an amplitude adjustment coefficient set manually using the ln() function. This refers to the degree of influence of the total number of times ZS2, used to adjust position and altitude, enters the restricted area on the safe flight factor AZ; when other conditions remain unchanged, The higher the AZ level, the greater the impact on the safe flight factor. The smaller the value, the less impact the safe flight factor (AZ) has.

[0046] It should be noted that the number of times threshold is set manually based on a fixed frequency GL, and the number of times threshold is proportional to the fixed frequency GL, and can be 10, 25 or 50.

[0047] Please see Figure 2 The habitual factor for determining the UAV's flight time within the current application, based on flight time, includes: Extract the number of flights at each time point within a certain number of historical days, and mark the time points where the number of flights exceeds the flight count threshold as target time points; the flight count threshold and the preset ratio YB are both obtained manually. Extract the time when the user applies for flight, obtain the proportion of the target time point in the applied flight time ZB, and when the proportion ZB exceeds the preset proportion YB, set the habit factor GZ of the drone in the current applied flight time to 1. When the proportion ZB does not exceed the preset proportion YB, the habit factor GZ is obtained based on the formula GZ=ZB / YB.

[0048] It is worth noting that the present invention, through the algorithm design of determining the habit factors of the drone within the current requested flight time based on flight time, can extract key behavioral patterns from historical flight data and quantify user behavior into analyzable indicators for analyzing the rationality of users flying in different time periods.

[0049] It should be noted that this invention marks high-frequency flight periods as "target time points" by statistically analyzing historical flight counts and combining them with manually set thresholds and proportions. Essentially, this process identifies a user's flight preferences within a specific time period through statistical patterns in historical data. For example, if a user's flight count between 10 AM and 12 PM far exceeds the threshold, the system will consider that period as their "habitual time point." This identification method avoids subjective assumptions and ensures the objectivity of the decision-making process.

[0050] It should be noted that the calculation logic of the habit factor GZ itself has an anomaly detection function. For example, if a user suddenly requests to fly during non-habitual times, such as late at night, and the proportion ZB is much lower than the preset proportion YB, the system can determine this as abnormal behavior and trigger a safety warning; this mechanism helps to: Preventing violations: Identifying potential user intent to violate regulations, such as avoiding monitored periods; Strengthen safety management: Add review steps to flight applications with low habitability factor (GZ) values ​​to reduce the risk of airspace conflicts.

[0051] It should be noted that the number of flights at various points in time within a historical period can be illustrated with examples: Between February 26, 2025 and May 26, 2025, the drone had flight records at 9:00:00 on February 26, 2025, March 1, 2025, March 20, 2025, April 6, 2025, May 6, 2025, and May 16, 2025. Therefore, the number of flights at the time 9:00:00 is 6.

[0052] In this application, the second access factor is obtained by updating the first access factor based on the safe flight factor and the habit factor, including: Extract the safe flight factor AZ, the habit factor GZ, and the first access factor WZ1. Based on the safe flight factor AZ, the habit factor GZ, and the first access factor WZ1, determine the second access factor WZ2; the second access factor WZ2 satisfies formula (6): (6); in, and All are proportional adjustment coefficients greater than 0, and , .

[0053] It should be noted that the second access factor WZ2 only participates in the flight permission settings for the current flight.

[0054] It should be noted that, and This is a manually set proportional adjustment coefficient. Because: The factor multiplied is the safe flight factor AZ, which indicates that the drone followed the rules during this flight. The factor multiplied is the habitual factor GZ, which represents the reasonableness of the user's flight at the current time. Since the second access factor WZ2 is used to further restrict the drone in this flight, the safety flight factor AZ, which represents the drone's compliance with the rules in this flight, is more important than the habitual factor GZ, which represents the reasonableness of the user's flight at the current time. Therefore, the proportional adjustment coefficient set for the safety flight factor AZ in this invention is greater than that for the habitual factor GZ.

[0055] This application sets the flight permissions of the current drone at the current time based on the second access factor, including: Extract the second access factor WZ2. When the second access factor WZ2 is greater than the first permission threshold, no restriction is imposed on the flight permission of the current drone at the current time. Both the first and second permission thresholds are manually set, and the first permission threshold is greater than the second permission threshold. When the second access factor WZ2 is less than permission threshold one and greater than permission threshold two, the safe distance of each no-fly zone is extracted. Based on the formula Obtain the second safe distance for this flight The second safe distance from the center point of each no-fly zone. The area within is set as the restricted area of ​​the current drone. The area within the expected flight area after removing each restricted area is marked as the flight area. The route within the expected flight path after removing each restricted area is marked as the flight path. When the second access factor WZ2 is less than the permission threshold of two, the drone is prohibited from flying in the current flight area and flight route.

[0056] Please see Figure 3 A second aspect of the present invention provides a secure access and dynamic monitoring system for low-altitude traffic control, comprising: a security analysis module, and a data collection module and a dynamic authorization module connected to the security analysis module; Data collection module: used to acquire the drone's identification code, model, and historical flight data; among which, historical flight data includes the number of historical violations and the total historical flight time; Safety Analysis Module: Used to determine the first access factor of the UAV based on historical flight data, and set the flight area and flight route of the UAV for this flight based on the model and the first access factor; Dynamic authorization module: used to obtain the position and altitude of the UAV within the flight area and flight route, determine the safe flight factor of the UAV at each time during the current flight based on the position and altitude, determine the habit factor of the UAV within the currently applied flight time based on the flight time, update the first access factor based on the safe flight factor and the habit factor to obtain the second access factor, and set the flight permission of the current UAV at the current time based on the second access factor.

[0057] Some of the data in the above formula are calculated by removing dimensions and taking their numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

[0058] Working principle of the invention: This invention first acquires the drone's identification code, model, and historical flight data, providing data support for subsequent analysis. Based on the historical flight data, a first access factor for the drone is determined. This step, by calculating the first access factor WZ1, avoids rigid, one-size-fits-all management and allows for differentiated control by adjusting the access range according to the relative proportion of flight duration and violation frequency. Based on the model and the first access factor, the drone's flight area and route for this flight are set. This step restricts the flight area of ​​low-credit drones while reducing interference with the flight plans of high-credit drones. The drone's position and altitude within the flight area and route are acquired. Based on the position and altitude, a safe flight factor for the drone at each time point during this flight is determined. A habit factor for the drone within the currently requested flight time is determined based on the flight time. This step extracts key behavioral patterns from historical flight data and quantifies user behavior into analyzable indicators for analyzing the rationality of user flights at different time points. Based on the safe flight factor and habit factor, the first access factor is updated to obtain a second access factor. Based on the second access factor, the flight permissions for the current drone at the current time are set.

[0059] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for safe access and dynamic monitoring of low-altitude traffic control, characterized in that, include: Obtain the drone's identification code, model, and historical flight data; the historical flight data includes the number of historical violations and the total historical flight time. The first access factor of the UAV is determined based on historical flight data, and the flight area and flight route of the UAV in this flight are set based on the model and the first access factor. The system acquires the position and altitude of the UAV within the flight area and flight route, determines the safe flight factor of the UAV at each time during the flight based on the position and altitude, and determines the habit factor of the UAV within the currently requested flight time based on the flight time. The system updates the first access factor based on the safe flight factor and the habit factor to obtain the second access factor, and sets the flight permissions of the current UAV at the current time based on the second access factor. The determination of the first access factor for the UAV based on historical flight data includes: Extract the historical violation count (GC). When the historical violation count (GC) is greater than the default threshold, set the first access factor to the minimum value of the standard access range. When the number of historical violations GC is not greater than the violation threshold, the total historical flight time ZC is extracted, and the first access factor WZ1 is determined based on the number of historical violations GC and the total historical flight time ZC. The first access factor WZ1 satisfies formula (1): (1)； Where ZBW is the median value of the standard access range, BZC is the standard total flight time, and BGC is the average number of historical violations recorded for each drone in the database; and It is the proportional adjustment coefficient, and ; When the first access factor WZ1 is less than the minimum value of the standard access range, the first access factor WZ1 is updated using the minimum value of the standard access range; when the first access factor WZ1 is greater than the maximum value of the standard access range, the first access factor WZ1 is updated using the maximum value of the standard access range.

2. The method for safe access and dynamic monitoring of low-altitude traffic control according to claim 1, characterized in that, The acquisition of the drone's identification code, model, and historical flight data includes: The identification code of the drone used in this flight is obtained through the user account, and the drone model and total historical flight time are extracted from the database based on the identification code. Based on the identification code, extract from the database the number of violations by the drone during flight before a preset time, such as sudden hovering, deviation from the predetermined route, and illegal entry into the no-fly zone; and the number of violations during flight within a preset time, such as sudden hovering, deviation from the predetermined route, and illegal entry into the no-fly zone. Multiply the number of violations by a fixed ratio to obtain the reference number one, and add the reference number one to the number of violations by violations by violations by violations to obtain the historical number of violations.

3. The method for safe access and dynamic monitoring of low-altitude traffic control according to claim 1, characterized in that, The setting of the UAV's flight area and flight route for this flight based on its model and the first access factor includes: Extract the drone model and the user's requested flight area and flight route. If there are restrictions on the drone model within the expected flight area, the user is notified to replan the flight area. If there are restrictions on the drone model within the expected flight route, the user is notified to replan the flight route. When there are no restrictions preventing the flight of the corresponding UAV model within the expected flight area and along the expected flight route, determine whether the first access factor WZ1 is less than the access factor threshold; if yes, determine the safety distance based on formula (2). No, determine the safety distance based on formula (3). ; Formula (2): (2)； Formula (3): (3)； in, The fixed safe distance for the no-fly zone, where i is the no-fly zone number; BWZ1 is the percentile value of the standard access range; It is the proportional adjustment coefficient, and The value range is (0,2]; The safe distance from the center point of each no-fly zone The area within is set as the restricted area of ​​the current drone. The area within the expected flight area after removing each restricted area is marked as the flight area. The route within the expected flight path after removing each restricted area is marked as the flight path.

4. A method for safe access and dynamic monitoring of low-altitude traffic control according to claim 1, characterized in that, The acquisition of the position and altitude of the UAV within the flight area and the flight path includes: When a drone enters a flight area or flight route, the time requested by the user for flight is divided into several time periods based on a fixed duration. When the time is in the first time period, the position and altitude of the UAV in the flight area and flight path are obtained based on a fixed frequency GL. When the time is not at the start time of the first time period, extract the position and altitude of each time period before the current time period; determine whether there is a situation where the position or altitude exceeds the flight area and flight route; if yes, obtain the total number of times the position or altitude exceeds the flight area and flight route ZS1, determine the dynamic frequency DL of the UAV in the current time period based on the total number of times ZS1, and obtain the position and altitude of the UAV when flying within the flight area or flight route through GPS based on the dynamic frequency DL; if no, obtain the position and altitude of the UAV when flying within the flight area or flight route through GPS based on the fixed frequency GL. The dynamic frequency DL satisfies formula (4): (4)； BCS represents the number of times the standard exceeds the limit.

5. A method for safe access and dynamic monitoring of low-altitude traffic control according to claim 3, characterized in that, The safe flight factors for the UAV at various times during this flight, determined based on position and altitude, include: Extract the position and altitude of the UAV in the flight area and flight path, and obtain the total number of times ZS2 of the UAV entering the restricted area at the given position and altitude in real time; When the total number of flights ZS2 exceeds the number of flights threshold CZ, the safe flight factor of the drone for this flight will be marked as 0. When the total number of attempts ZS2 does not exceed the number of attempts threshold CZ, the safe flight factor AZ of the UAV at the current time is determined based on the total number of attempts ZS2; the safe flight factor AZ satisfies formula (5): (5)； in, It is the amplitude adjustment factor, and The value range is (0,2).

6. A method for safe access and dynamic monitoring of low-altitude traffic control according to claim 1, characterized in that, The habitual factor for determining the UAV's flight time within the currently applied flight time based on flight time includes: Extract the number of flights at each time point within a certain number of days in history, and mark the time points where the number of flights exceeds the flight count threshold as target time points; Extract the time when the user applies for flight, obtain the proportion ZB of the target time point in the applied flight time, and when the proportion ZB exceeds the preset proportion YB, set the habit factor GZ of the drone in the current applied flight time to 1. When the percentage ZB does not exceed the preset percentage YB, the habit factor GZ is obtained based on the formula GZ=ZB / YB.

7. A method for safe access and dynamic monitoring of low-altitude traffic control according to claim 1, characterized in that, The process of updating the first access factor based on a safe flight factor and a habitual factor to obtain a second access factor includes: Extract the safe flight factor AZ, the habit factor GZ, and the first access factor WZ1, and determine the second access factor WZ2 based on the safe flight factor AZ, the habit factor GZ, and the first access factor WZ1; the second access factor WZ2 satisfies formula (6): (6)； in, and All are proportional adjustment coefficients greater than 0, and , .

8. A method for safe access and dynamic monitoring of low-altitude traffic control according to claim 1, characterized in that, The step of setting the flight permissions of the current drone at the current time based on the second access factor includes: Extract the second access factor WZ2. When the second access factor WZ2 is greater than the first permission threshold, no restriction is imposed on the flight permission of the current drone at the current time. Wherein, the first permission threshold is greater than the second permission threshold. When the second access factor WZ2 is less than permission threshold one and greater than permission threshold two, the safe distance of each no-fly zone is extracted. Based on the formula Obtain the second safe distance for this flight The second safe distance from the center point of each no-fly zone. The area within is set as the restricted area of ​​the current drone. The area within the expected flight area after removing each restricted area is marked as the flight area. The route within the expected flight path after removing each restricted area is marked as the flight path. When the second access factor WZ2 is less than the permission threshold of two, the drone is prohibited from flying in the current flight area and flight route.

9. A secure access and dynamic monitoring system for low-altitude traffic control, operating based on the secure access and dynamic monitoring method for low-altitude traffic control as described in any one of claims 1 to 8, characterized in that, include: A security analysis module, and a data collection module and a dynamic authorization module connected to the security analysis module; The data collection module is used to acquire the drone's identification code, model, and historical flight data; the historical flight data includes the number of historical violations and the total historical flight time. The safety analysis module is used to determine the first access factor of the UAV based on historical flight data, and to set the flight area and flight route of the UAV for this flight based on the model and the first access factor. The dynamic authorization module is used to obtain the position and altitude of the UAV within the flight area and the flight route, determine the safe flight factor of the UAV at each time during the current flight based on the position and altitude, determine the habit factor of the UAV within the currently applied flight time based on the flight time, update the first access factor based on the safe flight factor and the habit factor to obtain the second access factor, and set the flight permission of the current UAV at the current time based on the second access factor. The determination of the first access factor for the UAV based on historical flight data includes: Extract the historical violation count (GC). When the historical violation count (GC) is greater than the default threshold, set the first access factor to the minimum value of the standard access range. When the number of historical violations GC is not greater than the violation threshold, the total historical flight time ZC is extracted, and the first access factor WZ1 is determined based on the number of historical violations GC and the total historical flight time ZC. The first access factor WZ1 satisfies formula (1): (1)； Where ZBW is the median value of the standard access range, BZC is the standard total flight time, and BGC is the average number of historical violations recorded for each drone in the database; and It is the proportional adjustment coefficient, and ; When the first access factor WZ1 is less than the minimum value of the standard access range, the first access factor WZ1 is updated using the minimum value of the standard access range; when the first access factor WZ1 is greater than the maximum value of the standard access range, the first access factor WZ1 is updated using the maximum value of the standard access range.

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