A method and system for monitoring electronic fence of unmanned aerial vehicle

Abstract

The present invention relates to the field of electronic fence technology, specifically to an electronic fence monitoring method and system for unmanned aerial vehicles, comprising the following steps: based on the real-time positioning data of the unmanned aerial vehicle, by analyzing the positioning changes of the unmanned aerial vehicle within a period of time, calculating the flight speed of the unmanned aerial vehicle, and analyzing the change trend of the flight speed of the unmanned aerial vehicle according to the flight speed data of the unmanned aerial vehicle within a period of time, and obtaining the speed information of the unmanned aerial vehicle. The present invention can analyze the distance between the unmanned aerial vehicle and the electronic fence in real time and estimate the crossing time by continuously tracking the flight speed and flight direction, thereby providing scientific data support for preventing potential safety risks, and by adjusting the warning threshold and matching the reaction time of the operator, improving the adaptability and practicality of the early warning, making the warning more timely and effective, significantly reducing the possibility of false alarms and missed alarms, enhancing the response speed and accuracy of the unmanned aerial vehicle electronic fence system, and effectively preventing the illegal flight of the unmanned aerial vehicle and the occurrence of safety accidents.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic fences, and in particular to an electronic fence monitoring method and system for an unmanned aerial vehicle. Background Art

[0002] The field of electronic fence technology is mainly used to set virtual boundaries to monitor and control the movement of objects by using GPS or RFID technology. In drone technology, electronic fences are an important safety and management tool used to ensure that drones fly within a preset airspace and prevent them from entering no-fly zones or risk areas. This technology can configure boundaries through software and set specific flight areas in the drone's control system. When the drone attempts to cross the boundary, the system will automatically take measures, such as returning or landing, to avoid potential collisions or illegal flight events.

[0003] Among them, the electronic fence monitoring method for drones involves the technical means of setting and maintaining virtual boundaries in the drone's control system to monitor and control the drone's activities in a designated airspace. The main purpose of this method is to enhance air traffic safety and prevent drones from entering sensitive or no-fly zones. It is also used for drone route management to ensure that it flies along the intended route. The electronic fence not only limits the drone's flight area, but also provides immediate feedback when the drone attempts to cross the boundary to ensure compliance with relevant airspace management regulations.

[0004] Traditional monitoring methods rely on preset flight areas and static fence configurations, lack the ability to analyze real-time dynamic data, and limit their application effectiveness under rapidly changing flight conditions. For example, when a drone deviates from the scheduled route due to environmental factors or operational errors, the traditional electronic fence system cannot adjust the warning threshold and response strategy in real time, resulting in an inability to effectively prevent the occurrence of cross-border incidents. Traditional methods only rely on the distance between the drone and the fence boundary, and fail to accurately analyze the cross-border point and time. This technical limitation will cause safety hazards and is prone to false alarms and missed alarms, making it difficult to achieve the expected monitoring and management effects. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an electronic fence monitoring method and system for an unmanned aerial vehicle.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for monitoring an electronic fence of a drone, comprising the following steps:

[0007] S1: Based on the real-time positioning data of the UAV, the flight speed of the UAV is calculated by analyzing the changes in the positioning of the UAV over a period of time. Based on the flight speed data of the UAV over a period of time, the change trend of the flight speed of the UAV is analyzed to obtain the speed information of the UAV.

[0008] S2: Based on the real-time positioning data of the drone, by analyzing the changes in the positioning of the drone over a period of time, analyzing the flight direction of the drone, and according to the preset electronic fence range coordinates, identifying the expected crossing point of the drone under the current flight trajectory, calculating the distance between the drone and the expected crossing point, and obtaining the fence distance information;

[0009] S3: Based on the drone speed information and the fence distance information, the time required for the drone to cross the boundary is calculated according to the drone's flight speed, the flight speed change rate and the electronic fence distance, and the drone crossing time evaluation result is obtained;

[0010] S4: Based on the evaluation result of the drone crossing the boundary time, according to the operator's drone operation record, analyze the operator's average reaction time when receiving the warning reminder, adjust the warning threshold, and evaluate the crossing risk level according to the drone crossing the boundary time, implement corresponding warning measures, and obtain the electronic fence monitoring result.

[0011] The present invention is improved in that the method for calculating the flight speed of the drone is:

[0012] S111: extracting three-dimensional coordinate data of the drone at different time points based on the real-time positioning data of the drone to obtain real-time three-dimensional coordinate information;

[0013] S112: Based on the real-time three-dimensional coordinate information, the formula:

[0014]

[0015] Calculate the displacement vector difference Δs of the drone at two consecutive time points, where (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at the two time points, and Δs is the displacement vector difference:

[0016] S113: Based on the displacement vector difference Δs of the UAV at two consecutive time points, the formula:

[0017]

[0018] Calculate the UAV flight speed v and obtain real-time flight speed data, where Δt is the time difference, v is the UAV flight speed, ∈ v is the correction factor for environmental factors.

[0019] The present invention is improved in that the steps of obtaining the speed information of the drone are as follows:

[0020] S121: extracting the UAV flight speed data within a period of time based on the real-time flight speed data, and obtaining the corresponding time point of the flight speed to obtain speed trend correlation data;

[0021] S122: Based on the speed trend correlation data, by formula:

[0022]

[0023] Calculate the change rate of the UAV flight speed r, where v i and v i+1 are consecutive time points t i and t i+1 The flight speed of the drone, t i and t i+1 are the i-th and i+1-th time points respectively, r is the velocity change rate, and n is the total number of time points;

[0024] S123: Based on the UAV flight speed change rate r, the UAV flight speed at the current time point is integrated to obtain UAV speed information.

[0025] The present invention is improved in that the steps of obtaining the fence distance information are:

[0026] S211: Based on the real-time positioning data of the drone, according to the three-dimensional coordinates of the drone at two consecutive time points, the formula:

[0027]

[0028] Calculate the flight direction vector Among them, (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at two time points. is the flight direction vector;

[0029] S212: Based on the flight direction vector Get the plane equation of the electronic fence, substitute the position vector and flight direction vector of the drone into the plane equation, and use the formula:

[0030]

[0031] Calculate the time scale parameters of the intersection point, where a, b, c, and g are the parameters that define the plane of the electronic fence, where ax+by+cz=g represents the plane equation of the fence, and the parameters are pre-set based on the physical layout and geographic coordinates of the fence, t is the time scale parameter from the current position of the drone to the crossing point, and (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at two time points respectively;

[0032] S213: Based on the time ratio parameter of the intersection point, by formula:

[0033] x b =x1+t(x2-x1)

[0034] and

[0035] y b =y1+t(y2-y1)

[0036] and

[0037] z b =z1+t(z2-z1)

[0038] Calculate the estimated cross-border point coordinates (x b ,y b , z b ), where (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the UAV at two time points, and t is the time ratio parameter from the current position of the UAV to the crossing point;

[0039] S214: Based on the estimated cross-border point coordinates (x b ,y b , z b ), combined with the current coordinates of the drone, through the formula:

[0040]

[0041] Calculate the expected crossing distance d and obtain the fence distance information, where d is the expected crossing distance, (x u ,y u , z u ) is the current three-dimensional coordinate of the drone, (x b ,y b , z b ) are the coordinates of the expected out-of-bounds point.

[0042] The present invention is improved in that the steps for obtaining the evaluation result of the UAV crossing the boundary time are as follows:

[0043] S311: extracting the drone flight speed, the drone flight speed change rate and the estimated crossing distance based on the drone speed information and the fence distance information, and obtaining crossing time correlation data;

[0044] S312: Based on the cross-border time association data, the formula:

[0045]

[0046] Calculate the expected crossing time T and obtain the UAV crossing time evaluation result, where v is the UAV flight speed, r is the UAV flight speed change rate, d is the expected crossing distance, ∈ T is the environmental impact coefficient, δ T is the instability coefficient of the drone.

[0047] The present invention is improved in that the method for adjusting the warning threshold is:

[0048] S411: extracting the operator's reaction time data when receiving a warning reminder according to the operator's UAV operation record, and performing average calculation to obtain the average reaction time of the operator;

[0049] S412: Based on the average reaction time of the operator, by formula:

[0050]

[0051] Calculate the adjusted warning threshold Y adjusted , get the warning threshold adjustment result, where Y adjusted is the adjusted warning threshold, Y base is the baseline warning threshold, R base is the base reaction rate, R avg is the average reaction time of the operator, k Y is the adjustment factor.

[0052] The present invention is improved in that the steps of obtaining the electronic fence monitoring result are:

[0053] S421: Based on the warning threshold adjustment result and the drone crossing time assessment result, the formula:

[0054]

[0055] Calculate the risk level L, where α L is the time sensitivity adjustment coefficient, β L is the baseline constant, k L is the basic coefficient, M is the preset minimum risk level, T is the expected crossing time, and Y adjusted is the adjusted warning threshold, e is the base of the natural logarithm, and L is the risk level;

[0056] S422: Based on the risk level L, compare with a preset risk level table, implement corresponding warning measures according to the risk level, and obtain the electronic fence monitoring result.

[0057] An electronic fence monitoring system for an unmanned aerial vehicle, the electronic fence monitoring system for an unmanned aerial vehicle is used to execute the electronic fence monitoring method for an unmanned aerial vehicle, and the system comprises:

[0058] The UAV speed analysis module is based on the real-time positioning data of the UAV. By analyzing the changes in the positioning of the UAV over a period of time, the flight speed of the UAV is calculated to obtain the real-time flight speed data;

[0059] The speed trend analysis module analyzes the change trend of the UAV flight speed based on the real-time flight speed data and the UAV flight speed data within a period of time to obtain the UAV speed information;

[0060] The distance assessment module is based on the real-time positioning data of the drone. By analyzing the changes in the drone's positioning over a period of time, the drone's flight direction is analyzed, and according to the preset electronic fence range coordinates, the drone's expected crossing point under the current flight trajectory is identified, and the distance between the drone and the expected crossing point is calculated to obtain the fence distance information;

[0061] The crossing time analysis module calculates the time required for the drone to cross the boundary based on the drone speed information and the fence distance information, according to the drone's flight speed, flight speed change rate and electronic fence distance, and obtains the drone crossing time evaluation result;

[0062] The out-of-bounds risk analysis module is based on the drone out-of-bounds time assessment result and the operator's drone operation record, analyzes the operator's average reaction time when receiving a warning reminder, adjusts the warning threshold, and assesses the out-of-bounds risk level based on the drone out-of-bounds time, implements corresponding warning measures, and obtains the electronic fence monitoring result.

[0063] Compared with the prior art, the advantages and positive effects of the present invention are:

[0064] In the present invention, by real-time analysis of the positioning changes of the drone, calculation of the drone's flight speed and prediction of potential crossing points, the efficiency and accuracy of airspace safety supervision are optimized. By continuously tracking the flight speed and flight direction, the distance between the drone and the electronic fence can be analyzed in real time, and then the crossing time can be estimated through the analysis of the flight speed and flight direction, providing scientific data support for preventing potential safety risks. By adjusting the warning threshold and matching the operator's reaction time, the adaptability and practicality of the early warning are improved, making the warning more timely and effective, significantly reducing the possibility of false alarms and missed alarms, enhancing the response speed and accuracy of the drone electronic fence system, and effectively preventing the illegal flight of drones and the occurrence of safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 is a flow chart of the method of the present invention;

[0066] Figure 2 A flow chart for calculating the flight speed of a drone according to the present invention;

[0067] Figure 3 A flow chart of obtaining the speed information of a UAV according to the present invention;

[0068] Figure 4 A flow chart of obtaining fence distance information of the present invention;

[0069] Figure 5 A flowchart of obtaining the evaluation result of the UAV crossing time of the present invention;

[0070] Figure 6 A flow chart for adjusting the warning threshold for the present invention;

[0071] Figure 7 This is a flow chart of obtaining electronic fence monitoring results in the present invention. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0073] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0074] See also Figure 1 The present invention provides a technical solution: a method for monitoring an electronic fence of a drone, comprising the following steps:

[0075] S1: Based on the real-time positioning data of the UAV, the flight speed of the UAV is calculated by analyzing the changes in the positioning of the UAV over a period of time. Based on the flight speed data of the UAV over a period of time, the change trend of the flight speed of the UAV is analyzed to obtain the speed information of the UAV.

[0076] S2: Based on the real-time positioning data of the drone, by analyzing the changes in the positioning of the drone over a period of time, analyzing the flight direction of the drone, and according to the preset electronic fence range coordinates, identifying the expected crossing point of the drone under the current flight trajectory, calculating the distance between the drone and the expected crossing point, and obtaining the fence distance information;

[0077] S3: Based on the drone speed information and fence distance information, the time required for the drone to cross the boundary is calculated according to the drone's flight speed, flight speed change rate and electronic fence distance, and the drone crossing time evaluation result is obtained;

[0078] S4: Based on the evaluation results of the drone crossing the boundary time, according to the operator's drone operation record, analyze the average reaction time of the operator when receiving the warning reminder, adjust the warning threshold according to the average reaction time, and evaluate the crossing risk level according to the drone crossing time. According to the crossing risk level, implement corresponding warning measures to obtain the electronic fence monitoring results.

[0079] Drone speed information includes the drone's flight distance per second, average speed within a time interval, and speed change rate. Fence distance information includes the estimated cross-border point location and predicted cross-border point distance. Drone cross-border time assessment results include the estimated cross-border time and the cross-border time range under differentiated speed changes. Electronic fence monitoring results include the cross-border risk level and corresponding warning measures.

[0080] See also Figure 2 , the method to calculate the flight speed of the drone is:

[0081] S111: extracting three-dimensional coordinate data of the drone at different time points based on the real-time positioning data of the drone to obtain real-time three-dimensional coordinate information;

[0082] S112: Based on the real-time three-dimensional coordinate information, the formula is:

[0083]

[0084] Calculate the displacement vector difference Δs of the drone at two consecutive time points, where (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at the two time points, and Δs is the displacement vector difference:

[0085] S113: Based on the displacement vector difference Δs of the drone at two consecutive time points, the formula:

[0086]

[0087] Calculate the UAV flight speed v and obtain real-time flight speed data, where Δt is the time difference, v is the UAV flight speed, ∈ v is the correction factor for environmental factors.

[0088] formula:

[0089]

[0090] and

[0091]

[0092] Parameter details and how to obtain them:

[0093] Three-dimensional coordinates (x1, y1, z1) and (x2, y2, z2): The coordinates represent the position of the drone at two consecutive time points t1 and t2 respectively. The coordinates are obtained in real time through the GPS or other positioning system carried by the drone.

[0094] Time difference Δt: It indicates the time interval between the flight of the drone at two time points, usually recorded by the system timestamp, that is, Δt = t2-t1.

[0095] Environmental factor correction factor ∈ v : The coefficient is used to adjust the speed calculation to adapt to environmental factors at a specific flight altitude. In practical applications, the coefficient can be obtained through empirical data, such as experimentally measuring the performance changes of the drone at different flight altitudes.

[0096] Calculation example:

[0097] Set the coordinates of the drone at time point t1 to (x1, y1, z1) = (100, 150, 200) meters, the coordinates at time point t2 to (x2, y2, z2) = (130, 180, 230) meters, and the time difference Δt to 10 seconds.

[0098] Calculate the displacement vector difference:

[0099]

[0100] Calculate the average speed:

[0101]

[0102] Set the environmental factor correction factor ∈ v 5 means a 5% impact, so the speed is adjusted to:

[0103]

[0104] The calculated result v≈5.456 m / s represents the corrected UAV flight speed, which more accurately reflects the performance under actual flight conditions. This speed takes into account the environmental factors at the altitude of the UAV and is closer to the actual flight conditions.

[0105] See also Figure 3 ,The steps to obtain the drone speed information are:

[0106] S121: extracting the UAV flight speed data within a period of time based on the real-time flight speed data, and obtaining the corresponding time point of the flight speed to obtain speed trend correlation data;

[0107] S122: Based on the speed trend correlation data, the formula is:

[0108]

[0109] Calculate the change rate of the UAV flight speed r, where v i and v i+1 are consecutive time points t i and t i+1 The flight speed of the drone, t i and t i+1 are the i-th and i+1-th time points respectively, r is the velocity change rate, and n is the total number of time points;

[0110] S123: Based on the UAV flight speed change rate r, the UAV flight speed at the current time point is integrated to obtain the UAV speed information.

[0111] formula:

[0112]

[0113] Parameter details and how to obtain them:

[0114] v i and v i+1 : is the UAV at two consecutive time points t i and t i+1 The flight speed is calculated by the previous method.

[0115] t i and t i+1 : Indicates consecutive time points. These timestamps are recorded by the drone's internal clock and sent along with the flight speed data.

[0116] n: is the total number of time points, indicating the amount of data collected and used to calculate the speed change trend.

[0117] Calculation example:

[0118] Set the drone speed data at three time points:

[0119] At t1 = 0 seconds, the speed v1 = 10 m / s, at t2 = 5 seconds, the speed v2 = 15 m / s, and at t3 = 10 seconds, the speed v3 = 20 m / s.

[0120] Calculate the speed trend.

[0121] Compute the change in velocity between two time intervals:

[0122] Δv1=v2-v1=15-10=5 m / s

[0123] Δv2=v3-v2=20-15=5 m / s

[0124] Calculate the time interval:

[0125] Δt1=t2-t1=5-0=5 seconds

[0126] Δt2=t3-t2=10-5=5 seconds

[0127] Calculate the rate of change of speed for each time period:

[0128]

[0129] Calculate the average rate of change of velocity:

[0130]

[0131] The calculated result r = 1 m / s2, which means that the speed of the drone increased by an average of 1 m / s per second during the observation period. The results show a consistent trend of the increase in the speed of the drone, providing key information for flight control and performance analysis.

[0132] See also Figure 4 , the steps to obtain fence distance information are:

[0133] S211: Based on the real-time positioning data of the drone, according to the three-dimensional coordinates of the drone at two consecutive time points, the formula:

[0134]

[0135] Calculate the flight direction vector Among them, (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at two time points. is the flight direction vector;

[0136] S212: Based on the flight direction vector Get the plane equation of the electronic fence, substitute the position vector and flight direction vector of the drone into the plane equation, and use the formula:

[0137]

[0138] Calculate the time scale parameters of the intersection point, where a, b, c, and g are the parameters that define the plane of the electronic fence, where ax+by+cz=g represents the plane equation of the fence, and the parameters are pre-set based on the physical layout and geographic coordinates of the fence, t is the time scale parameter from the current position of the drone to the crossing point, and (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at two time points respectively;

[0139] S213: Based on the time ratio parameter of the intersection point, by formula:

[0140] x b =x1+t(x2-x1)

[0141] and

[0142] y b =y1+t(y2-y1)

[0143] and

[0144] z b =z1+t(z2-z1)

[0145] Calculate the estimated cross-border point coordinates (x b ,y b , z b ), where (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the UAV at two time points, and t is the time ratio parameter from the current position of the UAV to the crossing point;

[0146] S214: Based on the estimated cross-border point coordinates (x b ,y b , z b ), combined with the current coordinates of the drone, through the formula:

[0147]

[0148] Calculate the expected crossing distance d and obtain the fence distance information, where d is the expected crossing distance, (x u ,y u , z u ) is the current three-dimensional coordinate of the drone, (x b ,y b , z b ) are the coordinates of the expected out-of-bounds point.

[0149] formula:

[0150]

[0151] x b =x1+t(x2-x1),

[0152] y b =y1+t(y2-y1),

[0153] z b =z1+t(z2-z1)

[0154] and

[0155]

[0156] Parameter details and how to obtain them:

[0157] (x1, y1, z1) and (x2, y2, z2): The coordinates represent the three-dimensional spatial position of the drone at two consecutive time points, which are obtained in real time through the drone's GPS or other positioning system.

[0158] a, b, c, g: are the parameters that define the plane of the electronic fence, where ax+by+cz=g represents the plane equation of the fence. The parameters are pre-set based on the layout and geographic coordinates of the fence.

[0159] t: It is the time ratio parameter from the current position of the UAV to the crossing point, which is obtained by solving the intersection of the plane and the UAV flight path.

[0160] Calculation example:

[0161] The position of the drone at time point t1 is set to (x1, y1, z1) = (100, 200, 300) meters, and the position at t2 is set to (x2, y2, z2) = (150, 250, 350) meters. The plane equation of the electronic fence is x+2y+3z=2100.

[0162] Flight direction vector calculation:

[0163]

[0164] Solve for the intersection time parameter t:

[0165]

[0166] Calculate the coordinates of the expected out-of-bounds point:

[0167] x b =100+2.33×50=216.5

[0168] y b =200+2.33×50=316.5

[0169] z b =300+2.33×50=416.5

[0170] The calculation result shows that the coordinates of the crossing point are (216.5, 316.5, 416.5), and the current position of the drone is set to (x u ,y u , z u )=(100, 200, 300) meters.

[0171] Calculate the distance d between the drone and the expected crossing point:

[0172]

[0173] The calculated result d≈201.8 meters represents the straight-line distance between the current position of the drone and the expected crossing point. It can be used to assess the proximity of the drone to the prohibited area and adjust the course in time to avoid crossing the boundary.

[0174] See also Figure 5 ,The steps to obtain the evaluation results of the UAV crossing the boundary time are:

[0175] S311: extracting the flight speed of the drone, the change rate of the flight speed of the drone and the estimated crossing distance based on the drone speed information and the fence distance information, and obtaining the crossing time correlation data;

[0176] S312: Based on the cross-border time correlation data, the formula is:

[0177]

[0178] Calculate the expected crossing time T and obtain the UAV crossing time evaluation result, where v is the UAV flight speed, r is the UAV flight speed change rate, d is the expected crossing distance, ∈ T is the environmental impact coefficient, δ T is the instability coefficient of the drone.

[0179] formula:

[0180]

[0181] Parameter details and how to obtain them:

[0182] v: UAV flight speed, calculated by the previous steps.

[0183] r: Flight speed change rate, calculated by the previous steps.

[0184] d: Estimated out-of-bounds distance, calculated using the previous steps.

[0185] ∈ T :Environmental impact coefficient is a preset parameter, which is set according to the wind speed of the drone’s operating environment. It reflects the impact of environmental factors on the drone’s flight performance.

[0186] δ T : Drone instability coefficient, a preset value set based on the drone's historical performance data and potential mechanical fluctuations, used to compensate for speed changes caused by performance instability.

[0187] Calculation example:

[0188] Set the following parameters:

[0189] v = 10 m / s (current drone flight speed), r = 0.2 m / s2 (speed change rate), d = 500 m (distance from the drone to the crossing point), ∈ T =0.05 (environmental impact coefficient), δ T =0.03 (UAV instability coefficient).

[0190] Calculation process:

[0191] Initial estimated crossing time T initial :

[0192]

[0193] The average speed takes into account the rate of change of speed:

[0194]

[0195] Cross-border time calculation:

[0196]

[0197] The calculation shows that it takes about 36.0 seconds for the drone to cross the boundary. The calculation results take into account the impact of the drone's acceleration behavior and environmental and mechanical stability factors, providing important information for the flight control system to adjust the flight plan in time or take appropriate preventive measures.

[0198] See also Figure 6 , the method to adjust the warning threshold is:

[0199] S411: extracting the operator's reaction time data when receiving a warning reminder according to the operator's UAV operation record, and performing average calculation to obtain the average reaction time of the operator;

[0200] S412: Based on the average reaction time of the operator, by the formula:

[0201]

[0202] Calculate the adjusted warning threshold Y adjusted , get the warning threshold adjustment result, where Y adjusted is the adjusted warning threshold, Y base is the baseline warning threshold, R base is the base reaction rate, R avg is the average reaction time of the operator, k Y is the adjustment factor.

[0203] formula:

[0204]

[0205] Parameter details and how to obtain them:

[0206] Y base : Baseline warning threshold, an initial warning time set based on industry safety standards and past experience data to provide operators with adequate response time in the absence of a specific risk assessment.

[0207] R base : The benchmark reaction speed is the average reaction time based on past drone operation data statistics, which represents the average time it takes for an operator to receive a warning and start responding under normal circumstances.

[0208] R avg : The average reaction time of the operator is obtained by analyzing the actual reaction time records of the operator in multiple warning events and calculating the average value.

[0209] k Y : Adjustment coefficient, a coefficient that is flexibly set according to the operating conditions, used to adjust the sensitivity of the warning threshold. The size of the coefficient reflects the adjustment range for the reaction time difference.

[0210] Calculation example:

[0211] Set the following parameters: base = 30 seconds (base warning threshold), R base = 10 seconds (baseline reaction speed), R avg = 12 seconds (average operator reaction time), k Y =0.1 (adjustment coefficient).

[0212] Calculation process:

[0213] Calculate the relative difference between the operator's reaction time and the baseline reaction speed:

[0214]

[0215] Calculate the adjusted warning threshold:

[0216] Y adjusted =Y base ×(1+k Y × Deviation)

[0217] =30×(1+0.1×0.2)

[0218] =30×1.02

[0219] =30.6s

[0220] Calculated Y adjusted= 30.6 seconds, indicating that according to the situation that the actual reaction time of the operator is slower than the benchmark reaction speed, the warning threshold is appropriately increased to ensure that the operator has enough time to react.

[0221] See also Figure 7 , the steps to obtain the electronic fence monitoring results are:

[0222] S421: Based on the warning threshold adjustment result and the drone crossing time assessment result, the formula is:

[0223]

[0224] Calculate the risk level L, where α L is the time sensitivity adjustment coefficient, β L is the baseline constant, k L is the basic coefficient, M is the preset minimum risk level, T is the expected crossing time, and Y adjusted is the adjusted warning threshold, e is the base of the natural logarithm, and L is the risk level;

[0225] S422: Based on the risk level L, the risk level is compared with the preset risk level table, and corresponding warning measures are implemented according to the risk level to obtain the electronic fence monitoring result.

[0226] formula:

[0227]

[0228] Parameter details and how to obtain them

[0229] α L : Time sensitivity adjustment factor, used to adjust the impact of time difference on risk level assessment. The factor is based on simulation or historical data analysis to ensure that the sensitivity of risk level to time matches the actual flight safety requirements.

[0230] k L : Base coefficient, used to adjust the impact of time difference in risk calculation. Usually set based on empirical data to ensure that the baseline of risk assessment is consistent with the actual operational safety standards.

[0231] β L : Baseline constant used to ensure that a certain risk level is maintained even when the time difference is small. The parameters are based on security requirements and risk management strategies.

[0232] M: Minimum risk level, M is the lowest risk level set to ensure that the system can alert the operator to potential risks even under optimal conditions. This is the minimum risk threshold determined based on safety standards and regulatory requirements.

[0233] Calculation Example

[0234] Assume the following parameters: α L =0.05, k L =10,β L =2, M = 5, T = 10 seconds (the estimated time for the drone to cross the boundary), Y adjusted = 12 seconds (adjusted warning threshold).

[0235] Calculate the time difference ΔT:

[0236] ΔT=TY adjusted =10-12=-2s

[0237] Calculation of risk level L:

[0238]

[0239]

[0240] The calculated L=14 indicates a risk level of 14, which is calculated based on the time difference between the estimated crossing time and the warning threshold. Since the difference is negative, it means that the actual crossing time is shorter than the warning threshold, and the risk level increases. This high risk level reflects the high risk of the drone crossing the boundary, and timely preventive measures need to be taken to avoid possible safety incidents.

[0241] An electronic fence monitoring system for a drone, the electronic fence monitoring system for a drone is used to execute the above-mentioned electronic fence monitoring method for a drone, and the system comprises:

[0242] The UAV speed analysis module is based on the real-time positioning data of the UAV. By analyzing the changes in the positioning of the UAV over a period of time, the flight speed of the UAV is calculated to obtain the real-time flight speed data;

[0243] The speed trend analysis module is based on real-time flight speed data. According to the flight speed data of the drone over a period of time, it analyzes the change trend of the drone's flight speed and obtains the drone's speed information;

[0244] The distance assessment module is based on the real-time positioning data of the drone. By analyzing the changes in the drone's positioning over a period of time, the drone's flight direction is analyzed, and according to the preset electronic fence range coordinates, the drone's expected crossing point under the current flight trajectory is identified, and the distance between the drone and the expected crossing point is calculated to obtain the fence distance information;

[0245] The crossing time analysis module is based on the drone speed information and fence distance information, and calculates the time required for the drone to cross the boundary according to the drone's flight speed, flight speed change rate and electronic fence distance, and obtains the drone crossing time evaluation result;

[0246] The out-of-bounds risk analysis module is based on the drone out-of-bounds time assessment results and the operator's drone operation records. It analyzes the operator's average reaction time when receiving a warning reminder, adjusts the warning threshold based on the average reaction time, and assesses the out-of-bounds risk level based on the drone out-of-bounds time. According to the out-of-bounds risk level, corresponding warning measures are implemented to obtain the electronic fence monitoring results.

[0247] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for monitoring an electronic fence of a drone, characterized in that: The following steps are involved: Based on the real-time positioning data of the UAV, the flight speed of the UAV is calculated by analyzing the changes in the positioning of the UAV over a period of time. Based on the flight speed data of the UAV over a period of time, the change trend of the flight speed of the UAV is analyzed to obtain the speed information of the UAV. Based on the real-time positioning data of the drone, by analyzing the changes in the drone's positioning over a period of time, analyzing the drone's flight direction, and according to the preset electronic fence range coordinates, identifying the drone's expected crossing point under the current flight trajectory, calculating the distance between the drone and the expected crossing point, and obtaining the fence distance information; Based on the drone speed information and the fence distance information, the time required for the drone to cross the boundary is calculated according to the drone's flight speed, the flight speed change rate and the electronic fence distance, and the drone crossing time evaluation result is obtained; Based on the drone crossing-border time assessment result, according to the operator's drone operation record, the operator's average reaction time when receiving a warning reminder is analyzed, the warning threshold is adjusted, and according to the drone crossing-border time, the crossing risk level is evaluated, and corresponding warning measures are implemented to obtain the electronic fence monitoring result.

2. The electronic fence monitoring method of a drone according to claim 1, characterized in that: The method for calculating the flight speed of the drone is: Based on the real-time positioning data of the UAV, the three-dimensional coordinate data of the UAV at different time points is extracted to obtain the real-time three-dimensional coordinate information; Based on the real-time three-dimensional coordinate information, by formula: Calculate the displacement vector difference Δs of the drone at two consecutive time points, where (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at the two time points, and Δs is the displacement vector difference: Based on the displacement vector difference Δs of the UAV at two consecutive time points, the formula: Calculate the UAV flight speed v and obtain real-time flight speed data, where Δt is the time difference, v is the UAV flight speed, ∈ v is the correction factor for environmental factors.

3. The electronic fence monitoring method of a drone according to claim 2, characterized in that: The steps for obtaining the UAV speed information are as follows: Based on the real-time flight speed data, extract the flight speed data of the drone within a period of time, obtain the corresponding time point of the flight speed, and obtain speed trend correlation data; Based on the speed trend correlation data, by formula: Calculate the change rate of the UAV flight speed r, where v i and v i+1 are consecutive time points t i and t i+1 The flight speed of the drone, t i and t i+1 are the i-th and i+1-th time points respectively, r is the velocity change rate, and n is the total number of time points; Based on the UAV flight speed change rate r, the UAV flight speed at the current time point is integrated to obtain the UAV speed information.

4. The electronic fence monitoring method of a drone according to claim 1, characterized in that: The steps for obtaining the fence distance information are as follows: Based on the real-time positioning data of the drone, according to the three-dimensional coordinates of the drone at two consecutive time points, the formula: Calculate the flight direction vector Among them, (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at two time points. is the flight direction vector; Based on the flight direction vector Get the plane equation of the electronic fence, substitute the position vector and flight direction vector of the drone into the plane equation, and use the formula: Calculate the time scale parameters of the intersection point, where a, b, c, and g are the parameters that define the plane of the electronic fence, where ax+by+cz=g represents the plane equation of the fence, and the parameters are pre-set based on the physical layout and geographic coordinates of the fence, t is the time scale parameter from the current position of the drone to the crossing point, and (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the drone at two time points respectively; Based on the time ratio parameter of the intersection point, by the formula: Xb=x1+t(x2-X1) and yby1+t(y2-y1 and Zb=z1+t(Z2-z1) Calculate the estimated cross-border point coordinates (x b ,y b , z b ), where (x1, y1, z1) and (x2, y2, z2) are the three-dimensional coordinates of the UAV at two time points, and t is the time ratio parameter from the current position of the UAV to the crossing point; Based on the estimated cross-border point coordinates (x b ,y b , z b ), combined with the current coordinates of the drone, through the formula: Calculate the expected crossing distance d and obtain the fence distance information, where d is the expected crossing distance, (x u ,y u , z u ) is the current three-dimensional coordinate of the drone, (x b ,y b , z b ) are the coordinates of the expected out-of-bounds point.

5. The electronic fence monitoring method of a drone according to claim 1, characterized in that: The steps for obtaining the drone crossing boundary time assessment result are as follows: Based on the drone speed information and fence distance information, extract the drone flight speed, the drone flight speed change rate and the estimated crossing distance to obtain crossing time correlation data; Based on the cross-border time association data, the formula: Calculate the expected crossing time T and obtain the UAV crossing time evaluation result, where v is the UAV flight speed, r is the UAV flight speed change rate, d is the expected crossing distance, ∈ T is the environmental impact coefficient, δ T is the instability coefficient of the drone.

6. The electronic fence monitoring method of a drone according to claim 1, characterized in that: The method for adjusting the warning threshold is: According to the operator's drone operation records, the operator's reaction time data when receiving warning reminders is extracted and averaged to obtain the operator's average reaction time; Based on the average reaction time of the operators, by the formula: Calculate the adjusted warning threshold Yaadjusted to obtain the warning threshold adjustment result, where Yaadjusted is the adjusted warning threshold, Ybase is the benchmark warning threshold, Rbase is the benchmark reaction speed, Ravg is the average reaction time of the operator, and k Y is the adjustment factor.

7. The electronic fence monitoring method of a drone according to claim 6, characterized in that: The steps for obtaining the electronic fence monitoring results are: Based on the warning threshold adjustment result and the drone crossing time assessment result, the formula is: Calculate the risk level L, where α L is the time sensitivity adjustment coefficient, β L is the baseline constant, k L is the basic coefficient, M is the preset minimum risk level, T is the expected crossing time, and Y adjusted is the adjusted warning threshold, e is the base of the natural logarithm, and L is the risk level; Based on the risk level L, it is compared with a preset risk level table, and corresponding warning measures are implemented according to the risk level to obtain the electronic fence monitoring result.

8. An electronic fence monitoring system for a drone, characterized in that: According to the electronic fence monitoring method of a drone according to any one of claims 1 to 7, the system comprises: The UAV speed analysis module is based on the real-time positioning data of the UAV. By analyzing the changes in the positioning of the UAV over a period of time, the flight speed of the UAV is calculated to obtain the real-time flight speed data; The speed trend analysis module analyzes the change trend of the UAV flight speed based on the real-time flight speed data and the UAV flight speed data within a period of time to obtain the UAV speed information; The distance assessment module is based on the real-time positioning data of the drone. By analyzing the changes in the drone's positioning over a period of time, the drone's flight direction is analyzed, and according to the preset electronic fence range coordinates, the drone's expected crossing point under the current flight trajectory is identified, and the distance between the drone and the expected crossing point is calculated to obtain the fence distance information; The crossing time analysis module calculates the time required for the drone to cross the boundary based on the drone speed information and the fence distance information, according to the drone's flight speed, flight speed change rate and electronic fence distance, and obtains the drone crossing time evaluation result; The out-of-bounds risk analysis module is based on the drone out-of-bounds time assessment result and the operator's drone operation record, analyzes the operator's average reaction time when receiving a warning reminder, adjusts the warning threshold, and assesses the out-of-bounds risk level based on the drone out-of-bounds time, implements corresponding warning measures, and obtains the electronic fence monitoring result.

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