Unmanned aerial vehicle aerial three-dimensional electronic fence construction method and system

Abstract

The invention discloses an unmanned aerial vehicle aerial three-dimensional electronic fence construction method and system, and relates to the technical field of unmanned aerial vehicles, and the method comprises the following steps: dividing the region boundary of an electronic fence in a preset geographic range based on a geographic information system and a three-dimensional modeling technology, and calculating the range of the electronic fence; integrating the configured electronic fence to an unmanned aerial vehicle system, establishing a real-time communication and data exchange channel with the unmanned aerial vehicle, and receiving position information and flight state data fed back in the flight process of the unmanned aerial vehicle in real time; and monitoring the flight state of the unmanned aerial vehicle and the area boundary of the electronic fence in real time, and triggering an early warning mechanism when the unmanned aerial vehicle is found to have a boundary crossing behavior. According to the electronic fence system, the size, shape and position of the fence can be automatically adjusted according to the real-time flight state of the unmanned aerial vehicle and the environment change, the dynamic adjustment capability of the electronic fence is directly improved, and it is ensured that the unmanned aerial vehicle can always fly safely in the complex and changeable airspace environment.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles (UAVs), and in particular to a method and system for constructing a three-dimensional electronic fence for UAVs. Background Art

[0002] With the rapid development of drone technology, drones are increasingly being used in various fields. Drones can easily enter various areas, including private property, sensitive facilities, and densely populated areas. These areas may face security risks or privacy breaches due to drone interference. Drones may also collide with other aircraft, buildings, or people during flight, causing serious safety incidents. Furthermore, unauthorized drones may enter restricted areas, such as airports and military bases, disrupting normal air traffic.

[0003] As an emerging security protection measure, drone aerial three-dimensional electronic fence prevents drones from flying into or out of specific areas by dynamically adjusting area boundaries within the corresponding geographical range using electronic information models. It ensures that drones can hover or automatically return when approaching or entering prohibited flight areas, thereby effectively protecting the safety and privacy of sensitive areas, while effectively avoiding flight conflicts and safety accidents.

[0004] Drone electronic fencing is a technology system designed to ensure regional security. Its primary purpose is to electronically restrict drone flights within specific areas. This system combines hardware and software technologies, using electronic information models within the drone system or drone cloud system to define area boundaries, preventing drones from entering or leaving these areas, thereby ensuring the safety of both aircraft and people on the ground.

[0005] While existing technologies such as the Global Positioning System (GPS) and the Beidou Satellite Navigation System offer high positioning accuracy, positioning signals can be interfered with in complex environments (such as urban canyons and areas with densely populated high-rise buildings), leading to reduced positioning accuracy or signal loss, thus compromising the accuracy and reliability of electronic fences. Furthermore, the boundary determination and control decision-making models of electronic fence systems require continuous optimization and improvement to ensure prompt and accurate response when drones approach or cross the fence boundary. However, existing algorithms can misjudge or miss detections in complex scenarios, impacting overall system performance.

[0006] For example, Chinese patent CN113784284B discloses a method for avoiding electronic fences for fixed-wing drones. The method includes: Step 1: Setting an electronic fence shape. Based on airspace usage requirements and restrictions, the electronic fence shape is set to describe the drone's effective airspace usage range; Step 2: Electronic fence contact detection. Based on the drone's current longitude and latitude and the longitude and latitude of the electronic fence shape, combined with the drone's flight speed and heading, the drone calculates whether it has touched or is about to touch the electronic fence; Step 3: Activating an electronic fence avoidance strategy. When the drone is about to touch the electronic fence, the drone selects a suitable position and hovers to await ground station instructions to avoid flying out of the electronic fence. This method addresses the problem that existing electronic fence technology is not suitable for fixed-wing drones because its avoidance method is designed for rotary-wing drones with fixed-point hovering and vertical landing capabilities. However, this method still has several shortcomings, including: 1. In practical applications, it may be affected by factors such as signal interference and multipath effects, resulting in reduced positioning accuracy, thereby affecting the dynamic adjustment capability of the electronic fence. 2. Traditional electronic fences often only define simple rectangular or circular areas. 3. Complex system integration and management: The system design that integrates multiple energy sources is complex and requires advanced coordination and intelligent control technologies to ensure stable operation.

[0007] Currently, no effective solutions have been proposed for the problems in related technologies. Summary of the Invention

[0008] In response to the problems in the related art, the present invention proposes a method and system for constructing a three-dimensional electronic fence in the air for UAVs to overcome the above-mentioned technical problems existing in the existing related art.

[0009] To this end, the specific technical solutions adopted in the present invention are as follows: According to one aspect of the present invention, a method for constructing a three-dimensional electronic fence in the air by a drone is provided, the method comprising the following steps: S1. Based on geographic information system and 3D modeling technology, divide the area boundary of the electronic fence within the preset geographical range, calculate the range of the electronic fence, and set the fence parameters of the electronic fence; S2. Integrate the configured electronic fence into the drone system, establish a real-time communication and data exchange channel with the drone, receive real-time feedback on the drone's location and flight status during flight, and dynamically adjust the electronic fence's area boundaries and fence parameters based on flight requirements; S3: Monitor the flight status of the drone and the boundary of the electronic fence in real time. When a drone is found to be crossing the boundary, the early warning mechanism is triggered to identify the dangerous state of the drone and output corresponding control measures.

[0010] Furthermore, based on the geographic information system and three-dimensional modeling technology, dividing the regional boundaries of the electronic fence within the preset geographical range, calculating the electronic fence range, and setting the fence parameters of the electronic fence include the following steps: S11. Select a target area within a preset geographic range, use a laser radar mounted on a drone to collect three-dimensional spatial data of the target area, and generate a three-dimensional model of the target area through point cloud construction and spatial coordinate system conversion; S12. Based on the satellite positioning system, the flight position of the drone is monitored in real time. In combination with wireless signal transmitters and receivers deployed on the ground, wireless positioning technology is used to capture the location information of the drone during flight. S13. Set a preset distance according to actual needs, divide the three-dimensional model using the preset distance to obtain a division result, and perform calculations based on the division result to obtain the range of the electronic fence and determine the area boundary of the electronic fence.

[0011] Furthermore, a target area is selected within a preset geographic range, and three-dimensional spatial data of the target area is collected using a lidar carried by a drone. A three-dimensional model of the target area is generated through point cloud construction and spatial coordinate system conversion, including the following steps: S111, using a laser radar carried by the drone to transmit laser pulses to the target area, and obtaining distance information of the target area by receiving the transmitted signals, until the drone completely scans the target area, thereby obtaining three-dimensional spatial data of the target area; S112. Based on the internal and external parameters of the laser radar, the discrete points in the three-dimensional spatial data are converted into a unified geographic coordinate system to form a point cloud of the target area; S113. Obtain the position coordinates, attitude angle, and distance and scanning angle of each laser point of the laser radar installed on the UAV, calculate the coordinate data of each laser point in the geographic coordinate system through the spatial coordinate conversion formula, and perform noise reduction on the coordinate data. Use the coordinate data after noise reduction to construct a three-dimensional model of the target area.

[0012] Furthermore, the electronic fence covers the blue warning zone and the red warning zone; The calculation formula for the blue warning zone is:

[0013] Where, This is the blue warning area; is the rate coefficient; V is the current speed of the drone; T The estimated time from the discovery of a potential risk to the possibility of the danger occurring; is the reference distance; is the coefficient related to the degree of meteorological influence;W is the wind speed; is the angle between the wind direction and the flight direction of the drone; is the environmental interference coefficient; E is the environmental interference intensity; The calculation formula for the red warning zone is:

[0014] Where, This is the red alert area; The reaction time of the drone; k is a safety factor greater than or equal to 1; The maximum distance the drone may continue to move if there is a delay in the control signal.

[0015] Furthermore, the configured electronic fence is integrated into the drone system, a real-time communication and data exchange channel is established between the drone and the system, the position information and flight status data fed back by the drone during flight are received in real time, and the area boundary and fence parameters of the electronic fence are dynamically adjusted according to flight requirements. The following steps are included: S21. Integrate multiple types of perception sensors into the drone to collect environmental data and flight status data during flight. Based on real-time monitoring of the drone's flight status and environmental changes, predict the drone's future flight trajectory and automatically adjust the fence parameters of the electronic fence to maintain the drone in a safe area. S22. Spectrum analysis chips are built into the drone and ground station. They continuously scan the communication frequency band to obtain the energy distribution within the frequency band. When abnormal signal fluctuations or interference signals are detected, the communication parameters are adjusted and the communication frequency is adjusted through the frequency synthesizer to maintain communication stability between the drone and the ground station. S23. Acquire meteorological data of the target area in real time, process and analyze the meteorological data, associate it with the fence parameters of the electronic fence, and adjust the fence parameters based on the meteorological data and the association results.

[0016] Furthermore, based on real-time monitoring of the drone's flight status and environmental changes, the drone's future flight trajectory is predicted, and the fence parameters of the electronic fence are automatically adjusted to maintain the drone in a safe area. The following steps are included: S211, sharing the location information and real-time flight status of each drone with the drone swarm, transmitting control instructions and flight intentions of different drones in the drone swarm. When the drone swarm performs a collaborative mission, the leader drone sends mission instructions and path planning information to other drones; S212, continuously monitoring the location information and real-time flight status of the UAV, recording the flight trajectory of the UAV at equal time intervals to obtain continuous trajectory points to display the position coordinates of the UAV in the three-dimensional model at each moment; and predicting the UAV's location information at the next moment based on the location information corresponding to the historical trajectory points of the UAV flight; S213. When the predicted result of the drone's position information at the next moment exceeds the range of the electronic fence, the fence parameters of the electronic fence are automatically adjusted to adapt to the flight changes of the drone.

[0017] Furthermore, real-time meteorological data of the target area is obtained, the meteorological data is processed and analyzed, and associated with the fence parameters of the electronic fence, and the fence parameters are adjusted based on the meteorological data and the association results, including the following steps: S231, cleaning and screening the collected meteorological data, eliminating outliers and erroneous data, analyzing and processing the cleaned and screened meteorological data using a data analysis algorithm, and extracting the changing trend of the meteorological data; S232: Associating the analyzed and processed meteorological data with the fence parameters of the electronic fence, and adjusting the corresponding fence parameters according to the numerical changes of specific data in the meteorological data.

[0018] Furthermore, the flight status of the drone and the boundary of the electronic fence are monitored in real time. When a drone is found to be crossing the boundary, an early warning mechanism is triggered to identify the dangerous state of the drone and output corresponding control measures. The following steps are included: S31. Obtain operating parameters of each working module of the drone and the drone swarm, calculate the free space path loss value and multi-frequency correlation value of each working module, and determine the relative distance between the drone and the boundary of the electronic fence area by mining the potential correlation between the operating parameters; S32. Compare the real-time location information of the drone with the preset electronic fence area boundary, and combine it with the cross-border detection algorithm based on the ray method to determine whether the drone has crossed the boundary. If there is cross-border behavior, the early warning mechanism is triggered, marking the drone in a dangerous state, and outputting control measures to implement anti-intrusion.

[0019] Furthermore, the free space path loss value is calculated as:

[0020] Where, is the free space path loss value; d is the distance to be calculated; is the wavelength value of each working module; The calculation formula of the multi-frequency correlation value is:

[0021] Where, is the multi-frequency correlation value; is the reference frequency; f is the operating frequency of the drone.

[0022] According to another aspect of the present invention, a system for constructing a three-dimensional electronic fence in the air by a drone is provided, the system comprising: The electronic fence calculation module is used to divide the area boundary of the electronic fence within a preset geographical range, calculate the electronic fence range, and set the fence parameters of the electronic fence based on the geographic information system and three-dimensional modeling technology; The electronic fence configuration module is used to integrate the configured electronic fence into the drone system, establish a real-time communication and data exchange channel with the drone, receive real-time feedback on the drone's position information and flight status data during flight, and dynamically adjust the area boundaries and fence parameters of the electronic fence according to flight requirements; The electronic fence monitoring module is used to monitor the flight status of the drone and the area boundary of the electronic fence in real time. When a drone is found to be crossing the boundary, the early warning mechanism is triggered, the dangerous state of the drone is identified, and corresponding control measures are output.

[0023] The beneficial effects of the present invention are: 1. To address the problem that existing technologies may cause reduced positioning accuracy due to signal interference and multipath effects, the electronic fence system of the present invention can automatically adjust the size, shape and position of the fence according to the real-time flight status of the drone and environmental changes, directly improving the dynamic adjustment capability of the electronic fence, ensuring that the drone can always maintain safe flight in complex and changing airspace environments, thereby improving flight safety and stability.

[0024] 2. The area defined by traditional electronic fences is limited in shape and can usually only be a simple rectangle or circle. The present invention uses point cloud construction and noise reduction and three-dimensional modeling technology to support the construction of fences of any shape and size. This enables electronic fences to better adapt to complex and changing airspace environments, improving space utilization and flexibility.

[0025] 3. In response to the problem that the system design of integrating multiple energy sources is complex and requires advanced coordination and intelligent control technologies, the present invention can accurately judge the flight data of the UAV through an out-of-bounds detection algorithm based on the ray method and the correlation mining technology of multi-frequency parameters, so that ground personnel can grasp the flight status of the UAV at any time, discover and deal with potential problems in a timely manner, thereby improving the reliability and response speed of the overall system. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 This is a flow chart of a method for constructing a three-dimensional electronic fence in the air of a drone according to an embodiment of the present invention; Figure 2 This is a principle block diagram of a system for constructing a three-dimensional electronic fence in the air by a drone according to an embodiment of the present invention; Figure 3 is a logic flow chart of an electronic fence according to an embodiment of the present invention; Figure 4 is a diagram of a drone electronic fence model according to an embodiment of the present invention; Figure 5 is a schematic diagram of a cross-border detection algorithm based on a ray method according to an embodiment of the present invention; Figure 6 This is a flow chart of adjusting the range of an electronic fence using meteorological data according to an embodiment of the present invention.

[0028] In the picture: 1. Electronic fence calculation module; 2. Electronic fence configuration module; 3. Electronic fence monitoring module. DETAILED DESCRIPTION

[0029] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention. They are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. By referring to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and the advantages of the present invention.

[0030] According to an embodiment of the present invention, a method for constructing a three-dimensional electronic fence in the air of a drone is provided.

[0031] The present invention will now be further described with reference to the accompanying drawings and specific embodiments. Figure 1 As shown in the figure, a method for constructing a three-dimensional electronic fence in the air of a drone according to an embodiment of the present invention includes the following steps: S1. Based on geographic information system and 3D modeling technology, the regional boundary of the electronic fence is divided within the preset geographical range, the range of the electronic fence is calculated, and the fence parameters of the electronic fence are set.

[0032] Specifically, using geographic information system (GIS) technology and three-dimensional modeling technology, the area boundaries are drawn with electronic information models within the corresponding geographical range, and parameters such as the shape, size and location of the electronic fence are set. Users can adjust the parameters and boundaries of the electronic fence at any time as needed to adapt to different application scenarios and flight missions.

[0033] In the description of the present invention, based on geographic information systems and three-dimensional modeling technology, dividing the area boundary of the electronic fence within a preset geographic range, calculating the electronic fence range, and setting the fence parameters of the electronic fence include the following steps: S11. Select a target area within a preset geographic range, use the lidar carried by the drone to collect three-dimensional spatial data of the target area, and generate a three-dimensional model of the target area through point cloud construction and spatial coordinate system conversion.

[0034] In the description of the present invention, a target area is selected within a preset geographical range, three-dimensional spatial data of the target area is collected using a lidar carried by a drone, and a three-dimensional model of the target area is generated through point cloud construction and spatial coordinate system conversion, including the following steps: S111. Use the laser radar carried by the drone to emit laser pulses to the target area, and obtain distance information of the target area by receiving the transmitted signal until the drone completely scans the target area to obtain three-dimensional spatial data of the target area.

[0035] S112. Based on the internal and external parameters of the laser radar, the discrete points in the three-dimensional spatial data are converted into a unified geographic coordinate system to form a point cloud of the target area.

[0036] Specifically, the distance information of the target is first obtained by emitting laser pulses and receiving reflected signals through the laser radar carried by the drone. After the laser radar sensor is installed on the drone, as the drone flies, the laser radar obtains the three-dimensional spatial data of the target area according to a certain scanning mode (such as linear scanning, conical scanning, etc.). According to the internal parameters of the laser radar (such as the divergence angle of the laser beam, scanning frequency, etc.) and external parameters (the position and attitude of the sensor, usually provided by the drone's positioning system and inertial measurement unit), the obtained discrete point data is converted to a unified geographic coordinate system and finally constructed into a point cloud. The position coordinates of the laser radar installed on the drone are known. The position of each laser point in the geographic coordinate system can be calculated by the spatial coordinate conversion formula based on the attitude angles (pitch, roll, yaw), the distance and scanning angle of each laser point.

[0037] S113. Obtain the position coordinates, attitude angle, and distance and scanning angle of each laser point of the laser radar installed on the UAV, calculate the coordinate data of each laser point in the geographic coordinate system through the spatial coordinate conversion formula, and perform noise reduction on the coordinate data. Use the coordinate data after noise reduction to construct a three-dimensional model of the target area.

[0038] Specifically, after obtaining geographic coordinate data, it is necessary to perform noise reduction processing on the data to obtain more accurate, denoised data. This process typically uses a specific algorithm to filter and denoise the collected data. Using a median filter algorithm, noise points in the data are replaced with the median of the surrounding data, effectively removing noise.

[0039] At the same time, according to the number of laser scans, the data is converted into polar coordinates ( is the polar distance, The data after noise elimination can be used to construct a 3D model. This 3D model supports the construction of fences of any shape and size, and can more intuitively reflect the actual position and shape of the electronic fence, such as Figure 4 The figure shows the model diagram of the electronic fence.

[0040] S12. Based on the satellite positioning system, the flight position of the drone is monitored in real time. In combination with wireless signal transmitters and receivers deployed on the ground, wireless positioning technology is used to capture the location information of the drone during flight.

[0041] Specifically, the Global Positioning System (GPS) and China's independently developed Beidou satellite navigation system provide high-precision latitude and longitude information to monitor the drone's flight position in real time. Simultaneously, by deploying a certain number of wireless signal transmitters or receivers on the ground, the characteristics of signal propagation are used to infer the drone's location, unaffected by satellite signal obstruction. Furthermore, ground-based wireless positioning technology offers relatively low cost and flexible deployment. It can be customized to meet specific needs based on different application scenarios. For example, at temporary event venues or construction sites, ground-based wireless positioning technology can quickly establish electronic fencing systems to ensure the safe flight of drones. Ground-based wireless positioning technology complements satellite positioning technology, improving positioning accuracy and reliability.

[0042] S13. Set a preset distance according to actual needs, divide the three-dimensional model using the preset distance to obtain a division result, and perform calculations based on the division result to obtain the range of the electronic fence and determine the area boundary of the electronic fence.

[0043] In the description of the present invention, the electronic fence range includes a blue warning area and a red warning area.

[0044] The calculation formula for the blue warning zone is:

[0045] Where, This is the blue warning area; is the calibration coefficient, which takes into account uncertainty factors such as sensor error; V is the current speed of the drone; T Time, which represents the estimated time from the discovery of potential risks to the occurrence of danger; It is a reference distance, which is related to factors such as the size of the drone itself and the minimum safe operating distance; It is a coefficient related to the degree of meteorological influence, which is used to measure the possible deviation effect of wind speed on the UAV; W is the wind speed; is the angle between the wind direction and the flight direction of the drone; is the environmental interference coefficient; E is the environmental interference intensity, which is used to describe the impact of the environment.

[0046] The calculation formula for the red warning zone is:

[0047] Where, This is the red alert area; The reaction time of the drone; k is a safety factor greater than or equal to 1, used to take into account the delay of drone control signals; The maximum distance the drone may continue to move if there is a delay in the control signal.

[0048] S2. Integrate the configured electronic fence into the drone system, establish a real-time communication and data exchange channel with the drone, receive real-time feedback on the location information and flight status data of the drone during flight, and dynamically adjust the area boundary and fence parameters of the electronic fence according to flight requirements.

[0049] In the present invention, integrating a configured electronic fence into a drone system, establishing a real-time communication and data exchange channel with the drone, receiving real-time position information and flight status data fed back by the drone during flight, and dynamically adjusting the area boundaries and fence parameters of the electronic fence according to flight requirements include the following steps: S21. Integrate various types of perception sensors into the drone to collect environmental data and flight status data during the flight. Based on real-time monitoring of the drone's real-time flight status and environmental changes, predict the drone's flight trajectory at future times, and automatically adjust the fence parameters of the electronic fence to keep the drone in a safe area.

[0050] In the present invention, based on real-time monitoring of the drone's flight status and environmental changes, predicting the drone's future flight trajectory, and automatically adjusting the fence parameters of the electronic fence to maintain the drone in a safe area include the following steps: S211. Share the location information and real-time flight status of each drone with the drone swarm, and transmit the control instructions and flight intentions of different drones in the drone swarm. When the drone swarm performs a collaborative task, the leader drone sends task instructions and path planning information to other drones.

[0051] S212. Continuously monitor the drone's location information and real-time flight status. Record the drone's flight trajectory at regular intervals to obtain continuous trajectory points, which display the drone's position coordinates in the three-dimensional model at each moment. Based on the location information corresponding to the drone's historical trajectory points, predict the drone's location information at the next moment.

[0052] S213. When the predicted result of the drone's position information at the next moment exceeds the range of the electronic fence, the fence parameters of the electronic fence are automatically adjusted to adapt to the flight changes of the drone.

[0053] Specifically, the electronic fence system can automatically adjust the size, shape, and position of the fence based on the drone's real-time flight status and environmental changes, ensuring that the drone always remains within a safe area in complex and changing airspace environments. Dynamic adjustment technology is mainly achieved through the following methods: First, a high-precision positioning system is used to continuously monitor the drone's location. When the drone approaches the boundary of the electronic fence, the system predicts its future flight trajectory based on parameters such as the drone's flight speed and direction. During the flight, the drone's flight trajectory is recorded and transmitted back at regular intervals. If the position transmitted at time 𝑡 is:

[0054] in is the position coordinate of the UAV at the tth moment.

[0055] The position information of the first k trajectory points can be used to predict the position information of the drone at time t+1. The input vector is:

[0056] The output vector is the predicted value of the drone's position information at time t+1, that is:

[0057] Each drone in a swarm shares its own flight status information, including position, speed, acceleration, attitude, etc., in real time. In this way, each drone can obtain the current status of other drones in the swarm, and thus take the movement trends of other drones into account when predicting its own trajectory.

[0058] In addition to flight status information, drones can also communicate control commands and flight intentions. When a swarm of drones performs a coordinated mission, the mission instructions and path planning information sent by the leader drone can be received by other drones, enabling them to more accurately predict their own flight paths based on the overall mission objectives and the leader's intentions, achieving coordinated flight for the entire swarm. If the prediction indicates that a drone may fly outside the electronic fence, the system automatically adjusts the fence's position or size to accommodate the drone's flight changes.

[0059] Secondly, changes in environmental factors may also require adjustments to the geo-fence. For example, severe weather conditions such as strong winds and heavy rain may affect the drone's flight stability and navigation accuracy. In such cases, the geo-fence system collects meteorological data from various channels, including weather stations, satellite cloud images, and meteorological sensors. This data includes information such as temperature, air pressure, humidity, wind speed, wind direction, cloud distribution, and precipitation areas. The collected data is cleaned, filtered, and analyzed to remove outliers and erroneous data. Statistical analysis and image recognition are then used to extract key information related to geo-fence adjustments. This information is then linked to the geo-fence adjustment parameters and the fence's range is adjusted to ensure the drone remains within a safe area.

[0060] Furthermore, different flight missions and scenarios may require dynamic adjustments to geo-fences. For example, during emergency rescue missions, the geo-fence range may need to be expanded to allow for more flexible flight. In sensitive areas such as military bases, the geo-fence range may need to be reduced to enhance security.

[0061] S22. Spectrum analysis chips are built into the drone and ground station. By continuously scanning the communication frequency band, the energy distribution within the band is obtained. When abnormal signal fluctuations or interference signals are detected, the communication parameters are adjusted, and the communication frequency is adjusted through the frequency synthesizer to maintain the communication stability between the drone and the ground station.

[0062] Specifically, the system uses chips with built-in spectrum analyzer functionality in both the drone and ground station to continuously scan the communication frequency band and obtain information about the energy distribution within it. When abnormal signal fluctuations or interference signals are detected, the parameter adjustment module adjusts the communication parameters based on pre-set algorithms (such as least mean square (LMS) and Kalman filtering). In terms of hardware, it controls the frequency synthesizer in the communication equipment to change the communication frequency, ensuring stable and reliable communication, helping the drone maintain communication with the ground station in complex electromagnetic environments.

[0063] The transmission distance between the drone and the ground station significantly affects communication parameters. Signal loss increases with distance. Therefore, when the drone is farther away from the ground station, the system increases transmit power or decreases the communication frequency as needed to maintain communication quality. Environmental factors, such as weather conditions, can also affect communication. Inclement weather like rain and fog can exacerbate signal attenuation. In these cases, the system may automatically adjust communication parameters based on a pre-established weather communication parameter model. For example, in light rain, the system may increase transmit power and decrease the communication frequency to accommodate signal attenuation.

[0064] Furthermore, when multiple drones fly in the same area, they can communicate and share data through self-organizing networking technology. This helps improve the collaborative combat capabilities and mission execution efficiency of drone swarms, ensuring the effectiveness and reliability of drone electronic fencing systems.

[0065] S23. Acquire meteorological data of the target area in real time, process and analyze the meteorological data, associate it with the fence parameters of the electronic fence, and adjust the fence parameters based on the meteorological data and the association results.

[0066] In the description of the present invention, real-time acquisition of meteorological data of a target area, processing and analyzing the meteorological data, associating the meteorological data with the fence parameters of the electronic fence, and adjusting the fence parameters based on the meteorological data and the association results include the following steps: S231. Clean and filter the collected meteorological data, remove outliers and erroneous data, analyze and process the cleaned and filtered meteorological data using a data analysis algorithm, and extract the changing trend of the meteorological data.

[0067] S232: Associating the analyzed and processed meteorological data with the fence parameters of the electronic fence, and adjusting the corresponding fence parameters according to the numerical changes of specific data in the meteorological data.

[0068] S3: Monitor the flight status of the drone and the boundary of the electronic fence in real time. When a drone is found to be crossing the boundary, the early warning mechanism is triggered to identify the dangerous state of the drone and output corresponding control measures.

[0069] It should be noted that this system monitors the drone's flight status and the boundaries of the geo-fence in real time. If a drone approaches or enters the geo-fence boundary, an early warning mechanism is immediately triggered. A warning signal is sent to the drone via sound, light, or wireless communication, instructing it to take safety measures such as hovering or automatically returning to home.

[0070] In the description of the present invention, the real-time monitoring of the flight status of the drone and the boundary of the electronic fence area, when the drone is found to have crossed the boundary, triggering the early warning mechanism, identifying the dangerous state of the drone, and outputting corresponding control measures includes the following steps: S31. Obtain the operating parameters of each working module within the drone and drone swarm (a working module is an independent electronic unit with specific functions, which is a component of a complex electronic system. This module is mainly responsible for signal transmission and reception. It contains a series of electronic components such as power amplifiers, low-noise amplifiers, filters, etc., which work together to realize signal processing. Each drone contains one or more working modules). Calculate the free space path loss value (free space path refers to the drop in signal strength caused by spatial attenuation when a wireless signal propagates in free space) and multi-frequency correlation value of each working module. By exploring the potential correlation between the operating parameters, determine the relative distance between the drone and the boundary of the electronic fence area.

[0071] In the description of the present invention, the calculation formula of the free space path loss value is:

[0072] Where, is the free space path loss value; d is the distance to be calculated; is the wavelength value of each working module; The calculation formula of the multi-frequency correlation value is:

[0073] Where, is the multi-frequency correlation value; is the reference frequency; f is the operating frequency of the drone.

[0074] It's important to note that by exploring potential correlations between parameters, it's possible to more accurately determine whether the distance being calculated is within the geo-fence. In practice, if a drone's operating frequency is high, then according to the free-space path loss formula, its path loss at the same distance may be relatively large. Using the multi-frequency correlation formula, we can further analyze the relationship between the operating module's frequency, other module frequencies, and the reference frequency, thereby comprehensively determining the relative distance between the drone and the geo-fence boundary.

[0075] S32. Compare the real-time location information of the drone with the preset electronic fence area boundary, and combine it with the cross-border detection algorithm based on the ray method to determine whether the drone has crossed the boundary. If there is cross-border behavior, the early warning mechanism is triggered, marking the drone in a dangerous state, and outputting control measures to implement anti-intrusion.

[0076] It's important to note that the system compares the drone's real-time location with the preset geo-fence boundary and, using a ray-based boundary detection algorithm, determines whether the drone is approaching or entering the geo-fence boundary. If a drone is deemed dangerous, the system immediately takes control measures to prevent further intrusion. These measures may include issuing a warning signal, causing the drone to hover, or automatically returning to home. The control decision algorithm comprehensively considers factors such as the drone's flight status, environmental conditions, and safety requirements to make the optimal control decision.

[0077] like Figure 2 According to another embodiment of the present invention, a system for constructing a three-dimensional electronic fence in the air by a drone is provided, the system comprising: The electronic fence calculation module 1 is used to divide the area boundary of the electronic fence within a preset geographical range, calculate the electronic fence range, and set the fence parameters of the electronic fence based on the geographic information system and three-dimensional modeling technology; The electronic fence configuration module 2 is used to integrate the configured electronic fence into the UAV system, establish a real-time communication and data exchange channel with the UAV, receive real-time feedback on the location information and flight status data of the UAV during flight, and dynamically adjust the area boundary and fence parameters of the electronic fence according to flight requirements; The electronic fence monitoring module 3 is used to monitor the flight status of the drone and the area boundary of the electronic fence in real time. When a drone is found to have crossed the boundary, the early warning mechanism is triggered, the dangerous state of the drone is identified, and corresponding control measures are output.

[0078] The objectives of the present invention are: 1. According to the real-time flight status of the drone and environmental changes, the electronic fence system can automatically adjust the size, shape and position of the fence to ensure that the drone always flies within a safe area in a complex and changeable airspace environment. 2. Using intelligent analysis algorithms, the fused data is deeply mined and analyzed to identify potential safety risks, and countermeasures are formulated in advance to improve the early warning capability and emergency response speed of the electronic fence. 3. Remote monitoring capability, capable of transmitting drone flight data, images, videos and other information to the ground station or cloud server in real time. This enables ground personnel to grasp the flight status of the drone at any time and promptly discover and deal with potential problems. 4. The drone aerial three-dimensional electronic fence of the present invention supports fences of any shape and size. This enables the electronic fence to better adapt to the complex and changeable airspace environment and improve space utilization. 5. The system has good scalability and can easily connect to new sensors, data processing modules or control algorithms to adapt to the future development of drone technology and new needs of airspace management.

[0079] The present invention aims to improve the performance, reliability and practicality of drone aerial three-dimensional electronic fence systems, so that they can better adapt to the ever-changing needs of aerial safety and promote the healthy development of the drone industry.

[0080] The present invention will be further described below with reference to the accompanying drawings.

[0081] The main process steps of the present invention are as follows Figure 3 As shown, the drone constructs a point cloud, then, after noise removal, creates a 3D model that visually reflects the actual location and shape of the geo-fence. Based on the drone's real-time flight mission, scenario, and environmental changes, the geo-fence's range is automatically adjusted to ensure the drone remains within a safe zone in complex and changing airspace. Using GPS and BeiDou satellite navigation systems, combined with ground-based wireless positioning technology, the system monitors the drone's flight position in real time. Comparing the geo-fence's height and horizontal boundaries, the system determines whether the drone is approaching or entering the fence's boundary. Ultimately, it triggers a warning signal, controlling the drone to hover or automatically return home.

[0082] Use the ray detection method to determine the position relationship between the drone and the fence boundary. Generally, if Figure 5 As shown in (1), drone A is within the fence boundary, and the number of intersections with the boundary is 1; Figure 5 (2) The drone is within the fence boundary, and the number of intersections with the boundary is 3; Figure 5 (3) The point is outside the fence boundary, and the number of intersection points is 0; Figure 5 (4) The drone is outside the fence boundary, and the number of intersection points is 4. Figure 5 (5) Figure 5(6) is a special case and requires special treatment. The treatment rules are as follows: the horizontal edges of the fence boundary are not considered; when the vertex of the fence boundary intersects with the ray, if the vertex is the vertex with the larger vertical coordinate on the boundary to which it belongs, it is counted, otherwise it is ignored. The principle of determining the relevant cross-border trend is: Given the running track AB and the fence boundary CD, the coordinates of points A, B, C, and D are (a x , a y )、(b x , b y )、(c x , c y )、(d x , d y ). Extend the trajectory AB into a ray in the AB direction and calculate whether the fence boundary CD and the trajectory AB intersect. The basic idea of ​​the algorithm is to first solve the intersection point between the straight lines where the two lines are located, and then determine whether the intersection point is on the fence boundary CD and the trajectory AB. The formula used is:

[0083]

[0084] in, R is the position of the intersection of the two straight lines on the directed trajectory AB, R =0, then the intersection coincides with A. R =1, then the intersection point coincides with B. L is the position of the intersection of the two straight lines on the directed fence boundary CD, L =0, then the intersection coincides with C. L =1, then the intersection point coincides with D.

[0085] To determine whether the running track AB intersects the fence boundary CD, first determine whether the denominator is zero. If it is zero, the two lines are parallel. If R or L In the equation, if the numerator or denominator is zero at the same time, the two lines coincide; if the two lines are not parallel, then the two lines have an intersection. First, determine whether the intersection is on the fence boundary CD, that is, L Between 0 and 1, if yes, then continue to judge whether the intersection is in the positive direction of AB, that is, R Is it greater than 0 (if R If the value is between 0 and 1, then point B has crossed the boundary. If the trajectory AB intersects the fence boundary CD, the distance between the intersection and the drone is calculated. If the distance is less than the warning distance, an alert is issued. The warning distance is the drone's flight speed multiplied by the warning time.

[0086] Weather data is crucial for adjusting drone geofencing. Different weather conditions, such as wind speed, direction, temperature, and air pressure, can affect a drone's flight performance and stability. For example, strong winds can cause a drone to deviate from its intended route, while heavy rain can affect its sensor performance. Therefore, adjusting drone geofencing based on weather data can improve the safety and compliance of drone flights.

[0087] like Figure 6 As shown, by installing meteorological sensors on drones, local weather changes can be monitored in real time. The collected meteorological data is analyzed and processed to extract information relevant to the adjustment of the drone's electronic fence. First, the collected meteorological data is cleaned and filtered to remove outliers and erroneous data. For example, wind speed or temperature data that clearly exceeds the acceptable range is marked and excluded to ensure the accuracy of subsequent analysis. Then, the cleaned meteorological data is processed using data analysis algorithms (such as time series analysis and cluster analysis). For example, statistical analysis methods are used to calculate statistical parameters such as the mean and standard deviation of wind speed and direction to understand the stability and changing trends of meteorological conditions. Furthermore, image recognition and pattern recognition techniques can be used to extract key information such as cloud height and precipitation probability from satellite cloud images and weather station data. Finally, the processed data is correlated with the adjustment parameters of the drone's electronic fence. For example, using a drone wind speed and direction measurement and correction algorithm based on an ultrasonic anemometer, wind speed and direction results can be corrected based on the drone's hovering and forward motion. This allows the scope and shape of the electronic fence to be adjusted, ensuring safe flight under varying wind speeds and directions. In thunderstorms, by processing meteorological data collected by weather stations, satellite cloud images, and meteorological sensors, key information such as cloud height and precipitation probability can be extracted to determine no-fly zones and safe distances within the electronic fence. This allows the fence's scope to be expanded or drones to be prohibited from flying in specific areas to avoid the risk of lightning strikes. By establishing this data association, the goal of dynamically adjusting drone electronic fences based on real-time meteorological data can be achieved.

[0088] In summary, the above-mentioned technical solutions of the present invention address the problem of reduced positioning accuracy caused by signal interference and multipath effects in existing technologies. The electronic fence system of the present invention can automatically adjust the size, shape, and position of the fence based on the drone's real-time flight status and environmental changes. This directly enhances the dynamic adjustment capabilities of the electronic fence, ensuring that the drone can always maintain safe flight in complex and changing airspace environments, thereby improving flight safety and stability. Traditional electronic fences define limited areas, typically only simple rectangles or circles. The present invention utilizes point cloud construction, noise reduction, and 3D modeling technology to support the construction of fences of arbitrary shapes and sizes, enabling electronic fences to better adapt to complex and changing airspace environments and improving space utilization and flexibility. To address the complex design of systems integrating multiple energy sources, which require advanced coordination and intelligent control technologies, the present invention utilizes a ray-based cross-border detection algorithm and multi-frequency parameter correlation mining technology to accurately determine drone flight data. This allows ground personnel to monitor the drone's flight status at all times, promptly identify and address potential problems, and thus improve the reliability and response speed of the overall system.

[0089] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for constructing a three-dimensional electronic fence in the air for a drone, characterized in that: The method comprises the following steps: S1. Based on geographic information system and 3D modeling technology, divide the area boundary of the electronic fence within the preset geographical range, calculate the range of the electronic fence, and set the fence parameters of the electronic fence; S2. Integrate the configured electronic fence into the drone system, establish a real-time communication and data exchange channel with the drone, receive real-time feedback on the drone's location and flight status during flight, and dynamically adjust the electronic fence's area boundaries and fence parameters based on flight requirements; S3: Monitor the flight status of the drone and the boundary of the electronic fence in real time. When a drone is found to be crossing the boundary, the early warning mechanism is triggered to identify the dangerous state of the drone and output corresponding control measures.

2. The method for constructing a three-dimensional electronic fence for a drone according to claim 1, characterized in that: The method of dividing the area boundary of the electronic fence within a preset geographical range, calculating the range of the electronic fence, and setting the fence parameters of the electronic fence based on the geographic information system and three-dimensional modeling technology includes the following steps: S11, selecting a target area within a preset geographical range, collecting three-dimensional spatial data of the target area using a laser radar carried by a drone, and generating a three-dimensional model of the target area through point cloud construction and spatial coordinate system conversion; S12. Based on the satellite positioning system, the flight position of the drone is monitored in real time. In combination with wireless signal transmitters and receivers deployed on the ground, wireless positioning technology is used to capture the location information of the drone during flight. S13. Set a preset distance according to actual needs, divide the three-dimensional model using the preset distance to obtain a division result, and perform calculation based on the division result to obtain the electronic fence range and determine the area boundary of the electronic fence.

3. The method for constructing a three-dimensional electronic fence for a drone according to claim 2, characterized in that: The method of selecting a target area within a preset geographical range, collecting three-dimensional spatial data of the target area using a laser radar carried by a drone, and generating a three-dimensional model of the target area through point cloud construction and spatial coordinate system conversion includes the following steps: S111, using a laser radar carried by the drone to transmit laser pulses to the target area, and obtaining distance information of the target area by receiving the transmitted signals, until the drone completely scans the target area, thereby obtaining three-dimensional spatial data of the target area; S112. Based on internal and external parameters of the laser radar, the discrete points in the three-dimensional spatial data are converted into a unified geographic coordinate system to form a point cloud of the target area; S113. Obtain the position coordinates, attitude angle, and distance and scanning angle of each laser point of the laser radar installed on the drone, calculate the coordinate data of each laser point in the geographic coordinate system through the spatial coordinate conversion formula, and denoise the coordinate data. Use the denoised coordinate data to construct a three-dimensional model of the target area.

4. The method for constructing a three-dimensional electronic fence for a drone according to claim 3, characterized in that: The electronic fence range includes the blue warning area and the red warning area; The calculation formula for the blue warning zone is: ； Where, This is the blue warning area; is the rate coefficient; V is the current speed of the drone; T The estimated time from the discovery of a potential risk to the possibility of the danger occurring; is the reference distance; is the coefficient related to the degree of meteorological influence; W is the wind speed; is the angle between the wind direction and the flight direction of the drone; is the environmental interference coefficient; E is the environmental interference intensity; The calculation formula for the red warning area is: ； Where, This is the red alert area; The reaction time of the drone; k is a safety factor greater than or equal to 1; The maximum distance the drone may continue to move if there is a delay in the control signal.

5. The method for constructing a three-dimensional electronic fence for a drone in the air according to claim 1, characterized in that: The steps of integrating the configured electronic fence into the drone system, establishing a real-time communication and data exchange channel with the drone, receiving real-time position information and flight status data fed back by the drone during flight, and dynamically adjusting the area boundary and fence parameters of the electronic fence according to flight requirements include the following: S21. Integrate multiple types of perception sensors into the drone to collect environmental data and flight status data during flight. Based on real-time monitoring of the drone's flight status and environmental changes, predict the drone's future flight trajectory and automatically adjust the fence parameters of the electronic fence to maintain the drone in a safe area. S22. Spectrum analysis chips are built into the drone and ground station. They continuously scan the communication frequency band to obtain the energy distribution within the frequency band. When abnormal signal fluctuations or interference signals are detected, the communication parameters are adjusted and the communication frequency is adjusted through the frequency synthesizer to maintain communication stability between the drone and the ground station. S23. Acquire meteorological data of the target area in real time, process and analyze the meteorological data, associate it with the fence parameters of the electronic fence, and adjust the fence parameters based on the meteorological data and the association results.

6. The method for constructing a three-dimensional electronic fence for a drone in the air according to claim 5, characterized in that: The method of monitoring the real-time flight status of the drone and environmental changes in real time, predicting the future flight trajectory of the drone, and automatically adjusting the fence parameters of the electronic fence to maintain the drone in a safe area includes the following steps: S211, sharing the location information and real-time flight status of each drone with the drone swarm, transmitting control instructions and flight intentions of different drones in the drone swarm. When the drone swarm performs a collaborative mission, the leader drone sends mission instructions and path planning information to other drones; S212, continuously monitoring the location information and real-time flight status of the UAV, recording the flight trajectory of the UAV at equal time intervals to obtain continuous trajectory points to display the position coordinates of the UAV in the three-dimensional model at each moment; and predicting the UAV's location information at the next moment based on the location information corresponding to the historical trajectory points of the UAV flight; S213. When the predicted result of the drone's position information at the next moment exceeds the range of the electronic fence, the fence parameters of the electronic fence are automatically adjusted to adapt to the flight changes of the drone.

7. The method for constructing a three-dimensional electronic fence for a drone according to claim 5, characterized in that: The real-time acquisition of meteorological data of the target area, associating the meteorological data with the fence parameters of the electronic fence by processing and analyzing the meteorological data, and adjusting the fence parameters based on the meteorological data and the association result includes the following steps: S231, cleaning and screening the collected meteorological data, eliminating outliers and erroneous data, analyzing and processing the cleaned and screened meteorological data using a data analysis algorithm, and extracting the changing trend of the meteorological data; S232: Associating the analyzed and processed meteorological data with the fence parameters of the electronic fence, and adjusting the corresponding fence parameters according to the numerical changes of specific data in the meteorological data.

8. The method for constructing a three-dimensional electronic fence for a drone in the air according to claim 1, characterized in that: The real-time monitoring of the flight status of the drone and the boundary of the electronic fence area, triggering the early warning mechanism when the drone is found to have crossed the boundary, identifying the dangerous state of the drone, and outputting corresponding control measures includes the following steps: S31. Obtain operating parameters of each working module of the drone and the drone swarm, calculate the free space path loss value and multi-frequency correlation value of each working module, and determine the relative distance between the drone and the boundary of the electronic fence area by mining the potential correlation between the operating parameters; S32. Compare the real-time location information of the drone with the preset electronic fence area boundary, and combine it with the cross-border detection algorithm based on the ray method to determine whether the drone has crossed the boundary. If there is cross-border behavior, the early warning mechanism is triggered, marking the drone in a dangerous state, and outputting control measures to implement anti-intrusion.

9. The method for constructing a three-dimensional electronic fence for a drone according to claim 8, characterized in that: The free space path loss value is calculated as follows: ； Where, is the free space path loss value; d is the distance to be calculated; is the wavelength value of each working module; The calculation formula of the multi-frequency correlation value is: ； Where, is the multi-frequency correlation value; is the reference frequency; f is the operating frequency of the drone.

10. A system for constructing a three-dimensional electronic fence in the air of a drone, for implementing the method for constructing a three-dimensional electronic fence in the air of a drone according to any one of claims 1 to 9, characterized in that: The system includes: The electronic fence calculation module is used to divide the area boundary of the electronic fence within a preset geographical range, calculate the electronic fence range, and set the fence parameters of the electronic fence based on the geographic information system and three-dimensional modeling technology; The electronic fence configuration module is used to integrate the configured electronic fence into the drone system, establish a real-time communication and data exchange channel with the drone, receive real-time feedback on the drone's position information and flight status data during flight, and dynamically adjust the area boundaries and fence parameters of the electronic fence according to flight requirements; The electronic fence monitoring module is used to monitor the flight status of the drone and the area boundary of the electronic fence in real time. When a drone is found to be crossing the boundary, the early warning mechanism is triggered, the dangerous state of the drone is identified, and corresponding control measures are output.

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