Atmosphere three-dimensional in-situ detection method and system based on unmanned aerial vehicle swarm

Abstract

The atmospheric three-dimensional in-situ detection method based on the unmanned aerial vehicle swarm comprises the following steps: deploying at least one ground central station and a plurality of unmanned aerial vehicle control stations in a target area; releasing the detection unmanned aerial vehicle by using the unmanned aerial vehicle control station, and building an unmanned aerial vehicle swarm after the detection unmanned aerial vehicle lifts off; after rising to the detection height, the unmanned aerial vehicle swarm hovers; within the hovering duration threshold value, the detection unmanned aerial vehicle utilizes a carried atmosphere detection device to detect atmosphere data and sends the atmosphere data to the corresponding unmanned aerial vehicle control station; and after the unmanned aerial vehicle swarm completes detection at all detection heights, the detection unmanned aerial vehicle returns to the unmanned aerial vehicle control station. According to the atmospheric three-dimensional in-situ detection method and system based on the unmanned aerial vehicle swarm, three-dimensional in-situ detection of basic meteorological elements of an atmospheric boundary layer of a target area can be realized, and the requirements of more accurate weather forecast, air quality forecast and low-altitude economic activity development are met.

Description

Technical Field

[0001] The present invention relates to the technical field of in-situ atmospheric detection, and specifically to an in-situ three-dimensional atmospheric detection method and system based on a drone swarm. Background Art

[0002] The atmospheric boundary layer refers to the atmosphere close to the ground and significantly affected by the ground. Its thickness generally ranges from 500 to 2000 m and varies greatly with weather processes, terrain, seasons, and day and night. The vertical distribution of the basic meteorological elements (temperature, pressure, humidity, wind speed, and wind direction) in the atmospheric boundary layer directly reflects the weather situation and is also the main factor controlling the diffusion ability of air pollutants. In addition, the atmospheric boundary layer is also the space field for developing low-altitude economy. Therefore, obtaining the meteorological conditions and accurate forecasting of the atmospheric boundary layer are indispensable for ensuring low-altitude activities.

[0003] Currently, the in-situ detection data of the atmospheric boundary layer mainly come from balloon radiosondes. However, the number of existing radiosonde stations is very limited, and the covered area is also very limited. Moreover, most radiosonde stations release balloons twice a day, that is, only two meteorological element profiles can be obtained every day. In this way, the spatio-temporal coverage rate of radiosonde observations is far from sufficient to reflect the real-time changes of the atmospheric boundary layer, especially when small and medium-scale severe convective weather occurs.

[0004] In addition to balloon radiosondes, with the gradual development of remote sensing detection technology, remote sensing detection technology has also been gradually applied to the atmospheric detection process. Remote sensing detection technology based on ground-based microwave wind profilers, microwave radiometers, lidar, and other equipment has an advantage in time resolution, and remote sensing technology based on satellites has an advantage in spatial coverage rate. However, the data provided by both types of technologies have the problem of strong uncertainty, especially in cloudy and rainy weather, no useful data can be provided. Summary of the Invention

[0005] In order to solve the deficiencies in the prior art, the present invention provides an in-situ three-dimensional atmospheric detection method and system based on a drone swarm, which can perform in-situ three-dimensional detection of the basic meteorological elements of the atmospheric boundary layer in the target area, meeting the needs of more accurate weather forecasting, air quality forecasting, and the development of low-altitude economic activities.

[0006] In order to achieve the above object, the specific solution adopted by the present invention is as follows: The in-situ three-dimensional atmospheric detection method based on a drone swarm includes the following steps: Deploy at least one ground central station and multiple drone control stations in the target area; Use the drone control stations to release detection drones, and after the detection drones take off, form a drone swarm; The drone swarm hovers after rising to the detection altitude; Within the hover duration threshold, the detection UAV uses the on-board atmospheric detection device to detect atmospheric data and sends the atmospheric data to the corresponding UAV control station; When the UAV swarm completes detection at all detection altitudes, the detection UAV returns to the UAV control station.

[0007] As a further optimization of the above atmospheric three-dimensional in-situ detection method based on UAV swarms: The method of deploying at least one ground central station and multiple UAV control stations in the target area includes: Determine the area of the target area; Determine the number of ground central stations and UAV control stations according to the area; Determine the optional location range of the ground central station according to the airspace conditions of the target area; Determine the best location of the central station within the optional location range according to the power supply conditions of the target area; Taking the best location of the central station as the center, determine the best locations of multiple control stations; Deploy the ground central station to the best location of the central station correspondingly, and deploy the UAV control station to the best location of the control station correspondingly; establish a central station communication network and a control station communication network. The central station communication network covers all ground central stations, and the control station communication network covers multiple UAV control stations and at least one ground central station.

[0008] As a further optimization of the above atmospheric three-dimensional in-situ detection method based on UAV swarms: After determining the best location of the central station and the best locations of the control stations, determine multiple alternative locations of the control stations according to the historical climate data of the target area, and the alternative locations of the control stations are close to at least one best location of the central station.

[0009] As a further optimization of the above atmospheric three-dimensional in-situ detection method based on UAV swarms: After determining the best location of the central station, the best locations of the control stations and the alternative locations of the control stations, obtain the altitude data of the best location of the central station, the best locations of the control stations and the alternative locations of the control stations, and generate a take-off time rule and a lift-off speed rule according to the altitude data.

[0010] As a further optimization of the above atmospheric three-dimensional in-situ detection method based on UAV swarms: The method of using the UAV control station to release the detection UAV includes: Determine the detection moment; Generate a release moment corresponding to the UAV control station according to the detection moment and the take-off time rule; After reaching the release moment, the UAV control station releases the detection UAV according to the lift-off speed rule.

[0011] As a further optimization of the above-mentioned atmospheric three-dimensional in-situ detection method based on a drone swarm: The method for forming a drone swarm after the detection drones take off includes: After the detection drones take off, their real-time altitude is determined in cooperation with the drone control station before reaching the detection altitude; The drone control station transmits the real-time altitude of the detection drones to the ground central station, and the ground central station exchanges all the obtained real-time altitudes; One of the ground central stations determines the real-time detection plane based on all the real-time altitudes; If the altitude difference between a detection drone and the real-time detection plane exceeds a preset altitude difference threshold, the central station generates altitude adjustment data and transmits it to the drone control station corresponding to the detection drone; After receiving the altitude adjustment data, the drone control station sends the altitude adjustment data to the detection drone; After receiving the altitude adjustment data, the detection drone changes its real-time altitude according to the altitude adjustment data; All the detection drones form a drone swarm.

[0012] As a further optimization of the above-mentioned atmospheric three-dimensional in-situ detection method based on a drone swarm: During the ascent of the drone swarm, the detection drones periodically collect the current wind speed. If at least two consecutive current wind speeds exceed a preset wind speed threshold, the detection drone descends and returns to the drone control station.

[0013] As a further optimization of the above-mentioned atmospheric three-dimensional in-situ detection method based on a drone swarm: Among all the detection altitudes, in the order from low to high, the distance between two adjacent detection altitudes gradually increases.

[0014] An atmospheric three-dimensional in-situ detection system based on a drone swarm, used to implement the above-mentioned atmospheric three-dimensional in-situ detection method based on a drone swarm. The system includes: At least one ground central station, used to issue detection control instructions and receive atmospheric data; Multiple drone control stations, used to release and receive detection drones; Multiple detection drones, which are correspondingly arranged at the drone control stations. The detection drones are equipped with atmospheric detection devices for detecting atmospheric data.

[0015] As a further optimization of the above-mentioned atmospheric three-dimensional in-situ detection system based on a drone swarm: The atmospheric detection device includes a temperature acquisition module, a humidity acquisition module, a pressure acquisition module, and a wind speed acquisition module.

[0016] Beneficial effects: Based on the drone swarm technology, this invention loads multi-factor meteorological detection sensors and real-time data transmission devices on multiple drones. After deployment in the target area, they take off for detection quasi-synchronously multiple times a day, achieving three-dimensional in-situ detection of the basic meteorological elements in the atmospheric boundary layer of the target area, meeting the needs of more accurate weather forecasting, air quality forecasting, and the development of low-altitude economic activities. Brief Description of the Drawings

[0017] Figure 1 It is a schematic diagram of the state after the detection drones form a drone swarm. Figure 2 It is a schematic diagram of the lifting process of the detection drone. Figure 3 It is a schematic diagram of the structure of the detection drone.

[0018] Brief Description of the Drawings: 1 - Landing support frame, 2 - Airframe, 3 - Rotor, 4 - Atmospheric detection device, 5 - Data acquisition module, 6 - Positioning module antenna, 7 - Flight control module, 8 - Energy storage module, 9 - Wireless communication module. Detailed Embodiment

[0019] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0020] As Figure 1 and 2 shown, the present invention first provides an atmospheric three-dimensional in-situ detection method based on a drone swarm, including S1 to S5.

[0021] S1. Deploy at least one ground central station and multiple drone control stations in the target area. Among them, the ground central station is mainly used for collecting, processing, analyzing, and distributing data, and the drone control station is used to control the takeoff and landing of the detection drones, charge the detection drones, and send the data detected by the detection drones to the ground central station. The method of deploying at least one ground central station and multiple drone control stations in the target area includes S11 to S8.

[0022] S11. Determine the area of the target area.

[0023] S12. Determine the number of ground central stations and UAV control stations according to the area of the region. Specifically, the larger the area of the target region, the more ground central stations are required to ensure that the ground central stations can successfully process the atmospheric data in the target region. In actual implementation, the target region can be equivalent to a regular geometric shape, and then the number of ground central stations can be determined according to the area of this geometric shape. For example, in an embodiment of the present invention, the target region can be equivalent to a square, and when the boundary size does not exceed 50 km × 50 km, only one ground central station is set. When the boundary size exceeds 50 km × 50 km, the number of ground central stations is increased. In another embodiment of the present invention, the target region can be equivalent to a circle, and when the diameter does not exceed 50 km, only one ground central station is set. When the diameter exceeds 50 km, the number of ground central stations is increased. After the number of ground central stations is determined, since the data processing capacity of the ground central stations is limited and the number of UAV control stations that each ground central station can connect to is also limited, it is necessary to determine the appropriate number of UAV control stations based on the number of ground central stations to ensure that the number of UAV control stations connected to each ground central station does not exceed its maximum load.

[0024] S13. Determine the optional location range of the ground central station according to the airspace conditions of the target region. To improve the safety of UAVs and the control accuracy of UAVs, it is necessary to enable UAVs to avoid obstacles in the upper air during flight, especially obstacles such as high-voltage transmission lines that can directly cause UAV failures. Therefore, it is necessary to determine the range where the ground central station can be deployed in the target region according to the airspace conditions of the target region, that is, the optional location range. In addition to the airspace conditions, the geographical situation in the target region can also be considered, especially the flatness of the ground, and a relatively open and flat location is selected to deploy the ground central station.

[0025] S14. Determine the best location of the central station in the optional location range according to the power supply conditions of the target region. In S13, the optional location range of the ground central station is determined based on factors such as the airspace conditions of the target region and the flatness of the ground surface. However, in the optional location range, the ground central station cannot be deployed arbitrarily because the ground central station needs to have stable power supply and communication conditions to successfully complete functions such as data processing and distribution. Therefore, after determining the optional location range, it is necessary to determine the location where the ground central station can be deployed again according to the power supply conditions of the target region, that is, the best location of the central station. The finally determined best location of the central station needs to have stable power supply and be able to communicate through wired and wireless methods.

[0026] S15. With the optimal position of the central station as the center, determine the optimal positions of multiple control stations. Since the UAV control station needs to interact with the ground central station to achieve data transmission, a stable connection condition is also required between the UAV control station and the ground central station. Determining the optimal positions of the control stations with the optimal position of the central station as the center can enable the UAV control stations to be distributed around the ground central station, and each UAV control station can be connected to at least one ground central station, thus ensuring that the UAV control station can successfully send data to the ground central station. When the UAV control station is connected to at least two ground central stations simultaneously, if the connection with a certain ground central station is disconnected, the UAV control station can still send data to the remaining ground central stations, thus fully ensuring that the UAV control station can upload the data detected by the detection UAV and avoiding data loss.

[0027] S16. Deploy the ground central station to the optimal position of the central station correspondingly, and deploy the UAV control station to the optimal position of the control station correspondingly.

[0028] S17. After determining the optimal positions of the central station and the control stations, determine multiple alternative positions of the control stations according to the historical climate data of the target area, and the alternative positions of the control stations are close to at least one optimal position of the central station. Considering that the climate characteristics of different target areas are different, and there may be frequent and drastic weather changes in some seasons, by determining the alternative positions of the control stations, the number of UAV control stations can be increased in a specific season, and correspondingly, the number of detection UAVs is increased. In the period of changeable weather, the scale of atmospheric data can be expanded, so as to more accurately master and predict the weather conditions of the target area.

[0029] S18. Establish a central station communication network and a control station communication network. The central station communication network covers all ground central stations, and the control station communication network covers multiple UAV control stations and at least one ground central station. The deployment form of the control station communication network can be determined based on the communication conditions of the target area, and it is best to use a combination of wired and wireless methods for networking to ensure stable communication.

[0030] Further, after determining the optimal position of the central station, the optimal position of the control station, and the alternative positions of the control station, obtain the altitude data of the optimal position of the central station, the optimal position of the control station, and the alternative positions of the control station, and generate a takeoff time rule and a lifting speed rule according to the altitude data. In the target area, different positions will have different altitudes. During the detection process of the detection UAVs, they need to hover at the same height, which results in different distances that different detection UAVs need to travel to reach the same height. Therefore, it is necessary to control the takeoff of the detection UAVs according to the altitude data to ensure that all detection UAVs can rise to the same height for high-precision detection. Specifically, the takeoff process of the detection UAVs can be controlled in two ways. The first way is to control the takeoff time of the detection UAVs. The detection UAVs corresponding to the UAV control stations with lower altitudes take off earlier than the detection UAVs corresponding to the UAV control stations with higher altitudes. The second way is to control the rising speed of the detection UAVs. The speed of the detection UAVs corresponding to the UAV control stations with lower altitudes is higher than the speed of the detection UAVs corresponding to the UAV control stations with higher altitudes.

[0031] S2. Release the detection UAVs using the UAV control station. After the detection UAVs take off, form a UAV swarm.

[0032] The method of releasing the detection UAVs using the UAV control station includes S201 to S210.

[0033] S201. Determine the detection time. The detection time is determined based on the actual detection requirements. Multiple detection times can be determined in a day. For example, 2 o'clock, 8 o'clock, 14 o'clock, and 20 o'clock are determined as the detection times. Further, before reaching the detection time, the detection UAVs perform self-checks. The self-check content includes whether the current meteorological conditions meet the non-conditional requirements, the current battery power, and the health status of each module, etc. The specific self-check method belongs to the conventional function of the UAV and will not be elaborated here.

[0034] S202. Generate the release time corresponding to the UAV control station according to the detection time and the takeoff time rule. As described above, in order to ensure that all detection UAVs can reach the same detection height for detection, it is necessary to determine the takeoff time rule according to the altitude of the UAV control station. After determining the detection time, based on the takeoff time rule and the detection time, the independent release time corresponding to the detection UAV can be obtained. For example, if the altitude of a certain UAV control station is relatively low and the corresponding detection UAV needs to take off earlier, then under the condition that the detection time is 2 o'clock, its release time can be 1:58. If the altitude of a certain UAV control station is relatively high and the corresponding detection UAV needs to take off later, then its release time can be 2:02.

[0035] S203. After reaching the release moment, the UAV control station releases the detection UAV according to the liftoff speed rule. Although taking off the detection UAVs at different release moments can enable all detection UAVs to reach the same detection altitude for detection, in actual situations, there may be different wind speeds and other factors at different positions in the target area that affect the flight of the UAVs. At this time, combined with the liftoff speed rule, it can further ensure that all detection UAVs can smoothly reach the same detection altitude for detection.

[0036] The method for the detection UAVs to form a UAV swarm after liftoff includes S204 to S210.

[0037] S204. After the detection UAV takes off and before reaching the detection altitude, it cooperates with the UAV control station to determine its real-time altitude. The real-time altitude can be determined based on the altitude sensor carried by the detection UAV itself, or based on the altitude of the UAV control station, the flight speed and flight duration of the detection UAV. It is also possible to use the results determined by the two methods for mutual verification to obtain a more accurate real-time altitude.

[0038] S205. The UAV control station transmits the real-time altitude of the detection UAV to the ground central station, and the ground central station exchanges all the real-time altitudes obtained.

[0039] S206. One of the ground central stations determines the real-time detection plane based on all the real-time altitudes.

[0040] S207. If the height difference between a detection UAV and the real-time detection plane exceeds a preset height difference threshold, the central station generates height adjustment data and transmits it to the UAV control station corresponding to the detection UAV.

[0041] S208. After receiving the height adjustment data, the UAV control station sends the height adjustment data to the detection UAV.

[0042] S209. After receiving the height adjustment data, the detection UAV changes its real-time altitude according to the height adjustment data.

[0043] S210. All detection UAVs form a UAV swarm.

[0044] Because the ground central station has stronger data processing capabilities and more stable communication conditions, the real-time altitudes of all detection drones are aggregated to the ground central station. The ground central station determines whether the detection drones are at the same altitude based on all the real-time altitudes. If the deviation degree of some detection drones is too high, corresponding altitude adjustment data is generated to precisely control the detection drones, ultimately ensuring that all detection drones can hover at the same detection altitude for detection. Further, after receiving all the real-time altitudes, the ground central station can determine the real-time detection plane through plane fitting. The specific plane fitting method belongs to conventional technology and will not be elaborated here.

[0045] Further, to ensure the safety of the detection drones and the accuracy of the atmospheric data, during the ascent of the drone swarm, the detection drones periodically collect the current wind speed. If at least two consecutive current wind speeds exceed the preset wind speed threshold, the detection drones descend and return to the drone control station. If the current wind speed continuously exceeds the wind speed threshold, the drone may malfunction or even crash. At this time, making the drone return to the drone control station can avoid losses caused by the drone getting out of control. After the drone returns to the drone control station, this detection can be ended, or detection can be restarted after a certain delay.

[0046] S3. The drone swarm hovers after ascending to the detection altitude. Among all the detection altitudes, the distance between adjacent two detection altitudes gradually increases in the order from low to high. All the detection altitudes can be determined based on the actual detection needs and the flight restriction altitude of the target area. For example, in an embodiment of the present invention, the flight restriction altitude is 1500 m, and the detection altitudes can include 10 m, 20 m, 50 m, 100 m, 200 m... 1500 m.

[0047] S4. Within the hovering duration threshold, the detection drones use the carried atmospheric detection device to detect atmospheric data and send the atmospheric data to the corresponding drone control station. Because the detection drones can detect more accurately only in a stable hovering state, after the drone swarm reaches the detection altitude, it needs to hover for a certain time to wait for its own state to stabilize. In an embodiment of the present invention, the duration threshold can be set to 0.5 min. During the detection process, the total hovering duration of the detection drones at each detection altitude is 10 min. If the ascent speed of the detection drone is 3 m / s, the total duration consumed during the ascent to the flight restriction altitude of 1500 m does not exceed 10 min, and the time for the detection drone to return to the drone control station after completing the detection is also 10 min. Therefore, during a single detection process, the total flight duration of the detection drone is within 30 min. The existing drone endurance can meet the requirements, and there is no need to specifically customize new drones, which can reduce costs.

[0048] Furthermore, the atmospheric data detected by the present invention mainly includes particulate matter data, polluted gas data, greenhouse gas data, temperature data, humidity data, and wind force data. Among them, the particulate matter data includes PM2.5 concentration, PM10 concentration, etc.; the polluted gas data includes ozone concentration, nitrogen oxide concentration, sulfur dioxide concentration, carbon monoxide concentration, etc.; and the greenhouse gas data includes carbon dioxide concentration, methane concentration, etc.

[0049] S5. When the drone swarm completes the detection at all detection altitudes, the detection drones return to the drone control station.

[0050] Furthermore, in addition to hovering at the detection altitude for detection, the detection drones also perform detection during the ascent and descent processes. Among the obtained atmospheric data, the atmospheric data obtained by hovering detection has higher accuracy.

[0051] The present invention further provides an atmospheric three-dimensional in-situ detection system based on a drone swarm for implementing the above-mentioned atmospheric three-dimensional in-situ detection method based on a drone swarm. The system includes at least one ground central station, multiple drone control stations, and multiple detection drones.

[0052] At least one ground central station is used to issue detection control instructions and receive atmospheric data.

[0053] Multiple drone control stations are used to release and receive detection drones.

[0054] Multiple detection drones are correspondingly arranged at the drone control stations. The detection drones are equipped with an atmospheric detection device for detecting atmospheric data. The atmospheric detection device includes a temperature acquisition module, a humidity acquisition module, a pressure acquisition module, and a wind speed acquisition module. It should be noted that each module of the atmospheric detection device is a mature existing technology in the art, and its structure and principle will not be elaborated here. Those skilled in the art can flexibly select a suitable model according to actual needs.

[0055] Furthermore, the structure of the detection drone is as Figure 3 shown, mainly including a landing support frame 1, a fuselage 2, a rotor 3, a positioning module antenna 6, a flight control module 7, an energy storage module 8, and a wireless communication module 9. These modules are all conventional structures of drones and will not be elaborated here. Furthermore, the atmospheric detection device 4 is mounted on the fuselage 2 through a bracket, and the atmospheric detection device 4 is higher than the rotor 3 to avoid the airflow generated by the rotor 3 interfering with the detection of wind speed and wind direction.

[0056] The foregoing description of the disclosed embodiments enables those skilled in the art to practice or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An in-situ atmospheric three-dimensional detection method based on a drone swarm, characterized in that The method includes the following steps: Deploy at least one ground central station and multiple drone control stations in the target area; Use the drone control stations to release detection drones. After the detection drones take off, a drone swarm is formed; The drone swarm hovers after rising to the detection altitude; Within the hovering duration threshold, the detection drones use the carried atmospheric detection devices to detect atmospheric data and send the atmospheric data to the corresponding drone control stations; When the drone swarm completes detection at all detection altitudes, the detection drones return to the drone control stations.

2. The method for atmospheric three-dimensional in-situ detection based on a drone swarm according to claim 1, wherein The method for deploying at least one ground central station and multiple drone control stations in the target area includes: Determine the area of the target area; Determine the number of ground central stations and drone control stations according to the area; Determine the optional location range of the ground central station according to the airspace conditions of the target area; Determine the optimal location of the central station within the optional location range according to the power supply conditions of the target area; Taking the optimal location of the central station as the center, determine the optimal locations of multiple control stations; Correspondingly deploy the ground central station to the optimal location of the central station, and correspondingly deploy the drone control stations to the optimal locations of the control stations; establish a central station communication network and a control station communication network. The central station communication network covers all ground central stations, and the control station communication network covers multiple drone control stations and at least one ground central station.

3. The method for in-situ atmospheric three-dimensional detection based on a drone swarm according to claim 2, wherein, After determining the optimal location of the central station and the optimal locations of the control stations, determine multiple alternative locations of the control stations according to the historical climate data of the target area, and the alternative locations of the control stations are close to at least one optimal location of the central station.

4. The method for in-situ atmospheric three-dimensional detection based on a drone swarm according to claim 3, wherein, After determining the optimal location of the central station, the optimal locations of the control stations, and the alternative locations of the control stations, obtain the altitude data of the optimal location of the central station, the optimal locations of the control stations, and the alternative locations of the control stations, and generate a takeoff time rule and a rising speed rule according to the altitude data.

5. The method for in-situ atmospheric three-dimensional detection based on a drone swarm according to claim 4, wherein, The method for using the drone control stations to release detection drones includes: Determine the detection moment; Generate a release moment corresponding to the drone control station according to the detection moment and the takeoff time rule; After reaching the release moment, the drone control station releases the detection drone according to the rising speed rule.

6. The atmospheric three-dimensional in-situ detection method based on an unmanned aerial vehicle (UAV) swarm according to claim 1, wherein The method for forming a drone swarm after the detection drones take off includes: After the detection drones take off, cooperate with the drone control stations to determine their real-time altitude before reaching the detection altitude; The drone control stations transmit the real-time altitude of the detection drones to the ground central station, and the ground central station exchanges all the obtained real-time altitudes; One of the ground central stations determines the real-time detection plane based on all the real-time altitudes; If the altitude difference between a detection drone and the real-time detection plane exceeds the preset altitude difference threshold, the central station generates altitude adjustment data and transmits it to the drone control station corresponding to the detection drone; After receiving the altitude adjustment data, the drone control station sends the altitude adjustment data to the detection drone; After receiving the altitude adjustment data, the detection drone changes its real-time altitude according to the altitude adjustment data; All the detection drones form a drone swarm.

7. The method for atmospheric three-dimensional in-situ detection based on an unmanned aerial vehicle (UAV) swarm according to claim 1, wherein During the ascent of the UAV swarm, the detection UAV periodically collects the current wind speed. If at least two consecutive current wind speeds exceed the preset wind speed threshold, the detection UAV descends and returns to the UAV control station.

8. The method for in-situ atmospheric three-dimensional detection based on a drone swarm according to claim 1, characterized in that Among all detection altitudes, in ascending order from low to high, the distance between adjacent two detection altitudes gradually increases.

9. An atmospheric three-dimensional in-situ detection system based on a drone swarm, characterized in that, A system for implementing the atmospheric three-dimensional in-situ detection method based on UAV swarm according to any one of claims 1-8, the system comprising: At least one ground central station, configured to issue detection control instructions and receive atmospheric data; Multiple UAV control stations, configured to release and receive detection UAVs; Multiple detection UAVs, which are correspondingly arranged at the UAV control stations, and the detection UAVs are equipped with atmospheric detection devices for detecting atmospheric data.

10. The atmospheric three-dimensional in-situ detection system based on the drone swarm according to claim 9, characterized in that, The atmospheric detection device includes a temperature acquisition module, a humidity acquisition module, a pressure acquisition module and a wind speed acquisition module.

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