UAV General Weather Payload

Abstract

This invention discloses a universal meteorological payload for unmanned aerial vehicles (UAVs). The payload includes a frame, a support tube, a shell, wind direction and speed sensors, temperature and humidity sensors, a barometric pressure sensor, and a visibility sensor. The meteorological sensors are mounted on the top of the shell, which is elevated by the support tube, to avoid interference from the UAV rotor downwash airflow; the visibility sensor is located at the bottom of the frame. The shell houses a data acquisition unit, a BeiDou module, and a memory. The data acquisition unit connects to each sensor via a digital interface, stores the processed meteorological data locally, and transmits it remotely via the BeiDou module. This payload has a compact structure, effectively solving the problems of multi-sensor integration and airflow interference. It can accurately acquire meteorological data for six elements: wind direction, wind speed, temperature, humidity, pressure, and visibility. It is suitable for many fields such as meteorological observation and research, environmental protection, agriculture, forestry, animal husbandry and fisheries, emergency rescue, urban management, and aviation safety.

Description

Technical Field

[0001] This invention relates to the field of meteorological monitoring equipment technology, specifically to a general meteorological payload for unmanned aerial vehicles (UAVs). Background Technology

[0002] Currently, in the field of meteorological observation, traditional ground-based fixed meteorological stations have limited coverage and struggle to obtain detailed, real-time meteorological data for specific areas (such as disaster sites or complex terrain). Unmanned aerial vehicle (UAV) platforms, with their mobility and flexibility, have become ideal carriers for carrying meteorological sensors for close-range observation.

[0003] However, existing drone weather payloads have significant technical problems in integration and layout: First, when a rotor drone is in flight, its rotor will generate a strong downwash airflow. When weather sensors (especially wind direction and speed sensors) are too close to the rotor, this airflow will seriously interfere with the measurement data, resulting in data distortion.

[0004] Secondly, UAV platforms have strict limitations on the size and weight of their payloads, while meteorological observations often require the integration of multiple sensors (such as temperature, humidity, air pressure, wind speed and direction, and visibility). Integrating multiple sensors, especially the typically large visibility sensors, densely into a small space is difficult.

[0005] Therefore, there is an urgent need for a specially designed drone weather payload whose structural layout must be able to effectively avoid interference from the drone's own airflow, while also solving the problem of integration and mutual interference of multiple sensors (especially visibility sensors) in a compact space. Summary of the Invention

[0006] The purpose of this invention is to provide a compact, multi-parameter, general-purpose meteorological payload system specifically designed for rotary-wing unmanned aerial vehicles (UAVs), capable of accurately, reliably, and in real-time measuring wind direction, wind speed, temperature, humidity, air pressure, and atmospheric visibility.

[0007] To achieve the above objectives, the present invention proposes the following technical solution: a general-purpose meteorological payload for unmanned aerial vehicles (UAVs), comprising:

[0008] Mounting plate, the bottom of which is fixedly connected to the top of the frame, a support tube is fixedly connected to the mounting plate, and a housing is fixedly connected to the top of the support tube;

[0009] The wind direction and speed sensor, temperature and humidity sensor, and air pressure sensor are used to collect basic environmental meteorological elements, while the wind direction and speed sensor is used to measure wind speed and wind direction data. The wind direction and speed sensor, temperature and humidity sensor, and air pressure sensor are arranged sequentially from top to bottom on the top of the housing.

[0010] A visibility sensor, used to measure atmospheric visibility, is mounted at the bottom of the frame.

[0011] Preferably, the housing is equipped with a data acquisition unit, a BeiDou module, and a memory;

[0012] The data acquisition unit includes a first digital acquisition interface, and the wind direction and speed sensor, temperature and humidity sensor and air pressure sensor are all connected to the data acquisition unit through the first digital acquisition interface.

[0013] The first digital acquisition interface is an I2C interface or a UART interface;

[0014] The data acquisition unit includes a second digital acquisition interface; the visibility measurement unit is connected to the data acquisition unit through the second digital acquisition interface, which is an RS485 interface.

[0015] The data acquisition unit is electrically connected to the memory, which is used to locally store the collected meteorological data and equipment status information.

[0016] Preferably, the data acquisition unit is further provided with a wired external interface, which includes an RS-232 interface or an RS-485 interface, for connecting the load to an external PC terminal;

[0017] The Beidou module is electrically connected to the data acquisition unit and is used to remotely transmit measurement data to the terminal via satellite communication.

[0018] It also includes a lithium battery and a power management unit, with the lithium battery housed inside the casing; the lithium battery supplies power to the data acquisition unit and each power-consuming unit of the meteorological payload through the power management unit.

[0019] Preferably, it also includes a magnetic north measurement unit, which is electrically connected to the data acquisition unit and is used to measure the orientation data of the load in real time and to perform magnetic north correction on the wind direction data measured by the wind direction and wind speed sensor.

[0020] Preferably, the wind direction and speed sensor includes two pairs of orthogonally mounted pitot tubes and two differential pressure sensors; the two pairs of pitot tubes are orthogonally mounted in pairs on a cross-shaped bracket, forming two measuring axes, the X-axis and the Y-axis; on each measuring axis, the total pressure end of the pitot tube in the positive direction and the total pressure end of the pitot tube in the negative direction are respectively connected to the two ends of the corresponding differential pressure sensor, so as to measure the pressure difference ΔP in the X-axis direction in a differential manner. X Pressure difference ΔP in the Y-axis direction Y .

[0021] Preferably, the data acquisition unit uses the ΔP measured by the differential pressure sensor. X and ΔP Y Based on the air density ρ, the wind speed components V in the X and Y axes are calculated using Bernoulli's equation. X and V Y The composite wind speed and direction are obtained through vector synthesis; wherein, the air density ρ is obtained by the data acquisition unit based on the air pressure value measured by the air pressure sensor and the temperature and humidity values ​​measured by the temperature and humidity sensor, by calculating the virtual temperature and then correcting it using the ideal gas law.

[0022] Preferably, the visibility sensor includes a forward scattering device and a camera; both the forward scattering device and the camera are mounted at the bottom of the frame; the camera is used to photograph a target placed on the ground, and by analyzing the degradation degree of the images taken at different altitudes, the atmospheric transmittance and extinction coefficient are estimated, and then the visibility value is calculated and fused with the measurement data of the forward scattering device for correction.

[0023] Preferably, the target is a high-contrast target with a black and white checkerboard pattern, wherein the black part is made of a low-reflectivity material; the drone hovers at multiple preset altitudes, the camera takes vertically downward pictures of the target at each hovering altitude, and the data acquisition unit analyzes the images at each altitude using the dual brightness difference method and calculates atmospheric visibility according to Cauchy's law.

[0024] Preferably, the mounting plate is fixed to the frame using a detachable quick-release connection, so that the load can be detached from the UAV and set up independently for use as a mobile weather station for meteorological observation.

[0025] Preferably, the data acquisition unit is configured to process the collected meteorological data according to meteorological observation specifications, including calculating the minute average wind direction and speed, minute average visibility, minute average temperature and humidity, minute average air pressure, and minute maximum wind speed and its corresponding wind direction, and then package the processed meteorological elements and send them through the Beidou module.

[0026] Beneficial effects: The technical solution of this application has the following technical effects:

[0027] 1. Effectively avoiding rotor airflow interference and improving measurement accuracy: This invention elevates the housing and its top components—wind direction and speed sensors, temperature and humidity sensors, and air pressure sensors—by setting up a support tube, placing them significantly above the plane of the UAV frame and rotor. This "high-position" layout removes the aforementioned key sensors (especially the airflow-sensitive wind direction and speed sensors) from the main interference area of ​​the UAV rotor downwash airflow, thereby ensuring the authenticity and accuracy of the collected data on basic meteorological elements such as wind speed, wind direction, temperature, humidity, and air pressure.

[0028] 2. Achieving Efficient Integration and Interference-Resistant Layout of Visibility Sensors: This invention employs an innovative "top-bottom separation" spatial layout. Addressing the typically large size of visibility sensors, they are positioned at the bottom of the frame. This design not only fully utilizes the space beneath the UAV frame, solving the integration challenge of large sensors on a compact payload, but also physically isolates them from other sensors located at the top of the housing. This separation layout effectively avoids thermal or electromagnetic interference that may arise from dense integration of multiple sensors, ensuring the independence and accuracy of each measurement, ultimately achieving precise multi-element measurement, including visibility, on a small UAV payload.

[0029] 3. Standardized quick-release interfaces and unified electrical interface design enable it to quickly and easily adapt to various mainstream quadcopter drone platforms, achieving true "plug and play".

[0030] It should be understood that all combinations of the foregoing concepts and the additional concepts described in more detail below can be considered part of the inventive subject matter of this disclosure, provided that such concepts do not contradict each other.

[0031] The foregoing and other aspects, embodiments, and features of the teachings of the present invention will be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the invention, such as features and / or beneficial effects of exemplary embodiments, will become apparent from the following description or may be learned through practice of specific embodiments according to the teachings of the present invention. Attached Figure Description

[0032] The accompanying drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component shown in the various figures may be denoted by the same reference numeral. For clarity, not every component is labeled in each figure. Embodiments of various aspects of the invention will now be described by way of example and with reference to the accompanying drawings, wherein:

[0033] Figure 1 This is a schematic diagram of the structure of the present invention;

[0034] Figure 2 A schematic diagram of a general meteorological payload architecture for unmanned aerial vehicles (UAVs);

[0035] Figure 3 This is a diagram illustrating the relationship between internal and external interfaces.

[0036] Figure 4 An artist's rendering of a pitot tube installed on a drone.

[0037] The meanings of the labels in the figure are as follows: 1. Wind direction and speed sensor; 2. Temperature and humidity sensor; 3. Barometric pressure sensor; 4. Visibility sensor; 5. UAV; 6. Support tube; 7. Frame; 8. Housing; 9. Mounting plate; 10. Pitot tube. Detailed Implementation

[0038] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings to clearly illustrate the structure, purpose, advantages, positional relationship, and connection method of each component. It should be noted that the directional indications (such as "front," "rear," "up," and "down") involved in this embodiment are based on the posture shown in the drawings and are only used to describe the relative positional relationship and movement of the components. If the posture changes, the directional indications will be adjusted accordingly. The term "connection" includes mechanical connections and electrical connections, and can be fixed connections, detachable connections, or indirect connections through an intermediate medium. The specific meaning will be understood by those skilled in the art based on the context.

[0039] Implementation, for example Figure 1-3 As shown, in this embodiment, the general-purpose meteorological payload is mounted on a drone 5. The drone 5 includes a frame 7, on which the meteorological measurement components of the payload are mounted. The frame 7 is the base of the entire payload, and a mounting plate 9 is bolted to its top. This design allows the entire payload to function as an independent module, facilitating assembly and disassembly and providing excellent versatility.

[0040] To minimize interference from the strong downwash airflow generated by the UAV rotor on the meteorological sensors, this embodiment employs a specific spatial layout. A support tube 6 is fixedly connected to the mounting plate 9, and a housing 8 for accommodating core electronic components is fixedly connected to the top of the support tube 6. From top to bottom, the top of the housing 8 houses a wind direction and speed sensor 1, a temperature and humidity sensor 2, and a barometric pressure sensor 3. These airflow-sensitive sensors are significantly elevated via the support tube 6, especially the wind direction and speed sensor 1, keeping it away from the main influence zone of the UAV body and rotor airflow, thereby ensuring the accuracy of data collection for basic environmental meteorological elements such as wind direction, wind speed, temperature, humidity, and barometric pressure.

[0041] The wind speed, wind direction, and temperature / humidity sensors utilize the SW600 module from Siwei Hi-Tech, featuring a lightweight improvement, high integration, and small size. The barometric pressure module has also been miniaturized. The visibility sensor uses the ASHUR-VD920g sensor, resulting in a total weight of only 0.5kg, significantly reducing weight compared to traditional visibility sensors. The visibility sensor's placement at the bottom of the drone optimizes the aircraft's center of gravity, facilitating attitude adjustments.

[0042] For atmospheric visibility, a critical meteorological element for which sensors are typically bulky, this embodiment cleverly places the visibility sensor 4 at the bottom of the frame 7, where it is mounted and fixed. This arrangement makes full use of the space beneath the UAV, without affecting the layout of other sensors, and provides the visibility sensor 4 with a wide field of view, achieving effective integration of visibility parameters into a miniaturized UAV payload.

[0043] Referring to the interface relationship diagram shown in Figure 2-3, the core control and data processing units of this embodiment are all integrated inside the housing 8 to provide good electromagnetic shielding and environmental protection. The housing 8 houses a data acquisition unit, a BeiDou module, a memory, a lithium battery, and a power management unit.

[0044] The data acquisition unit is the "brain" of the entire payload, responsible for collecting and transmitting data from all sensors. The data acquisition unit is equipped with multiple interfaces to accommodate the communication needs of different sensors:

[0045] The wind direction and speed sensor 1, temperature and humidity sensor 2, and air pressure sensor 3 are all connected to the data acquisition unit via a first digital acquisition interface. In this embodiment, the first digital acquisition interface is preferably a UART interface or an IIC interface. This bus-type interface allows multiple devices to be mounted, simplifies the wiring on the top of the housing 8, and reduces system complexity.

[0046] The visibility sensor 4, located at the bottom of the rack 7, is connected to the data acquisition unit via a second digital acquisition interface. In this embodiment, the second digital acquisition interface is preferably an RS485 interface. The RS485 interface has strong anti-interference capabilities and a long transmission distance, ensuring reliable transmission of visibility data in complex electromagnetic environments.

[0047] The data acquisition unit is electrically connected to the memory. The memory is used to locally store the collected raw meteorological data and equipment status information in real time, ensuring data integrity and traceability.

[0048] The BeiDou module is electrically connected to the data acquisition unit. The data acquisition unit sends the processed and packaged meteorological data to the BeiDou module, which then remotely transmits the measurement data to the ground-based meteorological UAV integrated application software terminal via satellite short message communication. This enables real-time data transmission in areas without terrestrial network coverage, such as disaster sites and remote areas.

[0049] The data acquisition unit is also equipped with a wired external interface, such as an RS-232 or RS-485 interface. This interface is used to connect the payload to an external PC terminal or meteorological station's operational system during ground commissioning, calibration, or wired connection, enabling rapid data export and sharing.

[0050] The housing 8 houses a built-in lithium battery and power management unit. The lithium battery serves as the payload's independent power source, supplying power to all electrical components, including the data acquisition unit, all weather sensors, the BeiDou module, and the memory, through the power management unit. Optimized low-power design and independent power management ensure the payload's operational stability and minimize the impact on the UAV's own flight time.

[0051] The workflow of the general meteorological payload for UAVs in this embodiment is as follows:

[0052] After the load is powered on, the power management unit supplies power to all modules of the system. The data acquisition unit initializes all sensors and communication modules.

[0053] Wind direction and speed sensor 1, temperature and humidity sensor 2, and air pressure sensor 3 report data to the data acquisition unit in real time via I2C / UART interface. Visibility sensor 4 reports data via RS485 interface. The magnetic north measurement unit reports the load orientation data in real time.

[0054] The data acquisition unit receives all raw data. Following meteorological observation specifications, the unit processes and transmits the acquired data, including standard meteorological elements. All data is stored locally. Simultaneously, the data acquisition unit sends data to the BeiDou module, which then remotely transmits it to the terminal software via satellite. Alternatively, data can be transmitted to a nearby PC terminal via an RS-232 / RS-485 wired external interface.

[0055] In summary, this embodiment successfully solves the challenges of airflow interference from UAV rotors and multi-sensor integration through ingenious structural layout and internal integration. It is highly integrated, versatile, and consumes little power, serving as a "plug-and-play" module, enabling rotorcraft UAV platforms to acquire real-time, accurate meteorological data including six elements such as visibility.

[0056] Example 2

[0057] The following is in conjunction with the appendix Figure 1-4 Embodiment 2 of the present invention will be described in detail. Based on Embodiment 1, this embodiment further details the wind measurement principle of the wind direction and speed sensor, the dual measurement scheme of the visibility sensor, the magnetic north correction mechanism, and the data processing flow.

[0058] In this embodiment, the wind direction and speed sensor 1 employs an orthogonal pitot tube 10 combined with a differential pressure sensor to achieve lightweight and high-precision wind speed and direction measurement. The orthogonal pitot tube 10 is described below. Figure 4 .

[0059] Specifically, the wind direction and speed sensor 1 includes four pitot tubes 10 and two differential pressure sensors. The four pitot tubes 10 are paired up and orthogonally mounted on a cross-shaped bracket, forming two measurement axes, the X-axis and the Y-axis, respectively. On each measurement axis, the openings of the two pitot tubes 10 are opposite, pointing to the positive and negative directions of that axis, respectively.

[0060] The wind measurement principle on each measuring axis is as follows: the total pressure end of the coaxial positive direction pitot tube 10 and the total pressure end of the coaxial negative direction pitot tube 10 are respectively connected to the two ends of the corresponding differential pressure sensor to measure the pressure difference in that axis direction in a differential manner. When the wind blows from a certain direction, the total pressure sensed by the total pressure end of the pitot tube 10 in the windward direction is higher (including the dynamic pressure component), while the total pressure sensed by the total pressure end of the pitot tube 10 in the leeward direction is lower, and a pressure difference is formed between the two.

[0061] Let the pressure difference measured by the X-axis differential pressure sensor be ΔP. X The pressure difference measured by the differential pressure sensor in the Y-axis direction is ΔP. Y According to Bernoulli's equation, the wind speed components in each axial direction can be calculated using the following formula:

[0062] ;

[0063] ;

[0064] Among them, V X V represents the wind speed component along the X-axis. Y Let ΔP be the wind speed component along the Y-axis. X The pressure difference ΔP is measured by the differential pressure sensor in the X-axis direction. Y The differential pressure sensor measures the pressure difference along the Y-axis, ρ is the air density in the current environment, and sgn() is the sign function used to determine the direction of the wind speed component.

[0065] After obtaining the wind speed components in two orthogonal directions, the combined wind speed V and wind direction angle θ can be obtained by vector synthesis.

[0066] ;

[0067] ;

[0068] Where V is the composite wind speed, and θ is the wind direction angle relative to the sensor's X-axis. This wind direction angle is relative to the load's own coordinate system and needs to be further corrected to the actual meteorological wind direction using data from the magnetic north measurement unit.

[0069] In the above wind speed calculation formula, air density ρ is the key parameter. Air density varies significantly under different temperature, air pressure, and humidity conditions. If the standard atmospheric density ρ0 = 1.225 kg / m³ is used for calculation, a large error will be introduced.

[0070] This embodiment utilizes real-time measurement data from the temperature and humidity sensor 2 and the air pressure sensor 3 integrated on the top of the housing 8 to dynamically correct the air density, thereby improving the accuracy of wind measurement.

[0071] The specific correction method is as follows: First, based on the temperature T (unit: °C) and relative humidity RH (unit: %) measured by temperature and humidity sensor 2, and the air pressure P (unit: Pa) measured by air pressure sensor 3, calculate the virtual temperature T of the current environment. v .

[0072] Saturated water vapor pressure e s The calculation uses the following empirical formula:

[0073] ;

[0074] Among them, e s 1 is the saturated vapor pressure, in Pa; T is the temperature, in °C.

[0075] The actual water vapor pressure e is calculated from the saturated water vapor pressure and relative humidity:

[0076] ;

[0077] Where e is the actual water vapor pressure, in Pa; RH is the relative humidity, in %.

[0078] Virtual temperature T v The calculation formula is:

[0079] ;

[0080] Among them, T v is the virtual temperature in K; P is the atmospheric pressure in Pa; 0.378 is a constant related to the ratio of the molecular weight of water vapor to the average molecular weight of dry air.

[0081] Finally, the corrected air density ρ is calculated using the ideal gas law:

[0082] ;

[0083] Where ρ is the corrected air density, in kg / m³; R d The specific gas constant for dry air is 287.05 J / (kg·K).

[0084] Each time the data acquisition unit calculates the wind speed, it reads the latest data from the temperature and humidity sensor 2 and the air pressure sensor 3, calculates the current air density ρ in real time according to the above formula, and substitutes it into the wind speed calculation formula, thereby eliminating the influence of environmental changes on the accuracy of wind measurement.

[0085] This embodiment also includes a magnetic north measurement unit, which is electrically connected to the data acquisition unit and is housed within the housing 8. The magnetic north measurement unit measures the orientation angle α of the load relative to the geomagnetic north pole in real time.

[0086] Since the wind direction and speed sensor 1 is fixedly mounted on the top of the housing 8, the wind direction angle θ it measures is the direction angle relative to the sensor's own X-axis. During the drone's flight, the heading of the aircraft changes constantly; therefore, it is necessary to convert the wind direction angle θ in the sensor coordinate system to a meteorological wind direction angle θ based on geomagnetic north. N :

[0087] , where θ N Let θ be the wind direction angle relative to magnetic north, α be the wind direction angle in the sensor coordinate system, and α be the load orientation angle measured by the magnetic north measurement unit, i.e., the angle between the load X-axis and the magnetic north direction. If θ N If the value exceeds the range of 0° to 360°, a modulo operation is performed to normalize it to the range of 0° to 360°.

[0088] Through real-time correction by the magnetic north measurement unit, the data acquisition unit can always output the true meteorological wind direction based on magnetic north, regardless of how the UAV turns during flight.

[0089] In this embodiment, the visibility sensor 4 is located at the bottom of the frame 7 and includes two measuring components: a forward scattering device and a camera.

[0090] Forward scattering is the primary method for visibility measurement. It works by emitting a beam of light and measuring the intensity of scattered light from suspended particulate matter in the atmosphere at a specific angle, typically the forward scattering angle of approximately 42°. Based on the relationship between scattered light intensity and the extinction coefficient, the atmospheric extinction coefficient σ is calculated. Then, using Cauchy's law, the meteorological optical range (MOR), i.e., visibility V, is calculated. MOR :

[0091] ;

[0092] Among them, V MOR σ is the meteorological optical range, i.e., visibility, in meters; σ is the atmospheric extinction coefficient, in meters ⁻¹; ε is the contrast threshold, which is approximately 3.912 when the internationally accepted value is 0.05.

[0093] The forward scattering instrument can output visibility data in real time while flying horizontally or hovering.

[0094] The camera serves as an auxiliary measurement tool to measure and correct vertical visibility. The specific method is as follows: A high-contrast target is placed in the target area on the ground. The target uses a black and white checkerboard pattern, with the black parts made of a low-reflectivity material and the white parts made of a high-reflectivity material to create a clear brightness contrast.

[0095] The drone hovers sequentially at multiple preset altitudes (e.g., H1, H2, H3...Hn) over the target area. At each hovering altitude H... i At this location, the camera is positioned vertically downwards to capture images of a ground target. The data acquisition unit receives the image data from the camera and analyzes and processes the images using a dual-luminosity difference method.

[0096] The principle of the dual brightness difference method is as follows: at height H i From the target image taken at [location], the average brightness value L of the black area is extracted. b (H i ) and the average brightness value L of the white area w (H i ), calculate the apparent contrast C(H) at this height. i ):

[0097] According to Cauchy's law, apparent contrast C(H) i ) and atmospheric transmittance T(H i The relationship is:

[0098] Where C0 is the inherent contrast of the target at zero distance, which can be pre-calibrated, and T(H) i () represents the propagation of light from a ground target to a height H i Atmospheric transmittance at that location.

[0099] Atmospheric transmittance T(H) i ) and extinction coefficient σ v and path length H i The relationship follows the Beer-Lambert law:

[0100] , where σ v Here, represents the atmospheric extinction coefficient in the vertical direction, expressed in m⁻¹. Therefore:

[0101] After taking the logarithm of the above expression, we perform linearization:

[0102] The data acquisition unit utilizes data from multiple elevation points [H] i ,ln(C(H iPerform a least-squares linear fit, and the slope of the fitted line is the vertical extinction coefficient σ. v The negative value of σ is obtained by finding σ. v Then, Cauchy's law is used to calculate the vertical visibility V. v :

[0103] The data acquisition unit fuses and analyzes the horizontal visibility data measured by the forward scattering instrument with the vertical visibility data obtained based on the camera target method, and outputs more comprehensive and accurate atmospheric visibility information.

[0104] In this embodiment, the data acquisition unit standardizes the raw data collected from each sensor according to meteorological observation specifications. Specifically, the data acquisition unit acquires raw data from each sensor at a fixed sampling frequency and processes the data using minutes as the basic statistical period, calculating the following meteorological statistics:

[0105] (1) Minute average wind speed: The arithmetic mean of instantaneous wind speed values ​​within one minute (e.g., 60 sampling points);

[0106] (2) Minute average wind direction: The instantaneous wind direction value within one minute is averaged by taking the average of the sine and cosine components of the wind direction and then obtaining the average wind direction through the arctangent function.

[0107] (3) Maximum wind speed per minute: Take the maximum value among all instantaneous wind speed samples within one minute;

[0108] (4) Wind direction corresponding to the maximum wind speed per minute: Record the instantaneous wind direction value corresponding to the moment when the maximum wind speed per minute occurs;

[0109] (5) Minute average temperature: The arithmetic mean of the instantaneous temperature values ​​within one minute;

[0110] (6) Minute average relative humidity: The arithmetic mean of the instantaneous relative humidity values ​​over one minute;

[0111] (7) Minute average air pressure: The arithmetic mean of the instantaneous air pressure values ​​within one minute;

[0112] (8) Minute average visibility: The arithmetic mean of instantaneous visibility values ​​over one minute.

[0113] The data acquisition unit packages the processed minute-by-minute meteorological statistics into standardized meteorological data messages. These messages are simultaneously written into the memory within the casing 8 for local storage and then remotely transmitted via BeiDou module using satellite short messages to the ground-based meteorological UAV integrated application software terminal for use by meteorological forecasters and related users.

[0114] In this embodiment, the mounting plate 9 and the frame 7 are connected by a detachable quick-release connection. When it is not necessary to carry the payload module on the UAV for flight observation, the entire payload module, including the housing 8, support tube 6, mounting plate 9 and its sensors, can be quickly detached from the UAV. The detached payload module can be independently mounted on a tripod or other fixed support for use as a mobile ground weather station.

[0115] In stand-alone mode, the payload's built-in lithium battery continuously supplies power to all power-consuming units, including the data acquisition unit, sensors, BeiDou module, and memory, through a power management unit. The data acquisition unit continues to collect and process meteorological data in real time according to the aforementioned process and remotely transmits the data back via BeiDou satellite short messages. This mode is particularly suitable for scenarios such as disaster sites and remote areas without network coverage or fixed meteorological stations, enabling the rapid establishment of temporary meteorological observation stations to meet emergency meteorological support needs.

[0116] In summary, based on Example 1, this embodiment elaborates on the differential wind measurement principle of the wind direction and speed sensor based on the orthogonal pitot tube 10 and differential pressure sensor, the method of using temperature, humidity and air pressure data to correct air density to improve wind measurement accuracy, the real-time correction mechanism of the magnetic north measurement unit for wind direction data, the dual measurement and fusion correction scheme of the visibility sensor using a combination of forward scattering instrument and camera target method, and the complete process of data processing such as minute averaging according to meteorological observation specifications and remote transmission via BeiDou satellite, providing comprehensive technical support for the practical application of general meteorological payloads for UAVs.

[0117] Example 3

[0118] Building upon Examples 1 and 2, this embodiment further proposes a method for obtaining more accurate and robust wind direction data through dual data comparison and combined analysis using a wind direction and speed sensor 1 and an orthogonal pitot tube 10 system. Since the wind direction and speed sensor 1 is mounted on the top of the housing raised by the support tube, while the orthogonal pitot tubes 10 are mounted laterally in pairs on a cross-shaped bracket, their different spatial positions result in varying degrees of aerodynamic interference from the downwash airflow of the UAV rotor and the aircraft's movement. This embodiment uses a data acquisition unit to perform variance evaluation and weighted fusion of the wind data monitored by these two devices. The specific steps are as follows:

[0119] The first step is data synchronization and standardization. The data acquisition unit synchronously acquires the initial wind speed and direction measured by wind speed sensor 1 within the same sampling period, as well as the initial wind speed and direction calculated by airspeed tube 10 and differential pressure sensor system in Example 2. Combined with the orientation angle data from the magnetic north measurement unit, both sets of wind direction data are corrected to the true geographical meteorological wind direction based on geomagnetic north.

[0120] The second step is orthogonal component decomposition. To facilitate linear comparison and fusion, the data acquisition unit decomposes the wind vectors measured by the two sets of devices into independent wind speed components in the geographic east (E) and north (N) directions, respectively. The decomposition formula is as follows: Among them, V E1 : Wind speed component of the wind vector in the geographical due east direction measured by wind direction and wind speed sensor 1, in m / s; V1: Composite wind speed measured by wind direction and wind speed sensor 1, in m / s; θ1: Wind direction angle measured by wind direction and wind speed sensor 1 and corrected for magnetic north, with geomagnetic north as the reference, in degrees.

[0121] , where V N1 V1: Wind speed component of the wind vector measured by wind direction and speed sensor 1 in the direction of geographic due north, in m / s; V2: Composite wind speed measured by wind direction and speed sensor 1, in m / s; θ1: Wind direction angle measured by wind direction and speed sensor 1 and corrected for magnetic north, with geomagnetic north as the reference, in degrees.

[0122] Similarly, the data acquired by the pitot tube 10 system is decomposed as follows: , where V E2 V1: Wind speed component of the wind vector measured by the Pitot Tube 10 system in the geographic due east direction, in m / s; V2: Composite wind speed measured by the Pitot Tube 10 system, in m / s; θ2: Wind direction angle measured by the Pitot Tube 10 system and corrected for magnetic north, based on geomagnetic north, in degrees. , where V N2 V1: Wind speed component of the wind vector measured by the Pitot Tube 10 system in the geographic north direction, in m / s; V2: Composite wind speed measured by the Pitot Tube 10 system, in m / s; θ2: Wind direction angle measured by the Pitot Tube 10 system and corrected for magnetic north, based on geomagnetic north, in degrees.

[0123] The third step is data stability assessment and weight allocation. The data acquisition unit calculates the measurement variance of the two devices on corresponding components over the past minute. The smaller the variance, the more stable the measurement data of that device is during that period, and the less it is affected by sudden changes in gusts or rotor airflow. The fusion weights are calculated using a dynamic weighting method based on the reciprocal of the variance. W1: Weighting coefficient assigned to the wind direction and speed sensor 1 measurement data, dimensionless; : The variance of wind speed component measurement within a previously set time window by wind direction and speed sensor 1; Variance of wind speed component measurement in the pitot tube 10 system within a previously set time window.

[0124] Detailed character explanation: W2: Weighting coefficient assigned to the measurement data of the pitot tube 10 system, dimensionless; : The variance of wind speed component measurement within a previously set time window by wind direction and speed sensor 1; Variance of wind speed component measurement in the pitot tube 10 system within a previously set time window.

[0125] The fourth step is data fusion calculation. The data acquisition unit uses the calculated dynamic weights to perform weighted summation on the eastward and northward components respectively, obtaining the fused wind speed components: ,in, : Eastward wind speed component after data fusion from both devices, in m / s; W1, W2: Weighting coefficients of wind direction and speed sensor 1 and airspeed tube 10 calculated above; V E1 V E2 The wind speed components in the due east direction obtained by the two aforementioned devices are in m / s.

[0126] ,in, : The northward wind speed component after data fusion from both devices, in m / s; W1, W2: The weighting coefficients of the wind direction and speed sensor 1 and airspeed tube 10 calculated above; V N1 V N2 The wind speed components in the due north direction obtained by the two aforementioned devices are in m / s.

[0127] Finally, the fused wind speed components are resynthesized using inverse trigonometric functions to obtain the final high-precision wind direction angle data: , The final high-precision meteorological wind direction angle is output after dual-device combined analysis and fusion correction, in degrees (°). : The combined eastward wind speed component, in m / s; The merged northward wind speed component, in m / s. The quadrant is determined by the sign of the component, and the wind direction angle is normalized from 0° to 360° during calculation.

[0128] The core principle of this method lies in "spatial heterogeneous measurement and error complementarity." Wind direction and speed sensor 1, installed at the highest point of the fuselage, effectively avoids the strong downwash directly beneath the rotor, but may be affected by the shielding effect caused by the fuselage pitch angle during high-speed horizontal flight. Meanwhile, the laterally extending pitot tube 10 system, located far from the fuselage's central axis, is extremely sensitive to horizontal wind shear, but may be more susceptible to local transient interference from rotor tip vortices. The measurement errors generated by the two devices are non-fully correlated independent errors. By calculating the variance within a sliding window, the system can automatically identify which sensor's state is more stable under the current flight attitude and environmental wind field. Dynamic weighting based on the reciprocal of the variance is essentially a simplified application of optimal linear unbiased estimation. It strongly suppresses local abrupt noise from individual sensors, causing the fused output to automatically favor the measurement channel with the higher signal-to-noise ratio.

[0129] By combining the advantages of two sets of wind measurement devices with different physical locations and measurement principles, the measurement blind spots and system errors that may occur with a single sensor under specific drone flight attitudes are eliminated, making the final output wind direction data closer to the real environmental wind field.

[0130] The dynamic variance weighting mechanism is equivalent to an adaptive filter. When the UAV encounters complex airflow (such as gusts or turbulence) or makes drastic attitude adjustments, even if the data of one sensor fluctuates drastically or even fails temporarily, the other more stable sensor will be automatically assigned a very high weight, ensuring the continuity and reliability of the payload's meteorological observation data.

[0131] The dual-device synchronous monitoring and the introduction of a comparative analysis mechanism provide a built-in hardware-level self-testing method for UAV meteorological payloads, achieving the standards of professional-grade meteorological stations in terms of fault diagnosis and data quality control.

[0132] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A general-purpose meteorological payload for unmanned aerial vehicles (UAVs), characterized in that: include: Mounting plate (9), the bottom of which is fixedly connected to the top of the frame (7), a support tube (6) is fixedly connected to the mounting plate (9), and a housing (8) is fixedly connected to the top of the support tube (6). The wind direction and speed sensor (1), temperature and humidity sensor (2) and air pressure sensor (3) are used to collect basic environmental meteorological elements. The wind direction and speed sensor (1) is used to measure wind speed and wind direction data. The wind direction and speed sensor (1), temperature and humidity sensor (2) and air pressure sensor (3) are arranged from top to bottom on the top of the housing (8). A visibility sensor (4) is used to measure atmospheric visibility. The visibility sensor (4) is located at the bottom of the frame (7).

2. The universal meteorological payload for unmanned aerial vehicles according to claim 1, characterized in that: The housing (8) is equipped with a data acquisition unit, a Beidou module, and a memory. The data acquisition unit includes a first digital acquisition interface, and the wind direction and speed sensor (1), temperature and humidity sensor (2) and air pressure sensor (3) are all connected to the data acquisition unit through the first digital acquisition interface; The first digital acquisition interface is an I2C interface or a UART interface; The data acquisition unit includes a second digital acquisition interface; the visibility measurement unit (4) is connected to the data acquisition unit through the second digital acquisition interface, which is an RS485 interface; The data acquisition unit is electrically connected to the memory, which is used to locally store the collected meteorological data and equipment status information.

3. The universal meteorological payload for unmanned aerial vehicles according to claim 2, characterized in that: The data acquisition unit is also provided with a wired external interface, which includes an RS-232 interface or an RS-485 interface, for connecting the load to an external PC terminal. The Beidou module is electrically connected to the data acquisition unit and is used to remotely transmit measurement data to the terminal via satellite communication. It also includes a lithium battery and a power management unit, wherein the lithium battery is disposed inside the housing (8); the lithium battery supplies power to the data acquisition unit and each power-consuming unit of the meteorological payload through the power management unit.

4. The universal meteorological payload for unmanned aerial vehicles according to claim 2 or 3, characterized in that: It also includes a magnetic north measurement unit, which is electrically connected to the data acquisition unit and is used to measure the orientation data of the load in real time and to perform magnetic north correction on the wind direction data measured by the wind direction and wind speed sensor (1).

5. The universal meteorological payload for unmanned aerial vehicles according to claim 1, characterized in that: The wind direction and speed sensor (1) includes two pairs of orthogonally mounted airspeed tubes (10) and two differential pressure sensors; the two pairs of airspeed tubes (10) are orthogonally mounted in pairs on a cross-shaped bracket, forming two measuring axes, the X-axis and the Y-axis, respectively; on each measuring axis, the full pressure end of the coaxial positive direction airspeed tube (10) and the full pressure end of the coaxial negative direction airspeed tube (10) are respectively connected to the two ends of the corresponding differential pressure sensor, so as to measure the pressure difference ΔP in the X-axis direction in a differential manner. X Pressure difference ΔP in the Y-axis direction Y .

6. The general-purpose meteorological payload for unmanned aerial vehicles according to claim 5, characterized in that: The data acquisition unit calculates ΔP based on the differential pressure sensor. X and ΔP Y Based on the air density ρ, the wind speed components V in the X and Y axes are calculated using Bernoulli's equation. X and V Y And the composite wind speed and wind direction are obtained by vector synthesis; wherein, the air density ρ is obtained by the data acquisition unit based on the air pressure value measured by the air pressure sensor (3) and the temperature and humidity values ​​measured by the temperature and humidity sensor (2), and then corrected by the ideal gas state equation after calculating the virtual temperature.

7. The universal meteorological payload for unmanned aerial vehicles according to claim 1, characterized in that: The visibility sensor (4) includes a forward scattering instrument and a camera; both the forward scattering instrument and the camera are located at the bottom of the frame (7); the camera is used to take pictures of targets placed on the ground, and by analyzing the degradation degree of the images taken at different heights, the atmospheric transmittance and extinction coefficient are estimated, and then the visibility value is calculated and fused with the measurement data of the forward scattering instrument for correction.

8. The universal meteorological payload for unmanned aerial vehicles according to claim 7, characterized in that: The target is a high-contrast target with a black and white checkerboard pattern, wherein the black part is made of a low-reflectivity material; the drone hovers at multiple preset altitudes, and the camera takes vertically downward pictures of the target at each hovering altitude; the data acquisition unit analyzes the images at each altitude using the dual brightness difference method and calculates atmospheric visibility according to Cauchy's law.

9. The universal meteorological payload for unmanned aerial vehicles according to any one of claims 1-8, characterized in that: The mounting plate (9) is fixed to the frame (7) by a detachable quick-release connection, so that the load can be removed from the UAV and set up independently for use as a mobile weather station for meteorological observation.

10. The general meteorological payload for unmanned aerial vehicles according to claim 4, characterized in that: The data acquisition unit is configured to process the collected meteorological data according to meteorological observation specifications, including calculating the minute average wind direction and speed, minute average visibility, minute average temperature and humidity, minute average air pressure, and minute maximum wind speed and its corresponding wind direction, and then package the processed meteorological elements and send them through the Beidou module.

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