A cloud measuring system and method based on wave glider

Abstract

This application provides a cloud measurement system and method based on a wave glider. By integrating a laser cloud-measuring radar with a marine meteorological observation instrument onto a wave glider platform with ultra-long endurance, autonomous navigation, and virtual mooring capabilities, a sea-based mobile cloud observation system is constructed. This system overcomes the inherent shortcomings of existing satellite remote sensing observations, such as discontinuity and lack of vertical structure information, as well as the high cost, poor maneuverability, and limited coverage of ship and buoy observations. It achieves long-term, continuous, and mobile observation of cloud systems over vast ocean areas and can acquire high-precision cloud base height, vertical structure, and conventional meteorological elements from the sea surface, significantly improving the spatiotemporal continuity and data quality of marine meteorological observation.

Description

Technical Field

[0001] This application relates to the field of meteorological observation technology, and more specifically, to a cloud measurement system and method based on a wave glider. Background Technology

[0002] The formation and development of maritime cloud systems are a crucial foundation for short-term weather forecasting; however, effective monitoring of maritime cloud systems remains a significant challenge due to the complexity of the marine environment and limitations in observation technology. Currently, maritime cloud observation primarily relies on satellite remote sensing and shipborne sounding.

[0003] While satellite remote sensing technology boasts a wide coverage area, it has inherent limitations. Due to its orbital period, satellites cannot conduct continuous observations of cloud systems in specific sea areas with high temporal resolution. Furthermore, its top-down detection method lacks sufficient accuracy in detecting key parameters such as cloud base height and vertical cloud layering, making it difficult to meet the needs of refined weather forecasting and research. Although ship-launched weather balloons can provide relatively accurate vertical detection data, ship operating costs are extremely high, and their maneuverability is limited by routes, making it difficult to achieve long-term, fixed-point, or large-scale mobile observations of specific sea areas. This results in low spatiotemporal density and poor cost-effectiveness. In addition, while some fixed ocean buoys can achieve long-term continuous observation, their onboard cloud-measuring equipment can only acquire cloud information over single points, failing to track and monitor cloud systems over area.

[0004] Therefore, existing observation methods are insufficient for long-term, continuous, mobile observation of cloud systems with vertical structure information over the vast ocean, resulting in "blind spots" of poor temporal and spatial continuity and missing vertical structure information in marine meteorological observation data. In particular, the lack of effective near-shore cloud observation data severely restricts the accuracy and timeliness of forecasts and warnings for rapidly evolving hazardous weather systems such as typhoons and severe convection. Summary of the Invention

[0005] The purpose of this application is to provide a cloud measurement system and method based on a wave glider, in order to solve the problem that the existing technology is unable to achieve long-term, continuous, maneuverable observation of cloud systems with vertical structure information over a vast ocean.

[0006] This application provides a cloud measurement system based on a wave glider, comprising: sea-based equipment and shore-based equipment; The sea-based equipment includes a wave glider platform, a laser cloud radar mounted on the wave glider platform, and a marine meteorological observation instrument; The wave glider platform is used for autonomous navigation on a preset route and has a virtual anchoring function; the laser cloud radar is installed in an open area at the tail of the wave glider platform to measure cloud base height and visibility at regular intervals; the marine meteorological observation instrument is installed on the base of the wave glider platform to measure temperature, air pressure, wind direction and wind speed at regular intervals. The meteorological data collected by the laser cloud radar and marine meteorological observation instrument are transmitted back to the shore-based equipment at regular intervals through the communication system.

[0007] The aforementioned technical solution integrates a laser cloud-measuring radar with a marine meteorological observation instrument onto a wave glider platform capable of ultra-long endurance, autonomous navigation, and virtual mooring, thus constructing a sea-based mobile cloud observation system. This system overcomes the inherent limitations of existing satellite remote sensing observations, such as discontinuity, lack of vertical structure information, and the high cost, poor maneuverability, and limited coverage of ship-based and buoy-based observations. It achieves long-term, continuous, and mobile observation of cloud systems over vast ocean areas, and can acquire high-precision cloud base height, vertical structure, and conventional meteorological elements from the sea surface, significantly improving the spatiotemporal continuity and data quality of marine meteorological observation.

[0008] In some alternative embodiments, the wave glider platform includes a surface hull and an underwater tractor, connected by armored cables to form a catamaran structure; The surface vessel hull includes solar panels, batteries, data storage media, a BeiDou communication module, and an AIS module; The underwater tractor includes an underwater thruster, hydrofoils, a propeller, and a steering tail rudder, used to convert wave energy into kinetic energy to propel the platform.

[0009] In some optional implementations, the laser cloud-measuring radar performs attitude correction using wave glider attitude data, including: Input the attitude data of the wave glider's surface hull, including heading, pitch angle, and roll angle; By combining the attitude information collected by the built-in hardware compass of the laser cloud radar, dual-source attitude data complementarity is achieved, and the radar detection angle deviation caused by changes in the attitude of the hull platform is corrected.

[0010] In the above technical solution, the correction method can correct the lidar detection angle deviation caused by the swaying of the wave glider platform with the waves in real time, effectively overcome the influence of platform attitude disturbance on the vertical cloud observation accuracy in the dynamic marine environment, and thus ensure the accuracy and reliability of cloud base height and visibility data obtained from the mobile platform, providing a high-precision attitude compensation solution for marine meteorological observation.

[0011] In some optional implementations, the attitude correction of the laser cloud-measuring radar further includes: Based on the raw data collected by the triaxial accelerometer and triaxial magnetometer, the pitch angle, roll angle and yaw angle are calculated; By using hard magnetic compensation, soft magnetic compensation, tilt compensation, and magnetic declination compensation, magnetic field interference and attitude deviation are eliminated, resulting in high-precision true north reference attitude data.

[0012] In the above technical solution, the multi-level compensation algorithm not only effectively overcomes the serious impact of complex magnetic fields and attitude disturbances on measurement accuracy in the dynamic marine environment, but also ensures the long-term stability of the lidar detection angle and the accuracy of geographical pointing, thus providing key attitude assurance for obtaining reliable and accurate cloud vertical structure information from a mobile platform.

[0013] In some alternative implementations, the marine meteorological observation instrument performs attitude correction using wave glider attitude data, including: Input the attitude data of the wave glider's surface hull; The electronic compass uses hard and soft magnetic calibration algorithms to counteract magnetic field interference. Azimuth compensation is performed on a wide range of tilt angles using a triaxial accelerometer; Integrate multi-source data to complete attitude deviation correction.

[0014] In the above technical solution, the correction method effectively overcomes the impact of swaying, tilting and magnetic field distortion on the measurement accuracy of meteorological elements (such as wind direction and wind speed) of the wave glider platform under dynamic sea conditions, ensuring the accuracy and reliability of conventional meteorological data such as temperature, air pressure, wind direction and wind speed obtained from the mobile platform, and improving the overall data quality of marine meteorological observation.

[0015] In some optional implementations, the communication system includes a BeiDou communication module for achieving stable long-distance communication; The meteorological data collected by the laser cloud radar and marine meteorological observation instrument is transmitted back to the shore-based equipment through the Beidou communication module, and the shore-based commands of the shore-based equipment are sent to the wave glider platform through the Beidou communication module.

[0016] In some alternative embodiments, the shore-based equipment is further used for: Data transmission and communication, data reception and parsing, data classification, storage and backup; Map display and platform status visualization, platform path planning, and platform trajectory playback analysis; The platform controls command issuance, detects faults and provides early warnings of potential hazards, and generates platform status reports.

[0017] The marine-based equipment also includes: a dual-redundant timing system; In some optional implementations, the dual-redundant timing system is used to acquire meteorological data at regular intervals; The dual-redundant timing system includes a fault detection module, a hardware timing device, and a software timing system. The fault detection module monitors the operating status of hardware timing devices or software timing systems in real time. Once a fault is detected in one of the timing systems, it automatically switches to another normally functioning timing system.

[0018] This application provides a cloud measurement method based on a wave glider, comprising the following steps: The navigation path of the cloud measurement system is planned according to the observation needs, the equipment is debugged on land, and then deployed to the designated sea area by the mother ship. The wave glider platform navigates autonomously along a preset path, using attitude data to correct the laser cloud radar and marine meteorological observation instrument, and collects meteorological data at regular intervals. The collected meteorological data is transmitted back to shore-based equipment via a communication system for data quality control, data calibration, and storage.

[0019] In the above technical solution, the navigation path is flexibly planned based on observation needs, and the autonomous navigation capability of the wave glider platform is used to achieve mobile coverage of the target sea area; by fusing the attitude data of the wave glider to perform real-time correction on the laser cloud radar and marine meteorological observation instrument, the impact of the dynamic platform at sea on the observation accuracy is effectively overcome, and the accuracy of data acquisition is ensured; the acquired data is reliably transmitted back to the shore base through the communication system, and undergoes a strict data quality control and calibration process to finally form a high-quality and usable meteorological dataset.

[0020] In some alternative implementations, the data quality control includes: A reasonable threshold range is set based on the physical characteristics and historical statistical patterns of meteorological elements; The data is smoothed using moving average and median filtering algorithms to reduce the impact of random noise.

[0021] In the above technical solution, data quality control, by combining the physical characteristics of meteorological elements and historical statistical patterns to set a reasonable data threshold range, can effectively identify and eliminate obvious outliers caused by sudden sensor failures or extreme environmental interference, ensuring the validity and reliability of the data. At the same time, algorithms such as moving average and median filtering are used to smooth the data, which significantly reduces the impact of random noise and instantaneous interference on data quality during the measurement process, thereby improving the accuracy and consistency of marine meteorological observation data and providing a high-quality data foundation for subsequent data analysis, weather forecasting and climate research.

[0022] In some alternative implementations, the data calibration includes: On-site calibration is performed using data from standard meteorological reference stations or high-precision meteorological instruments. A sensor drift model is established by combining long-term observation data to correct the collected meteorological data in real time.

[0023] In the above technical solution, on the one hand, at key nodes such as the deployment and recovery of wave gliders, the calibrated standard meteorological reference station or high-precision meteorological instrument carried on the mother ship is used to conduct synchronous and same-location on-site comparison and calibration to directly correct system-level observation deviations; on the other hand, a sensor drift model is constructed by combining long-term continuous observation data, and the collected data is corrected in real time online through software algorithms, which effectively suppresses the accuracy decay and drift of the sensor caused by long-term operation or environmental changes.

[0024] In some optional implementations, a dual-redundant timing system is used to achieve timed acquisition of meteorological data; The dual-redundant timing system includes a fault detection module, a hardware timing device, and a software timing system. The fault detection module monitors the operating status of hardware timing devices or software timing systems in real time. Once a fault is detected in one of the timing systems, it automatically switches to another normally functioning timing system. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of the structure of a marine-based device provided in an embodiment of this application; Figure 2 This is a flowchart of the cloud measurement method steps provided in the embodiments of this application. Detailed Implementation

[0027] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0028] This application provides a cloud measurement system based on a wave glider, comprising: sea-based equipment and shore-based equipment; Please refer to Figure 1 The marine-based equipment includes wave glider platforms, laser cloud radar mounted on the wave glider platforms, and marine meteorological observation instruments; Among them, the wave glider platform is used to navigate autonomously on a preset route and has a virtual anchoring function; the laser cloud radar is installed in an open area at the tail of the wave glider platform to measure cloud base height and visibility at regular intervals; the marine meteorological observation instrument is installed on the base of the wave glider platform to measure temperature, air pressure, wind direction and wind speed at regular intervals. Meteorological data collected by laser cloud radar and marine meteorological observation instruments are transmitted back to shore-based equipment on a regular basis through a communication system.

[0029] The aforementioned technical solution integrates a laser cloud-measuring radar with a marine meteorological observation instrument onto a wave glider platform capable of ultra-long endurance, autonomous navigation, and virtual mooring, thus constructing a sea-based mobile cloud observation system. This system overcomes the inherent limitations of existing satellite remote sensing observations, such as discontinuity, lack of vertical structure information, and the high cost, poor maneuverability, and limited coverage of ship-based and buoy-based observations. It achieves long-term, continuous, and mobile observation of cloud systems over vast ocean areas, and can acquire high-precision cloud base height, vertical structure, and conventional meteorological elements from the sea surface, significantly improving the spatiotemporal continuity and data quality of marine meteorological observation.

[0030] In some alternative implementations, the wave glider platform includes a surface hull and an underwater tractor connected by armored cables to form a catamaran structure; The surface vessel hull includes solar panels, batteries, data storage media, a BeiDou communication module, and an AIS module; The underwater tractor consists of an underwater thruster, hydrofoil, propeller, and steering tail rudder, used to convert wave energy into kinetic energy to propel the platform.

[0031] Specifically, the wave glider platform possesses the capability for long-duration autonomous navigation at sea (over 3 months, a navigation distance of over 1000 kilometers, and normal operation in sea states below level 7), navigation along preset routes, and virtual anchoring (positional accuracy offset radius < 20 meters in sea states below level 3). During navigation, onboard equipment simultaneously conducts continuous observations of meteorological elements, acquiring data such as cloud base height, visibility, sea surface temperature, air pressure, wind direction, and wind speed. The observation data is relayed back to a shore-based terminal via satellite communication at regular intervals. The terminal possesses the capability for all-weather visual monitoring and control of the wave glider and its onboard instruments, as well as the ability to receive, classify, store, and visualize environmental data.

[0032] The wave glider platform consists of a surface hull and an underwater towing mechanism, connected by an armored cable to form a catamaran structure. The surface hull is primarily composed of a lightweight hull and frame, solar panels, batteries, data storage media, BeiDou / wireless communication, a beacon, and strobe lights. The wave glider is equipped with an AIS module to receive information from nearby vessels, providing fundamental information for situational awareness and ensuring navigational safety. The solar panels provide power for observation and communication equipment on the platform in clear weather and ensure normal operation of the equipment in cloudy weather by charging the batteries, ensuring the wave glider's ability to operate continuously in designated sea areas for extended periods. The underwater propulsion unit mainly consists of a frame, underwater thrusters, hydrofoils, a propeller, and a steering rudder. The underwater propulsion unit converts wave energy into kinetic energy to propel the platform.

[0033] The laser cloud-measuring radar is installed in a relatively open, unobstructed area at the stern of the wave glider platform. This area is far from other equipment or structural components on the hull that might interfere with the radar's signal transmission and reception, ensuring that the radar can transmit laser beams into the sky and receive reflected signals without obstruction. The marine meteorological observation instrument is fixed to a base on the wave glider platform via fiberglass tubes, avoiding mutual obstruction with other communication equipment to ensure accurate data acquisition. To protect against wind and wave impacts in the marine environment, the meteorological observation system is equipped with protective covers to prevent seawater corrosion. The two devices are interconnected with the wave glider platform's power and communication systems. The laser cloud-measuring radar can periodically observe cloud base height and visibility; the marine meteorological instrument can periodically observe routine marine meteorological elements such as temperature, air pressure, wind direction, and wind speed. The observed data is stored in the wave glider's storage medium and periodically transmitted back to the shore-based terminal via the communication system.

[0034] In some alternative implementations, the laser cloud-measuring radar performs attitude correction using wave glider attitude data, including: Input the attitude data of the wave glider's surface hull, including heading, pitch angle, and roll angle; By combining the attitude information collected by the built-in hardware compass of the laser cloud radar, dual-source attitude data complementarity is achieved, and the radar detection angle deviation caused by changes in the attitude of the hull platform is corrected.

[0035] In the above technical solution, the correction method can correct the lidar detection angle deviation caused by the swaying of the wave glider platform with the waves in real time, effectively overcome the influence of platform attitude disturbance on the vertical cloud observation accuracy in the dynamic marine environment, and thus ensure the accuracy and reliability of cloud base height and visibility data obtained from the mobile platform, providing a high-precision attitude compensation solution for marine meteorological observation.

[0036] In some optional implementations, the attitude correction of the laser cloud-measuring radar also includes: Based on the raw data collected by the triaxial accelerometer and triaxial magnetometer, the pitch angle, roll angle and yaw angle are calculated; By using hard magnetic compensation, soft magnetic compensation, tilt compensation, and magnetic declination compensation, magnetic field interference and attitude deviation are eliminated, resulting in high-precision true north reference attitude data.

[0037] In the above technical solution, the multi-level compensation algorithm not only effectively overcomes the serious impact of complex magnetic fields and attitude disturbances on measurement accuracy in the dynamic marine environment, but also ensures the long-term stability of the lidar detection angle and the accuracy of geographical pointing, thus providing key attitude assurance for obtaining reliable and accurate cloud vertical structure information from a mobile platform.

[0038] In some alternative implementations, the marine meteorological observation instrument performs attitude correction using wave glider attitude data, including: Input the attitude data of the wave glider's surface hull; The electronic compass uses hard and soft magnetic calibration algorithms to counteract magnetic field interference. Azimuth compensation is performed on a wide range of tilt angles using a triaxial accelerometer; Integrate multi-source data to complete attitude deviation correction.

[0039] In the above technical solution, the correction method effectively overcomes the impact of swaying, tilting and magnetic field distortion on the measurement accuracy of meteorological elements (such as wind direction and wind speed) of the wave glider platform under dynamic sea conditions, ensuring the accuracy and reliability of conventional meteorological data such as temperature, air pressure, wind direction and wind speed obtained from the mobile platform, and improving the overall data quality of marine meteorological observation.

[0040] Attitude calculation is based on raw data from triaxial accelerometers and triaxial magnetometers. The X, Y, and Z axis values ​​of the sensors are acquired in real time through IIC communication. The pitch angle, roll angle, and yaw angle are calculated by combining standard geometric and geomagnetic formulas. The sensor coordinate system is defined as a right-handed coordinate system: the X-axis is horizontal to the right, the Y-axis is horizontal to the front, and the Z-axis is vertical to the top. Before calculation, the raw sensor data needs to be normalized (to eliminate the influence of range).

[0041] Calculate the elevation angle: Taking advantage of the fact that the accelerometer is only subject to gravitational acceleration in a stationary state, the pitch angle is calculated by analyzing the components of gravitational acceleration on the three axes of the sensor, which reflects the tilt angle of the cloud measuring instrument in the YZ plane.

[0042]

[0043] in: , , These are the normalized values ​​for the X, Y, and Z axes of the accelerometer. The arctangent function is in the four quadrants (ensuring the angle range is...). The calculation result is in degrees (°).

[0044] Calculate the roll angle: The same pitch angle calculation logic reflects the tilt angle of the cloud measuring instrument in the XZ plane, providing basic data for tilt compensation of the heading angle.

[0045]

[0046] in: , , The values ​​are normalized values ​​for the X, Y, and Z axes of the accelerometer. The calculation results are in degrees (°), and the angle range is... .

[0047] Calculate the heading angle: First, tilt compensation is performed on the original data of the magnetometer using the pitch and roll angles calculated by the accelerometer (to eliminate the influence of the non-horizontal state of the cloud measuring instrument on the magnetic field detection). The three-dimensional magnetic field components are then projected onto the horizontal plane, and the geomagnetic azimuth angle on the horizontal plane is calculated to reflect the angle between the cloud measuring instrument and magnetic north.

[0048] Tilt compensation of raw magnetometer data, calculation of horizontal magnetic field components. , :

[0049]

[0050] in: , , These are the original values ​​for the X, Y, and Z axes of the magnetometer. , Pitch angle and roll angle are measured in radians.

[0051] Calculate the heading angle (magnetic north reference):

[0052] If the calculation result Then the correction is The final result range is The unit is degrees (°).

[0053] Attitude correction is the core calibration step for cloud measuring instrument attitude data. It is performed in the order of hard magnetic compensation → soft magnetic compensation → tilt compensation → magnetic declination compensation, eliminating magnetic field fixed interference, magnetic field distortion interference, non-horizontal state interference, and magnetic north and true north deviation in turn. Finally, it outputs high-precision true north reference attitude data. The data of each compensation step must be strictly consistent with the sensor coordinate system.

[0054] Hard magnetic compensation: Eliminate the interference from the fixed magnetic field generated by the permanent magnet and circuit board operating current inside the cloud measuring instrument. This interference manifests as a fixed offset of the center of the geomagnetic measuring sphere and is the most basic compensation item among all magnetic field interferences.

[0055] Three-dimensional compensation vector ,in , , These are the hard magnetic offset compensation values ​​for the X, Y, and Z axes, respectively (in the same units as the original data from the magnetometer).

[0056]

[0057] in: , , These are the original values ​​from the magnetometer. , , This is the magnetic force count value after hard magnetic compensation.

[0058] The compensation value needs to be obtained through calibration on a three-dimensional turntable. In an environment without external magnetic interference, the cloud measuring instrument is rotated 360° around each of the three axes, and the extreme values ​​of the magnetometer are collected. The midpoint of the extreme values ​​is taken as the hard magnetic offset compensation value.

[0059] Soft magnetic compensation: Eliminate the distortion of the geomagnetic field caused by soft magnetic materials such as the outer shell (iron shell) of the cloud measuring instrument, battery, and metal connectors. The distortion of the geomagnetic field manifests as the magnetic field measurement changing from a standard sphere to an ellipsoid. The compensation goal is to correct the ellipsoid to a sphere, which needs to be performed after hard magnetic compensation.

[0060] 3×3 symmetric compensation matrix (Usually a diagonal matrix to reduce computation), the matrix form is:

[0061] in: , , These are the triaxial principal compensation coefficients. , , This is the cross-compensation coefficient (taken as 0 when there is no cross-interference, the matrix degenerates into a diagonal matrix).

[0062]

[0063] in: This is the inverse of the soft magnetic compensation matrix. , , These are the values ​​after hard magnetic compensation. , , The values ​​are after soft magnetic compensation.

[0064] By acquiring N sets (N≥12) of magnetometer measurements and actual geomagnetic field values ​​under different postures using a three-dimensional turntable, a linear equation system is established to solve for the compensation matrix parameters, ensuring that the magnitude of the three-axis magnetic field strength is consistent after compensation.

[0065] Magnetic declination compensation: Converting the magnetic north reference heading angle obtained after soft magnetic compensation into the true north reference heading angle eliminates the angular deviation between the Earth's magnetic north pole and the geographic north pole. This is the final calibration step for the heading angle, and the compensation value is related to the geographical latitude, longitude, and altitude of the cloud measuring instrument.

[0066] Magnetic declination Eastward deviation is positive, and westward deviation is negative. This can be obtained by inputting the latitude, longitude, and altitude of the cloud measuring instrument into the NOAA magnetic declination calculator or a geographic information platform. For high-altitude areas, an altitude correction needs to be added.

[0067] in: This is the magnetic declination after altitude correction. Magnetic declination at sea level This is the altitude correction factor. To measure the actual altitude of the cloud instrument, The reference height is sea level (0m).

[0068]

[0069] in: The reference heading angle for magnetic north (after tilt compensation). The final heading angle is the true north reference. If the calculation result is... Then take ;like Then take The result range is guaranteed to be .

[0070] Magnetic declination has spatiotemporal characteristics and needs to be updated in real time according to the working area of ​​the cloud measuring instrument. The same compensation value can be used for a short period of time (≤30 days) within the same area.

[0071] In some alternative implementations, the communication system includes a BeiDou communication module for achieving stable long-distance communication; Meteorological data collected by laser cloud radar and marine meteorological observation instruments are transmitted back to shore-based equipment via Beidou communication modules, and shore-based commands from shore-based equipment are sent to the wave glider platform via Beidou communication modules.

[0072] In some alternative implementations, the shore-based equipment is also used for: Data transmission and communication, data reception and parsing, data classification, storage and backup; Map display and platform status visualization, platform path planning, and platform trajectory playback analysis; The platform controls command issuance, detects faults and provides early warnings of potential hazards, and generates platform status reports.

[0073] Specifically, the shore-based equipment features functions such as data transmission and communication, data reception and parsing, data classification, storage and backup, system security and data encryption, map display and platform status visualization, platform path planning, platform trajectory playback and analysis, platform command issuance and control, fault detection and hazard warning, and platform status report generation. The system also provides a user-friendly interface, enabling operators to monitor the real-time operating status of each device and changes in collected data. Furthermore, the system offers a data download function, with data primarily including platform status data and data collected by relevant onboard sensors.

[0074] Please refer to Figure 2 This application provides a cloud measurement method based on a wave glider, which includes the following steps: Step 100: Plan the navigation path of the cloud measurement system according to the observation requirements, debug the equipment on land, and deploy it to the predetermined sea area via the mother ship; Specifically, based on observation needs (such as long-term monitoring of key areas), the navigation path of the cloud measurement system is planned (including the route to the target sea area, the fixed-point or cruise route within the target sea area, and the return route after the mission is completed), and the mission instructions are input into the system. Two days before the mission begins, the equipment is debugged and inspected on land. After successful verification operation, the equipment is transferred and loaded onto a ship. Subsequently, the equipment is transported to the designated sea area on a mother ship. The mother ship measures or queries the sea area's depth, current velocity and direction, sea surface density, meteorological conditions, etc., and after determining the deployment location, personnel are organized to deploy the cloud measurement system equipment.

[0075] Step 200: The wave glider platform navigates autonomously along a preset path, using attitude data to correct the laser cloud radar and marine meteorological observation instrument, and periodically collects meteorological data. Specifically, the wave glider platform autonomously navigates along a preset path, and attitude data is input into the laser cloud-measuring radar and marine meteorological observation instrument for attitude correction. The observation equipment synchronously and automatically executes observation tasks at a set sampling frequency (e.g., every 10 minutes). Shore-based operators monitor task execution logs and process status to determine sensor operating conditions. If a timing system malfunction is detected, such as a hardware timing device communication interruption or a software timing task failing to execute on time, the fault detection module will immediately issue an alarm and automatically switch to the normally operating timing system to continue observation tasks, thus ensuring uninterrupted cloud base height and visibility observations. Simultaneously, the system records the time and cause of the malfunction, providing a basis for subsequent maintenance and system optimization. The collected raw data is temporarily stored within the wave glider platform and, using a data compression strategy, is then packetized and transmitted according to communication protocol requirements, with a CRC32 checksum added to each data packet to ensure data integrity during transmission.

[0076] Step 300: The collected meteorological data is transmitted back to the shore-based equipment through the communication system for data quality control, data calibration and storage.

[0077] In the above technical solution, the navigation path is flexibly planned based on observation needs, and the autonomous navigation capability of the wave glider platform is used to achieve mobile coverage of the target sea area; by fusing the attitude data of the wave glider to perform real-time correction on the laser cloud radar and marine meteorological observation instrument, the impact of the dynamic platform at sea on the observation accuracy is effectively overcome, and the accuracy of data acquisition is ensured; the acquired data is reliably transmitted back to the shore base through the communication system, and undergoes a strict data quality control and calibration process to finally form a high-quality and usable meteorological dataset.

[0078] In some alternative implementations, data quality control includes: A reasonable threshold range is set based on the physical characteristics and historical statistical patterns of meteorological elements; The data is smoothed using moving average and median filtering algorithms to reduce the impact of random noise.

[0079] In the above technical solution, data quality control, by combining the physical characteristics of meteorological elements and historical statistical patterns to set a reasonable data threshold range, can effectively identify and eliminate obvious outliers caused by sudden sensor failures or extreme environmental interference, ensuring the validity and reliability of the data. At the same time, algorithms such as moving average and median filtering are used to smooth the data, which significantly reduces the impact of random noise and instantaneous interference on data quality during the measurement process, thereby improving the accuracy and consistency of marine meteorological observation data and providing a high-quality data foundation for subsequent data analysis, weather forecasting and climate research.

[0080] Specifically, the criteria for setting thresholds for meteorological observation data can be considered from the following aspects: physical limits, climatological or statistical range, correlation between different elements, spatial consistency, temporal consistency, and performance indicators of observation instruments.

[0081] Physical limits generally refer to extreme values ​​of meteorological elements on a global scale, especially the threshold range of polar surface temperature, which is much larger than the threshold range of tropical ocean temperature.

[0082] Climatological or statistical ranges are the most important factors when setting thresholds for specific regional elements. For example, the average surface temperature of the South China Sea ranges from approximately 15°C to 32°C. Strong cold air masses brought by winter cold waves can cause the surface temperature to drop below 12°C; while the surface temperature may briefly rise before and after typhoons pass through the South China Sea in summer. Taking into account the impact of different weather processes on the South China Sea region and the resulting temperature changes, the surface temperature threshold for the South China Sea can be set at 10°C to 35°C.

[0083] The correlation between different elements: There are basic physical relationships between meteorological elements. When setting a threshold for a certain element, it is necessary to check whether the observed values ​​of other related elements exceed their own variation limits. For example, the relationship between air pressure and altitude, and the relationship between sea surface temperature and sea surface air temperature.

[0084] Spatial consistency: When meteorological elements undergo extreme changes, they will also be spatially correlated with other regions. Therefore, when setting thresholds for a specific region, the changing characteristics of meteorological conditions in the surrounding areas must be considered.

[0085] Temporal consistency: For single-station observation data, it is necessary to check whether the rate of change of the data over time is reasonable. For example, air pressure is unlikely to rise or fall by 10 hPa within 1 minute, and temperature is unlikely to change by more than 10°C within 1 hour. Therefore, even if such abrupt changes are found in the observation, the reasonableness of the data change should be carefully checked before setting the threshold.

[0086] Instrument performance specifications: The instrument itself has a limited measurement range. Measurement data exceeding the range should be considered invalid and cannot be used as a threshold.

[0087] In some alternative implementations, data calibration includes: On-site calibration is performed using data from standard meteorological reference stations or high-precision meteorological instruments. A sensor drift model is established by combining long-term observation data to correct the collected meteorological data in real time.

[0088] In the above technical solution, on the one hand, at key nodes such as the deployment and recovery of wave gliders, the calibrated standard meteorological reference station or high-precision meteorological instrument carried on the mother ship is used to conduct synchronous and same-location on-site comparison and calibration to directly correct system-level observation deviations; on the other hand, a sensor drift model is constructed by combining long-term continuous observation data, and the collected data is corrected in real time online through software algorithms, which effectively suppresses the accuracy decay and drift of the sensor caused by long-term operation or environmental changes.

[0089] Specifically, the on-site calibration method is as follows: Wave gliders are typically deployed from a vessel to a designated location. The vessel is equipped with marine meteorological instruments and cloud-measuring radar, which are calibrated before deployment. During deployment, the marine meteorological instruments and cloud-measuring radar on the launching vessel can be used to conduct synchronous and simultaneous observations with the wave glider. The on-site comparison results can correct for systematic biases in the wave glider's meteorological data. Similarly, on-site calibration can also be performed during wave glider recovery or other meteorological and hydrological research missions conducted near the wave glider.

[0090] Post-recovery sensor drift correction: By analyzing the acquired long-term series of observation data, unreasonable abrupt changes or trend drifts in long-term variations are extracted. Trend drifts can be identified by comparing with overflying satellite remote sensing data and reanalysis data. Abrupt data can be corrected by deleting it or by smoothing it using normal data before and after. Trend drifts require sensor calibration after recovering the wave glider to confirm the amount of drift and retrospectively correct historical data.

[0091] In some optional implementations, a dual-redundant timing system is used to achieve timed acquisition of meteorological data; The dual-redundant timing system includes a fault detection module, a hardware timing device, and a software timing system. The fault detection module monitors the operating status of hardware timing devices or software timing systems in real time. Once a fault is detected in one of the timing systems, it automatically switches to another normally functioning timing system.

[0092] To ensure timely observation of meteorological elements, this embodiment employs a dual-redundancy scheme combining hardware and software timing. Under normal circumstances, the hardware timing device (such as a dedicated timing controller) and the software timing system (operating system task scheduling or professional task scheduling software) operate simultaneously, each independently executing the timing triggering operation.

[0093] The system deploys a dedicated fault detection module to monitor the operational status of both hardware timing devices and software timing systems in real time. For hardware timing devices, its operational status is determined by monitoring indicators such as output signals, communication status, and power supply. For software timing systems, its operational status is determined by monitoring task execution logs and process status. Once a fault is detected in a timing system, such as a communication interruption in a hardware timing device or a software timing task failing to execute on time, the fault detection module immediately issues an alarm and automatically switches to another normally functioning timing system to continue the observation task, thus ensuring uninterrupted meteorological observation. Simultaneously, the system records the time and cause of the fault, providing a basis for subsequent maintenance and system optimization.

[0094] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0095] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0096] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0097] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0098] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A cloud measurement system based on a wave glider, characterized in that, include: Marine-based and shore-based equipment; The sea-based equipment includes a wave glider platform, a laser cloud radar mounted on the wave glider platform, and a marine meteorological observation instrument; The wave glider platform is used for autonomous navigation on a preset route and has a virtual anchoring function; the laser cloud radar is installed in an open area at the tail of the wave glider platform to measure cloud base height and visibility at regular intervals; the marine meteorological observation instrument is installed on the base of the wave glider platform to measure temperature, air pressure, wind direction and wind speed at regular intervals. The meteorological data collected by the laser cloud radar and marine meteorological observation instrument are transmitted back to the shore-based equipment at regular intervals through the communication system.

2. The system as described in claim 1, characterized in that, The wave glider platform comprises a surface hull and an underwater tractor, which are connected by armored cables to form a catamaran structure. The surface vessel hull includes solar panels, batteries, data storage media, a BeiDou communication module, and an AIS module; The underwater tractor includes an underwater thruster, hydrofoils, a propeller, and a steering tail rudder, used to convert wave energy into kinetic energy to propel the platform.

3. The system as described in claim 2, characterized in that, The laser cloud-measuring radar performs attitude correction using wave glider attitude data, including: Input the attitude data of the wave glider's surface hull, including heading, pitch angle, and roll angle; By combining the attitude information collected by the built-in hardware compass of the laser cloud radar, dual-source attitude data complementarity is achieved, and the radar detection angle deviation caused by changes in the attitude of the hull platform is corrected.

4. The system as described in claim 3, characterized in that, The attitude correction of the laser cloud-measuring radar also includes: Based on the raw data collected by the triaxial accelerometer and triaxial magnetometer, the pitch angle, roll angle and yaw angle are calculated; By using hard magnetic compensation, soft magnetic compensation, tilt compensation, and magnetic declination compensation, magnetic field interference and attitude deviation are eliminated, resulting in high-precision true north reference attitude data.

5. The system as described in claim 3, characterized in that, The marine meteorological observation instrument performs attitude correction based on wave glider attitude data, including: Input the attitude data of the wave glider's surface hull; The electronic compass uses hard and soft magnetic calibration algorithms to counteract magnetic field interference. Azimuth compensation is performed on a wide range of tilt angles using a triaxial accelerometer; Integrate multi-source data to complete attitude deviation correction.

6. The system as described in claim 5, characterized in that, The communication system includes a BeiDou communication module for achieving stable long-distance communication; The meteorological data collected by the laser cloud radar and marine meteorological observation instrument is transmitted back to the shore-based equipment through the Beidou communication module, and the shore-based commands of the shore-based equipment are sent to the wave glider platform through the Beidou communication module.

7. The system as described in claim 1, characterized in that, The shore-based equipment is also used for: Data transmission and communication, data reception and parsing, data classification, storage and backup; Map display and platform status visualization, platform path planning, and platform trajectory playback analysis; The platform controls command issuance, detects faults and provides early warnings of potential hazards, and generates platform status reports.

8. The system as described in claim 8, characterized in that, The marine-based equipment also includes: a dual-redundant timing system; The dual-redundant timing system is used to collect meteorological data at regular intervals. The dual-redundant timing system includes a fault detection module, a hardware timing device, and a software timing system. The fault detection module monitors the operating status of hardware timing devices or software timing systems in real time. Once a fault is detected in one of the timing systems, it automatically switches to another normally functioning timing system.

9. A cloud measurement method based on a wave glider, characterized in that, Includes the following steps: The navigation path of the cloud measurement system is planned according to the observation needs, the equipment is debugged on land, and then deployed to the designated sea area by the mother ship. The wave glider platform navigates autonomously along a preset path, using attitude data to correct the laser cloud radar and marine meteorological observation instrument, and collects meteorological data at regular intervals. The collected meteorological data is transmitted back to shore-based equipment via a communication system for data quality control, data calibration, and storage.

10. The method as described in claim 8, characterized in that, The data quality control includes: A reasonable threshold range is set based on the physical characteristics and historical statistical patterns of meteorological elements; The data is smoothed using moving average and median filtering algorithms to reduce the impact of random noise.

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