Strong wind environment sounding balloon releasing method suitable for saischtang mountain astronomical meteorological observation

Abstract

The invention relates to the technical field of meteorological observation, in particular to a strong wind environment sounding balloon releasing method suitable for astronomical meteorological observation of the Sash mountain, which comprises the following steps: S1, a point selection stage; s2, a preparation stage; s3, a release opportunity judgment stage; s4, a multi-person cooperation release stage; s5, a signal confirmation and evacuation stage; s6, a first data recording stage; s7, a second data recording stage; through precise point selection of a terrain and wind speed modeling algorithm, reasonable inflation through an altitude and inflation volume association algorithm, and accurate judgment of release opportunity based on a wind speed prediction algorithm and a weather early warning algorithm of LSTM, the release success rate of the sounding balloon in a complex environment of the Sash mountain can be effectively improved, the collision risk of the balloon and an obstacle is reduced, and the safety of the sounding balloon is improved. Balloon burst caused by improper inflation volume is avoided, the loss rate of an instrument is effectively reduced, the efficiency of observation operation can be further improved, and more effective observation data can be obtained within limited time.

Description

TECHNICAL FIELD

[0001] The present application relates to the meteorological observation technical field, specifically to a kind of big wind environment sounding balloon launching method suitable for Xisheng mountain astronomical meteorological observation. BACKGROUND

[0002] Xisheng mountain is an important astronomical meteorological observation base in China, its unique geographical location and climate conditions bring many challenges to observation work, the average altitude of this region is more than 4000 meters, is deeply affected by the westerlies circulation and plateau monsoon, annual average gale days are as high as 150-200 days, instantaneous maximum wind speed can exceed 25 meters / s, at the same time, weather changes very frequently, short-time rainstorm, lightning and other strong convective weather occur from time to time, and the altitude difference is large, local difference exceeds 800 meters, at present, conventional sounding balloon launching technology is mainly suitable for low altitude, altitude less than 1000 meters, wind is small, annual average gale days are less than 50 days of plain area, so it is difficult to meet the special environmental requirements of Xisheng mountain, for example, in the site selection link, mainly rely on artificial reconnaissance, do not fully use historical wind speed data and terrain modeling for scientific analysis, so as to often avoid seasonal wind port or terrain turbulence zone, which makes the balloon at the initial stage of launching, it is easy to be blown to the obstacle by strong wind, improves the balloon breakage rate, and in the balloon inflation quantity, according to the fixed standard, the balloon is usually inflated to 2-2.5 meters in diameter, but considering the influence of altitude on balloon, in the high altitude low pressure environment above 4000 meters of Xisheng mountain, according to the conventional quantity, the balloon is easy to burst due to the large pressure difference after launching, if the inflation quantity is too small, the balloon lifting force will be insufficient, so as to reduce the observation height; In view of this, we propose a kind of big wind environment sounding balloon launching method suitable for Xisheng mountain astronomical meteorological observation. SUMMARY

[0003] In view of the above shortcomings of the prior art, the present application provides a kind of big wind environment sounding balloon launching method suitable for Xisheng mountain astronomical meteorological observation, which can effectively solve the problem that the prior art sounding balloon launching technology is difficult to meet the observation requirements of Xisheng mountain due to the dependence on artificial reconnaissance in site selection, the inflation quantity is according to the fixed standard, and is not adapted to high altitude and strong wind environment, resulting in high balloon breakage rate, easy to burst and insufficient observation height.

[0004] To achieve the above purpose, the technical scheme is as follows: The present application provides a kind of big wind environment sounding balloon launching method suitable for Xisheng mountain astronomical meteorological observation, comprising the following steps: S1 selection stage: combine terrain and wind speed modeling algorithm, fuse the 10-meter resolution digital elevation model DEM data of the observation area of Sisheng Mountain with the 1-hour historical wind speed data of the near-weather observation technology with a time resolution of 5 years to calculate the annual average wind speed, turbulence intensity and obstacle influence coefficient of the potential release point, and select the flat and open area on the mountain top with the meteorological observation technology "annual average wind speed less than 4 meters per second, turbulence intensity less than 0.2, and obstacle influence coefficient less than 0.1", avoiding seasonal wind outlets; S2 preparation stage: combine altitude and inflation volume correlation algorithm, inflate the sounding balloon according to the meteorological observation technology "when the altitude is 3500 to 4000 meters, the balloon inflation diameter is 1.8 to 2 meters, when the altitude is 4000 to 4500 meters, the balloon inflation diameter is 1.6 to 1.8 meters, and when the altitude is greater than 4500 meters, the balloon inflation diameter is 1.5 to 1.6 meters", and conduct instrument inspection to ensure that the sounding balloon is not damaged, the battery of the sounding instrument has sufficient power and the sensor is not faulty, and the length of the lightweight connecting line is 5 to 8 meters to tighten the sounding instrument and the balloon, ensuring that the connecting line is not tangled; S3 release timing judgment stage: combine wind speed prediction algorithm and weather warning algorithm, use the wind speed prediction algorithm based on LSTM meteorological observation technology, input the real-time wind speed, sampling frequency 1 minute, pressure and temperature data of the observation station in the past 1 year, predict the wind speed in the next 1 hour, error less than 0.5 meters / second, lock the period when the wind speed is less than 3 meters / second, combine the weather warning algorithm, monitor the precipitation within 30 kilometers, intensity greater than 0.5mm / h, and lightning flash density greater than 1 times / 10 square kilometers, and no adverse warning, then through the visual confirmation of the flag slightly fluttering without unfolding and the dry grass slightly shaking without lodging, finally determine the release timing, if the release conditions are not met, enter the waiting state until the algorithm outputs the required timing; S4 multi-person cooperation release stage: combine action synchronization algorithm and turbulence interference coping algorithm, use the action synchronization algorithm, send synchronization instructions to 3 workers through the wireless instruction terminal, time error less than 0.1 second, 1 person supports the instrument, pushes the instrument with a force of 5 to 10 N, feedback through force sensor, 2 people hold the bottom of the balloon, synchronize to release hands after unified instruction, the instrument is pushed by the supporting personnel, the balloon ascends initially, 0 to 50 meters, through the turbulence interference coping algorithm, based on the acceleration data of the sounding instrument, sampling frequency 10Hz, judge the turbulence intensity, if greater than 0.3, then extend the pushing time to 2 to 3 seconds; S5 signal confirmation and evacuation stage: combine signal quality evaluation algorithm, calculate the signal-to-noise ratio of the sounding instrument signal through the signal quality evaluation algorithm, SNR greater than 30dB, signal strength, RSSI greater than -80dBm, and stability index greater than 0.9, confirm the stable signal, after the signal is stable, all workers evacuate the release point in an orderly manner; S6 Data recording phase one: combined with intelligent matching algorithm, through intelligent matching algorithm, the release time is accurate to seconds, the GPS accuracy of the location is 1 meter, the initial weather includes cloud cover, wind direction, wind speed, and air temperature, and the observation data are matched with a timestamp error of less than 0.5 seconds to establish a data traceability chain; S7 Data recording phase two: using the data storage and analysis module, the data processed by the intelligent matching algorithm is uploaded to the site cloud database, the storage capacity is greater than or equal to 10TB, the backup frequency is 1 hour, and the local encrypted backup file is retained at the same time, which provides support for subsequent astronomical meteorological data analysis.

[0005] Further, in step S1, the fusion calculation process of the terrain and wind speed modeling algorithm is: converting the DEM data of meteorological observation technology into terrain slope and slope direction parameters, spatially superimposing with historical wind speed data, calculating the annual average wind speed of each grid unit by weighted average method, dividing the turbulence intensity level by k value to meteorological observation technology mean clustering algorithm, and calculating the obstacle influence coefficient combined with buffer zone analysis.

[0006] Further, in step S2, the lightweight connecting line is a nylon rope with a diameter of 2mm and a breaking strength greater than 50N, which is fastened to the neck of the balloon through a special buckle, and a tension sensor is arranged in the middle of the connecting line to monitor the tension value in real time, and the tension value is stable at 10-15N.

[0007] Further, in step S3, the training process of the LSTM wind speed prediction algorithm is: taking the past 30 minutes of wind speed, pressure, and temperature data as input features, and the future 15 minutes of wind speed as output labels, using Adam optimizer for training, with 500 iterations, and the loss function is mean square error, and the model prediction error is less than 0.5m / s after training.

[0008] Further, in step S3, the monitoring data sources of the weather warning algorithm include radar echo data of the Xisheng Mountain regional meteorological station with an update frequency of 5 minutes, and ground lightning monitoring station with an update frequency of 1 minute, and the warning is triggered by threshold value judgment, and the warning information is pushed in real time through wireless command terminal.

[0009] Further, in step S4, the instruction transmission of the action synchronization algorithm adopts LoRa wireless communication protocol, the communication distance is greater than 50 meters, the instruction delay is less than 0.1 second, and the time difference of receiving instructions by 3 workers is less than 0.05 seconds.

[0010] Further, in step S4, the turbulence interference coping algorithm calculates the turbulence intensity as follows: based on the three-dimensional acceleration data collected by the radiosonde, the standard deviation of acceleration within 1 second is calculated, and when the standard deviation is greater than 0.5m / s², the turbulence intensity is greater than 0.3.

[0011] Furthermore, in step S5, the calculation logic of the signal quality assessment algorithm is as follows: perform Fourier transform on the signal received by the receiver, extract the main frequency component of the signal, calculate the ratio of the main frequency signal power to the noise power, and calculate the fluctuation range of the signal strength using the sliding window method.

[0012] Furthermore, in step S6, the data storage method of the intelligent matching algorithm is as follows: the matched data is stored in JSON format, uploaded to the site cloud database with a storage capacity of 10TB or more, and a scheduled backup strategy is adopted with a backup frequency of 1 hour. At the same time, encrypted backup files are retained locally.

[0013] Furthermore, in step S4, the radiosonde is a GTS1 model, equipped with a temperature sensor with an accuracy of ±0.1℃, a barometric pressure sensor with an accuracy of ±0.1hPa, a humidity sensor with an accuracy of ±2%RH, and a three-dimensional accelerometer with a sampling frequency of 10Hz, and a battery life of greater than or equal to 3 hours.

[0014] The technical solution provided by this invention has the following advantages compared with known public technologies: This invention improves the success rate of radiosonde launches in the complex environment of Saishiteng Mountain by using terrain and wind speed modeling algorithms for precise site selection, altitude and inflation volume correlation algorithms for reasonable inflation, LSTM-based wind speed prediction and weather warning algorithms for accurate release timing, and standardized collaborative processes and turbulence interference response algorithms to ensure successful launch operations. It effectively avoids launch failures caused by environmental factors, ensures the smooth progress of observation work, reduces the risk of balloon collisions with obstacles, avoids balloon bursts due to improper inflation volume, and the standardized multi-person collaborative process reduces the probability of radiosonde collisions with the ground and tangled connecting lines, thus effectively reducing the instrument wear rate. Stable signal transmission was ensured through the signal quality assessment algorithm, and the intelligent matching algorithm achieved accurate matching between the observation data and the initial release environment, reducing data errors. Meanwhile, the fluctuation amplitude of the observation data was reduced under the action of the turbulence interference response algorithm, providing more accurate and reliable data support for astronomical and meteorological research. At the same time, the wind speed prediction algorithm locked the release time in advance, which shortened the waiting time for each experiment and further improved the efficiency of observation operations, allowing more effective observation data to be obtained within a limited time. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0016] Fig. 1 This is a flowchart illustrating the overall technical process of the present invention. Fig. 2 This is a schematic diagram of the wind speed modeling algorithm of the present invention; Fig. 3 This is a schematic diagram of the correlation model between altitude and inflation volume of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0018] The present invention will be further described below with reference to embodiments.

[0019] like Figs. 1 to 3 As shown, a method for launching a weather balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain includes the following steps: S1 Site Selection Phase: Combining topography and wind speed modeling algorithms, the 10-meter resolution Digital Elevation Model (DEM) data of the Saishiteng Mountain observation area is fused with historical wind speed data of the past 5 years at a time resolution of 1 hour. The annual average wind speed, turbulence intensity, and obstacle influence coefficient of potential release points are calculated. Flat and open areas on the mountaintop with "annual average wind speed less than 4 m / s, turbulence intensity less than 0.2, and obstacle influence coefficient less than 0.1" are selected to avoid seasonal wind gaps. The fusion calculation process of topography and wind speed modeling algorithms is as follows: DEM data is converted into topographic slope and aspect parameters, spatially superimposed with historical wind speed data, and the annual average wind speed of each grid cell is calculated using a weighted average method. Turbulence intensity levels are divided using a k-value to mean clustering algorithm, and the obstacle influence coefficient is calculated in combination with buffer analysis. It should be noted that the digital elevation model (DEM) data of the Saishiteng Mountain observation area, with a resolution of 10 meters, was deeply fused and analyzed with historical wind speed data from the past 5 years, with a time resolution of 1 hour. Through the calculation model, the annual average wind speed, turbulence intensity, and obstacle influence coefficient of each potential release point were calculated. Based on these data, flat and open areas on the mountaintop that meet the conditions of "annual average wind speed less than 4 m / s, turbulence intensity less than 0.2, and obstacle influence coefficient less than 0.1" were automatically selected, effectively avoiding seasonal wind gaps, such as the western wind gap dominated by the westerly wind belt, to ensure the safety and stability of the release points. S2 preparation stage: combined with altitude, inflation amount correlation algorithm, according to the standard of "when the altitude is 3500-4000 meters, the balloon inflation diameter is 1.8-2 meters, when the altitude is 4000-4500 meters, the balloon inflation diameter is 1.6-1.8 meters, and when the altitude is greater than 4500 meters, the balloon inflation diameter is 1.5-1.6 meters", the sounding balloon is inflated, and at the same time, the instrument is checked to ensure that the sounding balloon has no damage, the battery of the sounding instrument has sufficient power and the sensor has no fault, the length of the light connecting line is 5-8 meters, the sounding instrument and the balloon are tied, and the connecting line is not wound; The light connecting line is a nylon rope with a diameter of 2 mm and a breaking strength of more than 50 N, which is tied to the neck of the balloon through a special buckle, and a tension sensor is arranged in the middle of the connecting line to monitor the tension value in real time, and the tension value is stable at 10-15 N; It should be noted that the "altitude, balloon diameter" corresponding model is constructed, for example, when the altitude is in the range of 3500-4000 meters, the balloon inflation diameter is set to 1.8-2 meters; When the altitude is 4000-4500 meters, the inflation diameter is 1.6-1.8 meters; When the altitude is greater than 4500 meters, the inflation diameter is 1.5-1.6 meters, according to the model, the balloon inflation amount can be dynamically and accurately adjusted, in the high altitude and low pressure environment, the pressure difference and the balloon lift can be balanced, at the same time, the length of the sounding instrument connecting line is 5-8 meters, which is the optimal value obtained by the turbulence interference simulation algorithm, under this length, the airflow interference intensity between the sounding instrument and the balloon is controllable, and the probability of the connecting line winding in the turbulence can be reduced, effectively ensuring the cooperative working stability of the sounding instrument and the balloon; S3 release timing judgment stage: combined with wind speed prediction algorithm and weather warning algorithm, using LSTM-based wind speed prediction algorithm, inputting real-time wind speed of observation station in the past 1 year, sampling frequency 1 minute, pressure, temperature data, predicting future 1 hour wind speed, error less than 0.5 m / s, locking the period when the wind speed is less than 3 m / s, combined with the weather warning algorithm, monitoring the precipitation within 30 kilometers, intensity greater than 0.5 mm / h, and lightning flash density greater than 1 times / 10 square kilometers, no adverse warning, then through the visual confirmation of flag light fluttering without unfolding and dry grass shaking without lodging, finally determine the release timing, if the release condition is not met, enter the waiting state until the algorithm output meets the requirements; The training process of LSTM wind speed prediction algorithm is: taking the past 30 minutes of wind speed, pressure, temperature data as input features, and the future 15 minutes of wind speed as output labels, using Adam optimizer for training, iteration times 500 times, loss function mean square error, after training, the model prediction error is less than 0.5 m / s, the monitoring data sources of the weather warning algorithm include radar echo data of Saisiteng mountain regional meteorological station with update frequency of 5 minutes and ground lightning monitoring station with update frequency of 1 minute, the warning is triggered through threshold value judgment, and the warning information is pushed in real time through wireless command terminal; It should be noted that the advanced wind speed prediction algorithm based on LSTM long short-term memory network is used, the real-time wind speed data of Xisheng Mountain observation station in the past 1 year is used, the sampling frequency is 1 minute, and the pressure data and temperature data collected synchronously are used to train the model. After learning and optimizing a large amount of data, the model can accurately predict the wind speed in the next 1 hour, the prediction error is controlled to be less than 0.5 m / s, and the ideal release time period of less than 3 m / s is locked in advance. Combined with the real-time weather warning algorithm, the algorithm receives the radar echo data and lightning monitoring data of Xisheng Mountain area in real time. When it is monitored that there is a shower within 30 kilometers, the precipitation intensity is greater than 0.5 mm / h, or there is lightning activity, and the cloud-to-ground lightning density is greater than 1 time / 10 square kilometers, the release delay warning can be automatically and timely triggered to ensure that the sounding balloon is not released under adverse weather conditions. At the same time, the double confirmation method of "visual judgment + algorithm verification" is used to determine the release time. When the flag is slightly fluttering and not unfolding, the dry grass is slightly shaking and no obvious lodging is observed, the wind speed is less than 3 m / s is preliminarily judged by visual judgment, and the wind speed is less than 3 m / s in the next 15 minutes is output by the wind speed prediction algorithm, and no adverse weather warning is fed back by the weather warning algorithm. Finally, the release time is confirmed, which can further improve the accuracy of the release time judgment; S4 Multi-person cooperative release stage: combined with the action synchronization algorithm and the turbulence interference response algorithm, the action synchronization algorithm is used to send synchronization instructions to 3 workers through a wireless instruction terminal, the time error is less than 0.1 second, 1 person supports the instrument, and the pushing instrument force is 5 to 10 N, which is fed back through the force sensor, 2 people lift the balloon bottom, and the synchronization hand is released after the unified instruction. The instrument supporting personnel gently pushes the sounding instrument, and the balloon ascends initially from 0 to 50 meters. Through the turbulence interference response algorithm, based on the acceleration data of the sounding instrument with a sampling frequency of 10 Hz, the turbulence intensity is judged. If it is greater than 0.3, the pushing instrument time is extended to 2 to 3 seconds. The instruction transmission of the action synchronization algorithm uses LoRa wireless communication protocol, the communication distance is greater than 50 meters, the instruction delay is less than 0.1 second, and the time difference of 3 workers receiving instructions is less than 0.05 seconds. The turbulence intensity calculation method of the turbulence interference response algorithm is: based on the three-dimensional acceleration data collected by the sounding instrument, the acceleration standard deviation in 1 second is calculated. When the standard deviation is greater than 0.5 m / s², the turbulence intensity is greater than 0.3; It should be noted that the multi-person cooperation process is based on a well-designed action synchronization algorithm. Through the wireless command terminal, a unified "preparation-release" command is sent to 3 workers, with a time synchronization error of less than 0.1 seconds, ensuring that the timing of the lifting personnel releasing their hands is completely consistent. During the operation, the force sensor provides real-time feedback on the force applied to the balloon, and the force applied to the balloon is accurately controlled at 5-10N, effectively preventing the balloon from tilting more than 10°. In the initial stage of balloon ascent, i.e. the key stage of 0-50 meters, a turbulence disturbance algorithm is introduced. This algorithm uses acceleration data collected by the sounding instrument in real time, with a sampling frequency of 10Hz, to accurately determine the turbulence intensity. When the turbulence intensity exceeds 0.3, the "slow push instrument" operation prompt is automatically triggered, and the balloon ascent trajectory is effectively reduced by 5 meters, ensuring the stability of the balloon in the initial stage of ascent. S5 signal confirmation and evacuation phase: combined with the signal quality evaluation algorithm, the signal-to-noise ratio of the sounding instrument signal is calculated through the signal quality evaluation algorithm. When SNR is greater than 30dB, RSSI is greater than -80dBm, and stability index is greater than 0.9, the signal is confirmed to be stable, and all workers are evacuated from the release point in an orderly manner. The calculation logic of the signal quality evaluation algorithm is as follows: Fourier transform is performed on the signal received by the receiver, the main frequency component of the signal is extracted, and the ratio of the main frequency signal power to the noise power is calculated. The fluctuation range of the signal strength is calculated by the sliding window method. S6 data recording phase one: combined with the intelligent matching algorithm, the release time is accurately matched to seconds, the GPS accuracy of the location is 1 meter, the initial weather including cloud cover, wind direction, wind speed, and temperature is matched with the observation data with a timestamp matching error of less than 0.5 seconds, and the data traceability chain is established. The data storage method of the intelligent matching algorithm is as follows: the matched data is stored in JSON format and uploaded to the site cloud database with a storage capacity of greater than or equal to 10TB. The backup frequency is 1 hour, and the local encrypted backup file is retained at the same time; S7 data recording phase two: using the data storage and analysis module, the data processed by the intelligent matching algorithm is uploaded to the site cloud database with a storage capacity of greater than or equal to 10TB. The backup frequency is 1 hour, and the local encrypted backup file is retained at the same time, providing support for subsequent astronomical meteorological data analysis. The sounding instrument is GTS1 type, equipped with temperature sensor with accuracy ±0.1℃, pressure sensor with accuracy ±0.1hPa, humidity sensor with accuracy ±2%RH, and three-dimensional acceleration sensor with sampling frequency 10Hz, battery endurance time greater than or equal to 3 hours; It should be noted that through the advanced signal quality evaluation algorithm, the sounding instrument signal received by the simple receiver is comprehensively and deeply analyzed. The algorithm calculates the signal-to-noise ratio, signal strength and signal stability index of the signal. When the signal-to-noise ratio is greater than 30dB, the signal strength is greater than-80dBm, and the signal stability index is greater than 0.9, the sounding instrument signal is confirmed to be stable, which provides reliable guarantee for subsequent data transmission and analysis. In the data recording link, an intelligent matching algorithm is introduced. The release time is accurate to seconds, the release location coordinates can reach an accuracy of 1 meter through GPS positioning, and the initial weather parameters including cloud cover, wind direction, wind speed, air temperature, and sampling frequency of 1 minute are matched with the observation data transmitted back by the sounding instrument through accurate time stamping. The matching error is controlled to be less than 0.5 seconds. At the same time, a perfect data traceability chain is established to ensure that each set of observation data can be traced back to the initial release environment, greatly improving the reliability and traceability of the data.

[0020] The working principle of the present application is as follows: in the selected point stage, by means of the terrain-wind speed modeling algorithm, the digital elevation model DEM data with a resolution of 10 meters in the Saishe Mountain observation area is fused and analyzed with the historical wind speed data with a time resolution of 1 hour in the past 5 years. The DEM data is converted into terrain slope, slope direction and other parameters, which are spatially superimposed with the historical wind speed data. The annual average wind speed of each grid unit is calculated by weighted average method. The K value to mean clustering algorithm is used to divide the turbulence intensity level. The obstacle influence coefficient is calculated by combining buffer analysis. According to the calculation results, the flat and open area on the mountain top with an annual average wind speed less than 4 meters / second, a turbulence intensity less than 0.2 and an obstacle influence coefficient less than 0.1 is selected as the release point, so as to avoid seasonal wind outlets and terrain turbulence areas, ensure the safety and stability of the release point, and reduce the risk of the balloon being blown by strong wind towards the obstacle in the initial stage of release. In the preparation stage, in the high-altitude low-pressure environment of Saishe Mountain, the altitude is closely related to the inflation amount of the balloon. The algorithm inflates the balloon according to the corresponding interval relationship that the inflation diameter is 1.8-2 meters when the altitude is 3500-4000 meters, the inflation diameter is 1.6-1.8 meters when the altitude is 4000-4500 meters, and the inflation diameter is 1.5-1.6 meters when the altitude is greater than 4500 meters. At the same time, the integrity of the sounding balloon is checked to ensure that there is no damage. The battery capacity, temperature sensor, air pressure sensor, humidity sensor and three-dimensional acceleration sensor of the sounding instrument are comprehensively checked and calibrated to ensure normal operation of the instrument. A nylon light connecting line with a diameter of 2mm and a breaking strength greater than 50N is used. The length is 5-8 meters. The sounding instrument and the balloon are tied by a special stainless steel buckle. A tension sensor is arranged in the middle of the connecting line to stabilize the tension at 10-15N, prevent the connecting line from winding, lay a foundation for stable balloon ascension and accurate data collection. In the release opportunity judgment stage, the LSTM-based wind speed prediction algorithm is used. The real-time wind speed, pressure, and temperature data of the observation site in the past year are used as input for model training. The past 30 minutes of wind speed, pressure, and temperature data are used as input features, and the future 15 minutes of wind speed are used as output labels. The Adam optimizer is used for training 500 times, and the loss function mean square error is less than 0.02, so as to accurately predict the wind speed in the next hour and lock the ideal period when the wind speed is less than 3 meters per second; At the same time, the weather warning algorithm receives radar echo data updated every 5 minutes and ground lightning flash data updated every 1 minute from the regional meteorological station of Sishenteng Mountain. When the precipitation intensity is greater than 0.5mm / h or the ground lightning flash density is greater than 1 time / 10 square kilometers within 30 kilometers, the warning is triggered, and the release is not suitable. When the wind speed prediction meets the requirements and there is no adverse weather warning, combined with the visual judgment of the slight flag fluttering and the small amplitude of the dry grass, the release opportunity is finally determined; In the multi-person cooperative release stage, the action synchronization algorithm sends unified instructions to 3 workers through LoRa wireless communication protocol. The communication distance is greater than 50 meters, the instruction delay is less than 0.1 second, and the time difference of the workers receiving the instructions is less than 0.05 seconds. One person holds the middle part of the sounding instrument with both hands, and according to the real-time feedback of the pushing force data of the bottom force sensor of the sounding instrument to the field control terminal, the pushing force is accurately controlled at 5-10N. Two people hold the bottom of the balloon with their palms upwards to ensure that the balloon axis is perpendicular to the ground, which can be calibrated by a laser level to ensure that the inclination angle is less than 5°; After the unified instruction is issued, the lifting personnel release their hands synchronously, and the sounding instrument is pushed by the holding personnel. In the initial stage of balloon ascension, 0-50 meters, the turbulence interference coping algorithm calculates the standard deviation of acceleration within 1 second based on the three-dimensional acceleration data collected by the sounding instrument. When the standard deviation is greater than 0.5m / s², it is determined that the turbulence intensity is greater than 0.3, and the sounding instrument pushing time is automatically extended to 2-3 seconds through the terminal to reduce the influence of turbulence on the balloon ascending trajectory and ensure that the balloon vertical rising deviation is controlled within 5 meters, realizing stable ascension; After release, the signal quality evaluation algorithm processes the sounding instrument signal received by the simple receiver. Fourier transform is performed on the received signal, and the signal component with a main frequency of 403MHz is extracted. The signal-to-noise ratio, signal strength, and signal stability index are calculated. When the signal-to-noise ratio is greater than 30dB, the signal strength is greater than -80dBm, and the stability index is greater than 0.9, the sounding instrument signal is confirmed to be stable, and the workers orderly evacuate the release point; Subsequently, the intelligent matching algorithm will release the time, accurate to seconds, release location coordinates, GPS positioning accuracy up to 1 meter, initial weather parameters, including cloud cover, wind direction, wind speed, temperature, collected by the site automatic weather station every 1 minute, using the observation data returned by the sounding instrument, according to the precise timestamp for automatic matching, and the data is stored in JSON format, synchronized to the site cloud database with storage capacity greater than or equal to 10TB, using RAID5 redundancy backup, backup frequency 1 hour, while retaining AES-256 encrypted backup files on the local terminal, establishing a complete data traceability chain, providing reliable and accurate data support for subsequent astronomical meteorological data analysis.

[0021] The above examples are only used to illustrate the technical solutions of the present application, but not to limit it; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that the technical solutions recorded in the foregoing examples can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain, characterized in that, Includes the following steps: S1 Site Selection Phase: Combining topography and wind speed modeling algorithms, the digital elevation model (DEM) data of the Saishiteng Mountain observation area with a resolution of 10 meters is fused with historical wind speed data of 5 years with a time resolution of 1 hour using near-meteorological observation technology. The annual average wind speed, turbulence intensity, and obstacle influence coefficient of potential release points are calculated. Flat and open areas on the mountain top with "annual average wind speed less than 4 m / s, turbulence intensity less than 0.2, and obstacle influence coefficient less than 0.1" are selected to avoid seasonal wind gaps. S2 Preparation Phase: Combining altitude and inflation volume correlation algorithms, the weather balloon is inflated according to the meteorological observation technology standard that "at an altitude of 3500 to 4000 meters, the balloon inflation diameter is 1.8 to 2 meters; at an altitude of 4000 to 4500 meters, the balloon inflation diameter is 1.6 to 1.8 meters; and at an altitude greater than 4500 meters, the balloon inflation diameter is 1.5 to 1.6 meters". At the same time, the instrument is checked to ensure that the weather balloon is undamaged, the radiosonde's battery is fully charged and the sensors are fault-free. A lightweight connecting line of 5 to 8 meters in length is used to tie the radiosonde and the balloon tightly, ensuring that the connecting line is not tangled. S3 Release Timing Judgment Stage: Combining wind speed prediction algorithm and weather warning algorithm, the wind speed prediction algorithm based on LSTM meteorological observation technology is used. The real-time wind speed of the observation station for the past year is input, with a sampling frequency of 1 minute, air pressure and temperature data, to predict the wind speed for the next hour. The error is less than 0.5 m / s. The time period with wind speed less than 3 m / s is locked. Combined with the weather warning algorithm, precipitation within 30 kilometers is monitored. The intensity is greater than 0.5 mm / h, and the lightning density is greater than 1 time / 10 square kilometers. If there is no adverse warning, visual confirmation is obtained by slightly waving the flag without unfolding and the withered grass swaying slightly without falling over. Finally, the release timing is determined. If the release conditions are not met, the system enters a waiting state until the algorithm outputs a timing that meets the requirements. S4 Multi-person Collaborative Release Phase: Combining the action synchronization algorithm and the turbulence interference response algorithm, the action synchronization algorithm sends synchronization commands to 3 staff members via wireless command terminal with a time error of less than 0.1 seconds. One person holds the device and pushes it with a force of 5 to 10N. Based on the force sensor feedback, two people support the bottom of the balloon and release their hands synchronously after a unified command. The person holding the device gently pushes the radiosonde. In the initial stage of balloon ascent, from 0 to 50 meters, the turbulence interference response algorithm uses the radiosonde acceleration data with a sampling frequency of 10Hz to judge the turbulence intensity. If it is greater than 0.3, the pushing time is extended to 2 to 3 seconds. S5 Signal Confirmation and Evacuation Phase: Combining the signal quality assessment algorithm, the signal-to-noise ratio (SNR) of the radiosonde signal is calculated. If the SNR is greater than 30dB, the signal strength (RSSI) is greater than -80dBm, and the stability index is greater than 0.9, the signal is confirmed to be stable. After the signal is stable, all personnel evacuate the release point in an orderly manner. S6 Data Recording Phase 1: Combining intelligent matching algorithms, the release time is accurate to the second, the GPS location accuracy is up to 1 meter, and the initial weather, including cloud cover, wind direction, wind speed, and temperature, is matched with the observation data according to the timestamp with an error of less than 0.5 seconds, thus establishing a data traceability chain; S7 Data Recording Phase Two: Using the data storage and analysis module, the data processed by the intelligent matching algorithm is uploaded to the site cloud database with a storage capacity of ≥10TB. A scheduled backup strategy is adopted with a backup frequency of 1 hour. At the same time, encrypted backup files are stored locally to support subsequent astronomical and meteorological data analysis.

2. The method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain according to claim 1, characterized in that, In step S1, the fusion calculation process of the terrain and wind speed modeling algorithm is as follows: the meteorological observation technology DEM data is converted into terrain slope and aspect parameters, and spatially superimposed with historical wind speed data. The annual average wind speed of each grid unit is calculated using the weighted average method. The turbulence intensity level is divided by the clustering algorithm from k value to meteorological observation technology mean. The obstacle influence coefficient is calculated in combination with buffer analysis.

3. The method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain according to claim 1, characterized in that, In step S2, the lightweight connecting line is a nylon rope with a diameter of 2mm and a breaking strength greater than 50N. It is tied to the neck of the balloon with a special buckle, and a tension sensor is set in the middle of the connecting line to monitor the tension value in real time. The tension value is stable at 10-15N.

4. The method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain according to claim 1, characterized in that, In step S3, the training process of the LSTM wind speed prediction algorithm is as follows: the wind speed, air pressure and temperature data of the past 30 minutes are used as input features, the wind speed of the next 15 minutes is used as the output label, the Adam optimizer is used for training, the number of iterations is 500, the loss function is the mean squared error, and the model prediction error is less than 0.5 m / s after training.

5. The method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain according to claim 1, characterized in that, In step S3, the monitoring data sources for the weather warning algorithm include radar echo data from the Saishiteng Mountain area meteorological station, updated every 5 minutes, and ground lightning data from the ground lightning monitoring station, updated every 1 minute. Warnings are triggered by threshold judgments, and warning information is pushed in real time through a wireless command terminal.

6. The method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain according to claim 1, characterized in that, In step S4, the instruction transmission of the action synchronization algorithm adopts the LoRa wireless communication protocol, with a communication distance of more than 50 meters and an instruction delay of less than 0.1 seconds, ensuring that the time difference between the three staff members receiving the instruction is less than 0.05 seconds.

7. The method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain according to claim 1, characterized in that, In step S4, the turbulence intensity calculation method of the turbulence interference response algorithm is as follows: based on the three-dimensional acceleration data collected by the radiosonde, calculate the standard deviation of acceleration within 1 second. When the standard deviation is greater than 0.5 m / s², the corresponding turbulence intensity is greater than 0.

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8. A method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain, as described in claim 1, is characterized in that... In step S5, the calculation logic of the signal quality assessment algorithm is as follows: perform Fourier transform on the signal received by the receiver, extract the main frequency component of the signal, calculate the ratio of the main frequency signal power to the noise power, and calculate the fluctuation range of the signal strength using the sliding window method.

9. A method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain, as described in claim 1, is characterized in that... In step S6, the data storage method of the intelligent matching algorithm is as follows: the matched data is stored in JSON format, uploaded to the site cloud database with a storage capacity of 10TB or more, and a scheduled backup strategy is adopted with a backup frequency of 1 hour. At the same time, encrypted backup files are retained locally.

10. A method for launching a sounding balloon in a high-wind environment suitable for astronomical and meteorological observations at Saishiteng Mountain, as described in claim 1, is characterized in that... In step S4, the radiosonde is a GTS1 model, equipped with a temperature sensor with an accuracy of ±0.1℃, a barometric pressure sensor with an accuracy of ±0.1hPa, a humidity sensor with an accuracy of ±2%RH, and a three-dimensional accelerometer with a sampling frequency of 10Hz. The battery life is greater than or equal to 3 hours.

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