367 results about "Atmospheric pressure" patented technology

The invention discloses a vehicle idling start and stop control system and method. The control system judges whether a vehicle has idling start and stop conditions by monitoring the water temperatureof an engine, the capacity of a storage battery, a safety belt and other information, judges whether the vehicle has conditions of stopping the engine by monitoring the rotating speed of the engine, the speed of the vehicle, the brake air pressure and other conditions, and judges whether the vehicle has conditions of starting the engine by monitoring the gear of a gearbox, the speed of the vehicle, a hand brake and other information. When the relevant conditions are met, start and stop work signals are sent to the engine though a CAN bus. In order to guarantee the reliability of frequent startand stop of the engine, the system strengthens flywheel gear rings of a starter and the engine. In order to ensure that the battery does not lose power, a storage battery capacity sensor is added tothe system on the basis of increasing the capacity of the storage battery, and the idling start and stop are allowed when the state of charge (SOC) of the storage battery satisfies a safe starting threshold. The idling start and stop control system has advantages of low cost and high reliability, and is especially suitable for commercial vehicles.

The invention discloses a constant-temperature and constant-humidity test box temperature control system based on a multistage PID algorithm and a control method thereof. The constant-temperature and constant-humidity test box temperature control system comprises an environmental parameter detection module, an in-box parameter detection module and a multistage PID controller, wherein the environmental parameter detection module is used for collecting temperature, humidity and air pressure data outside a test box in real time; the in-box parameter detection module is used for collecting multi-dimensional environmental parameters inside the test box; when the failure of any sensor is detected, starting a fault self-diagnosis module, replacing the data of the failure sensor with a data interpolation method of a side sensor, and recording the deviation compensation amount at the same time. A multi-stage PID control architecture is adopted, and feedforward compensation, parameter adaptive optimization and fault redundancy strategies are combined, so that high-precision and anti-interference control of the temperature and humidity of the test box is realized.

The invention discloses a high-precision flow online monitoring device and method for a siltation section, and belongs to the technical field of hydrological monitoring. The device comprises a sensing terminal, an edge terminal and a mounting mechanism, the sensing terminal is integrated with an upper and lower section layered speed measurement module, an underwater distance measurement module, a first absolute pressure type water level measurement module and an attitude and temperature sensor, and vertical section flow velocity data is obtained by receiving water body reflection signals in a time-sharing manner; and the dynamic deposition section area is corrected in real time in combination with ultrasonic ranging. And the edge terminal compensates water level measurement data by using atmospheric pressure, and calculates the flow through fusion of a telemetering module. The installation mechanism supports fixed or telescopic installation, and the height of the installation mechanism is automatically adjusted according to the distance between a deposition layer and equipment. The method comprises the steps of dynamically correcting the section, calculating the flow through layered integration and compensating errors of multiple sensors, the problems of large area deviation, high operation and maintenance cost and the like caused by sedimentation in a traditional flow measurement technology are solved, and high-precision online monitoring under the high-sand-content complex flow state is achieved.

The invention provides a marine meteorological data quality control method based on a cross-parameter correlation network, which belongs to the technical field of marine meteorology, and comprises the following steps: constructing a cross-parameter correlation network model comprising an air temperature and air pressure correlation rule, a humidity and air temperature linear correlation rule and a wind speed and air pressure gradient extraction correlation rule; a sliding window algorithm is adopted to calculate a correlation coefficient in real time and identify correlation abnormity, a multivariate abnormity detection mechanism of four dimensions of parameter threshold overrun, spatio-temporal change rate abnormity, probability density distribution offset and correlation verification failure is established, a fuzzy comprehensive evaluation method is adopted to calculate a comprehensive abnormity index, and data abnormity is judged. And the authenticity of the abnormal data is confirmed in combination with a multi-sensor cross validation mechanism, and finally the abnormal data is restored by adopting a virtual sensor data reconstruction algorithm based on correlation network reverse calculation, so that the technical problem of poor abnormal data detection effect in the prior art is solved.

The invention discloses a typhoon wave height prediction method based on a deep learning MOE-Transform model, and the method comprises the following specific steps: collecting historical typhoon data of a research region, and constructing a virtual typhoon data set in combination with a central pressure difference formula; processing the historical and virtual typhoon data sets through a Holland typhoon empirical model and a storm growth relation to obtain a wind field, an air pressure field and a significant wave height field; correcting the field data by using an error model on the basis of the ERA5 data set to form a typhoon space-time fusion database containing meteorological data, the significant wave height field and typhoon data; and training and testing the MOE-Transform model to obtain a typhoon wave significant wave height prediction model for typhoon wave height prediction. According to the method, the multi-task adaptability and generalization ability are improved, and the precision and timeliness of typhoon wave height prediction are improved.

The embodiment of the invention discloses a water-gas interface greenhouse gas flux automatic monitoring system and a distribution prediction method. The system comprises a wind speed sensor and an air pressure and temperature sensor which are respectively used for collecting the wind speed of air at a monitoring point, the atmospheric pressure and the Kelvin air temperature; the infrared sensor is used for collecting the content of CO2, CH4 and N2O in the air of the monitoring point; the acidity sensor and the temperature sensor are respectively used for collecting the pH value and the centigrade water temperature of monitoring point water; the carbon dioxide sensor is used for collecting the concentration of bicarbonate in water at a monitoring point; the methane sensor and the nitrous oxide sensor are respectively used for collecting the contents of greenhouse gases CH4 and N2O dissolved in the monitoring point water; and the calculation module is used for calculating the flux of the greenhouse gas on the water-gas interface. According to the embodiment of the invention, the water-gas interface flux of various greenhouse gases under actual conditions can be accurately monitored.

The invention relates to the technical field of pipeline noise elimination, in particular to a precision filter sealing performance detection method and device.The method comprises the steps that in the pressurization and pressure maintaining process of different temperature grades, air pressure is collected, and the real air pressure sequence, the standard air pressure sequence, the pressurization time period and the pressure maintaining time period of the same temperature grade are determined; determining the temperature influence degree of the precision filter; leakage sub-time periods are divided from the pressurization time period and the pressure maintaining time period, and the intermittent leakage degree corresponding to the same temperature grade is determined according to the duration of all the leakage sub-time periods divided according to the same temperature grade and the duration of the pressurization time period and the duration of the pressure maintaining time period; and combining the difference between all the temperature grades and the actual temperature for detecting the sealing performance of the precision filter and the temperature influence degree of the precision filter to finish the sealing performance detection of the precision filter. The precision filter sealing performance detection accuracy can be improved.

The invention relates to the technical field of three-dimensional real-time wind speed measurement, and discloses a large-span roof three-dimensional ultrasonic anemometer and a measurement method thereof, and the method comprises the steps: building a three-dimensional coordinate system through laser ranging, and analyzing and compensating installation errors; an initial calibration coefficient is generated through a self-inspection and optimization algorithm, and the initial calibration coefficient is compared and analyzed with a standard instrument for initial calibration; ultrasonic pulse emission is controlled, full-path scanning and redundancy measurement of all axes are completed, signal quality is improved through multi-modal signal processing detection, and abnormal values are eliminated through weighted median values; the sound velocity is corrected based on real-time temperature data, the influence of humidity and air pressure on the sound velocity is adjusted through a nonlinear regression model, and a Reynolds stress correction term is introduced to compensate for sound wave path bending in an eddy current field; a three-dimensional turbulence intensity distribution diagram is constructed by fusing ultrasonic and LiDAR data, meteorological parameters are calculated, an extreme weather event is early warned by using a machine learning model, a visual three-dimensional wind speed field is provided through a cloud platform, and a potential risk area is identified.

The invention discloses a control method for defrosting of a parallel flow evaporator, which comprises the following steps of: constructing a multi-dimensional state sensing network, constructing a three-dimensional state sensing matrix by utilizing a distributed temperature sensor array on the surface of an evaporator coil, an air inlet humidity sensor and an inlet and outlet differential pressure type pressure sensor, and acquiring information such as temperature distribution, environment humidity and air pressure difference; through dynamic threshold self-adaptive judgment, based on an environment temperature field, the historical temperature of an evaporator and an icing critical temperature field calculated by a time sequence prediction model, the defrosting triggering condition is judged by combining humidity and an air pressure difference change gradient field; gradient type energy injection defrosting is adopted, in the first-stage defrosting process, the refrigerant flow is adjusted through a proportional electromagnetic valve to conduct directional defrosting, and in the second-stage defrosting process, a compressor is closed, a fin gap shape memory alloy heating network is activated, and latent heat of a phase change material is released to conduct uniform defrosting. And performing multi-physical field cooperative regulation and control, constructing a coupling model, and adjusting the heating power and pulse modulation duty ratio sequence.

The invention relates to the technical field of meteorological observation, in particular to a parameter measurement method and device based on a dual-band mode, equipment and a storage medium. Generating a dual-band excitation signal according to the aligned sine wave signal; analyzing the echo signal according to a preset gain coefficient, a time difference method and a preset attitude compensation formula to obtain a reconstructed quasi-unipolar pulse, an actual wind speed, a horizontal wind direction angle, a pitch angle, a three-dimensional wind speed vector, a roll angle and a real wind direction; acquiring real-time air pressure, and correcting a preset standard state sound velocity according to a preset sound velocity correction formula and the real-time air pressure to obtain a corrected sound velocity; according to the scheme, a dual-band signal attached to a medium is generated, after efficient transmission analysis, high-resolution pulses and multi-dimensional wind field parameters are obtained by means of gain, a time difference method, attitude compensation and the like, the sound velocity is corrected in combination with air pressure, comprehensive, accurate and rapid updating of data are considered, and the measurement reliability is improved.

The invention provides an active and passive combined microwave remote sensing detection method for earth surface air pressure and air pressure profile, which comprises the following steps: by combining a satellite-borne / airborne millimeter wave differential absorption radar and a satellite-borne / airborne microwave radiometer and utilizing oxygen differential absorption measurement, obtaining accurate land / ocean surface air pressure data; and the air pressure profile is further obtained by combining temperature and humidity profile data measured by a satellite-borne / airborne microwave radiometer. Compared with the prior art, the method has the advantages that active and passive microwaves are adopted for combined detection, detection information obtained by a microwave radiometer is complemented, calculation of the surface pressure is enhanced, and the surface pressure inversion precision is improved; according to the method, the surface pressure value can be obtained, and the atmospheric pressure profile can also be obtained. According to the method, accurate surface pressure detection can be realized, and the atmospheric pressure profile can be further deduced by combining the temperature profile and the humidity profile observed by the microwave radiometer.

The invention belongs to the technical field of underwater measurement, and discloses a test probe underwater depth automatic positioning method and system, and the method comprises the steps: collecting an absolute water pressure value of a current underwater environment, and carrying out the calculation of a hydrostatic pressure value through combining with water surface reference air pressure data; meanwhile, acoustic signals from the water surface base station are received, response is returned, and the round-trip propagation time of sound waves in the water body is measured and obtained; collecting water body temperature data and salinity change data, estimating density information of the current water body, and converting a hydrostatic pressure value into a pressure depth value; calculating an average sound wave propagation speed by adopting an empirical sound velocity model, and calculating an acoustic depth value of the probe in combination with back-and-forth propagation time of sound waves in the water body; the depth positioning precision and stability of the underwater probe in a complex environment are effectively improved, and high-reliability and high-precision underwater depth automatic positioning is realized.

The invention discloses a wind field downscaling method based on physical constraint and artificial intelligence, and relates to the technical field of meteorological numerical forecasting, and the method comprises the steps: obtaining an input data set which comprises topographic data, low-resolution forecasting data and observation data; feature extraction and data processing are carried out on the input data set to obtain a training data set, the training data set is utilized to train a neural network model fused with the attention mechanism, and a loss function of the neural network model comprises physical constraint terms. According to the method, feature information of the terrain and the air pressure field is brought into model input, feature extraction is carried out on the air pressure field through principal component analysis, and the adaptability of the model to different terrain and weather backgrounds is improved.

The invention relates to the technical field of artificial intelligence and aviation technology crossing, and discloses a multi-environment aircraft trajectory prediction method based on a space-time self-attention mechanism, and the method comprises the steps: obtaining historical trajectory data of a target aircraft and synchronous meteorological data, namely wind speed, wind direction and air pressure; s2, extracting time sequence features of the historical trajectory through a time-space self-attention network (TSAN), wherein the time sequence features specifically comprise local time sequence feature extraction by adopting a time convolution block; according to the multi-environment aircraft trajectory prediction method based on the space-time self-attention mechanism, the prediction precision is remarkably improved, on a TrajAir high-dynamic data set, the average displacement error (ADE) is reduced by 27.7% to 0.68 m, and the final displacement error (FDE) is reduced by 26.7% to 1.37 m. The FDE is reduced to 1.29 m (39.7%) from 2.14 m in severe convection weather, and the problem of track abrupt change caused by wind direction jump of a traditional model is effectively solved.

The invention discloses a space grid method for interconversion of geodetic height and barometric height, and belongs to the technical field of aviation navigation and geographic information systems. According to the method, the mutual conversion of geodetic height and barometric height is realized through establishing a global space-time grid reference system, establishing a space-time grid data base, converting barometric height to geodetic height, inversely converting the geodetic height to the barometric height, and carrying out reference conversion, data fusion and grid compression between the barometric heights. According to the method, the vertical availability of the height estimation value obtained through air pressure measurement within the height range within the stratosphere can be improved, the method is suitable for most weather conditions, the height estimation value with the precision reaching the ten-meter level can be achieved, and compared with an existing ISA-based method, the precision is higher, the application range is wider, and the application range is wider. The method can effectively improve the reliability of flight control systems of various aircrafts, and has wide application prospects in urban air traffic operation.

The invention discloses an offshore floating type low-altitude waveguide all-weather detection method and system, and relates to the technical field of marine environment monitoring and electronic information engineering.The method comprises the steps that the current weather condition is judged according to a rain intensity sensor, a miniature weather station, a visibility sensor and an infrared cloud measurement sensor; obtaining a temperature and humidity value range according to the current weather condition, and adding liquid water for correction according to the weather condition; a simulated brightness temperature is obtained according to a MonoRTM model by combining an air pressure profile constructed by sea surface air pressure and a pressure height formula; designing a multi-objective genetic inversion algorithm, constructing an objective function, and when the objective function obtains a minimum value, obtaining an inverted atmospheric parameter profile group; and according to the atmospheric parameter profile group, calculating an atmospheric refractive index profile, judging whether a low-altitude waveguide occurs or not, and uploading a result to a shore station data management center. According to the invention, the atmospheric absorption coefficient is corrected according to different weathers, and all-weather and high-precision monitoring of the low-altitude waveguide on the offshore floating platform is realized.

The invention provides an attitude control method and system for a mixed target. The method comprises the following steps: predicting a scene change trend by using a pre-trained neural network model according to topographic data and temperature and humidity data to obtain a scene change trend vector, and adjusting parameters of a target hybrid model according to the scene change trend vector; calculating an air pressure target value through the target hybrid model after parameter adjustment; according to the air pressure target value, the gas injection or release rate of the two-way pressure adjusting equipment of the mixed target is controlled until the fluctuation amplitude of the air pressure actual value after pressure adjustment is smaller than a preset fluctuation amplitude threshold value and the stable duration is larger than a preset duration threshold value, and the two-way pressure adjusting equipment comprises an air pump and a pressure release valve; and controlling the attitude of the mixed target according to the actual air pressure value after the control is completed. According to the technical scheme provided by the invention, the attitude of the mixed target is controlled through the actual air pressure value of the mixed target, and precision and stability can be realized in a complex environment.

The invention discloses a shield front karst fissure grouting plugging method based on feedforward identification and directional regulation and control, which comprises the steps of front geological information acquisition, target area identification, grouting path planning, parameter adaptive regulation and control, directional grouting execution and plugging effect feedback. Feature fusion processing of geometric features of the cavity region from a time domain to a frequency domain is realized, geological types and features of the cavity region are analyzed in combination with data, and remarkable reduction of cavity three-dimensional coordinate positioning errors and remarkable improvement of boundary recognition precision are realized; in the drilling process, the boundary of the cavity is sensed in real time, synchronous grouting and air exhaust are achieved through automatic deviation correction of the posture adjusting mechanism and the double-through-hole design, air pressure fluctuation in the cavity is controlled within a safe and stable range, and the risk of cavity collapse caused by air pressure changes is effectively prevented.

A thermal resistance measurement result uniformization device for a heat dissipation module, including: a control unit for storing an executable thermal resistance measurement logic; a wind tunnel having a casing, a wind tunnel blower and a flow rate measurement unit, allowing air flow rate inside the wind tunnel to be fixed; a heater attached to a heat dissipation module under test and having a fixed heating power; a heating sensor for sensing the temperature of the heater block; and an environment sensor for sensing ambient temperature, relative humidity and atmospheric pressure. The thermal resistance measurement logic has equations, namelyRCVT=R×hhSTP,and⁢ h=WA⁢Δ⁢T,Δ⁢T=TC-TA,and⁢ R=Δ⁢TW,and calculates converted thermal resistance with the equations. The control unit executes the thermal resistance measurement logic to obtain the converted thermal resistance of the heat dissipation module under test.

The invention provides a height measurement method and device, and the method comprises the following steps: S1, obtaining sample point data, the sample point data comprising feature data and label data of a sample point, the feature data comprising air pressure data, temperature data, humidity data and wind speed data of the sample point at any moment, and the label data comprising altitude data of the sample point, acquiring multiple groups of sample point data to form a sample data set; s2, constructing an initialized prediction model based on a LightGBM framework, and training the initialized prediction model based on the sample data set to obtain a final prediction model; and S3, acquiring air pressure data, temperature data, humidity data and wind speed data of a to-be-measured point at a certain moment, and inputting the data into the final prediction model to obtain an altitude prediction value of the to-be-measured point. According to the height measurement method and device provided by the invention, the altitude prediction model is established by using the LightGBM framework, the altitude is measured, and the accuracy of altitude measurement can be improved.

The invention provides an atmospheric particulate water-soluble ion analysis instrument calibration system and calibration method, and belongs to the technical field of atmospheric particulate measurement. The system comprises an atmospheric environment simulation measurement device and a portable calibration device. The atmospheric environment simulation measurement device simulates actual environmental conditions through an aerosol mixing cabin in a thermotank, and is equipped with various sensors to monitor temperature, air pressure and humidity. The portable calibration device is internally provided with an aerosol generator, a constant-speed diverter, a particle sensor and the like, and an aerosol sample can be generated on site for calibration. The calibration method comprises two parts of constructing a standard parameter database and performing field calibration, and the calibration precision is ensured by comparing a measured value of the particulate matter sensor with a particle size spectrum. According to the calibration system and the calibration method for the atmospheric particulate water-soluble ion analysis instrument, the problems that traditional calibration equipment is large in size and cannot be calibrated on site are solved, and reliable technical support is provided for on-site calibration of the atmospheric particulate water-soluble ion analysis instrument.

A system for estimating the altitude of a cellular telephone or other wireless device based on a measurement of barometric pressure. The system cleverly uses cellular telephones at various locations to assist in generating an accurate estimate of a reference barometric pressure p0. For example, the system has a cellular telephone near the location of interest make two measurements of barometric pressure near the time of interest. Thereafter, the system calculates the change in barometric pressure Δp during the time-interval Δt when the measurements were made. If the cellular telephone is stationary during the time-interval Δt, then the system reasonably conclude that the value of Δp is caused by changes in the atmosphere and not by the movement of the cellular telephone. In this case, the system can use Δp as a factor in generating the reference barometric pressure p0; otherwise, it cannot.

The invention provides a multi-source data fusion flood risk assessment early warning method, and relates to the technical field of natural disaster early warning. The multi-source data fusion flood risk assessment early warning method comprises the following steps: data acquisition: acquiring meteorological data including but not limited to rainfall, air temperature, air pressure and wind speed; hydrological data including river flow, water level and soil humidity are collected; collecting geographic data including terrain elevation, land utilization type and vegetation coverage; social data including population density, building distribution and infrastructure conditions are collected; and data preprocessing: cleaning the collected data, removing noise and abnormal values, and carrying out standardization processing on the data to ensure that the data of different data sources has comparability. According to the flood risk assessment method, multi-dimensional features of flood risks can be comprehensively reflected by integrating multi-source data of meteorology, hydrology, geography, society and the like, and richer information support is provided by integrating different types of data, so that risk assessment is more comprehensive and accurate.

The invention belongs to the technical field of ocean engineering. According to the seabed data intelligent calculation center structure and the working method, a plurality of stand columns and a tubular structure are connected to form a frame used for bearing a tank body, a supporting seat is fixed in the frame, and the tank body is arranged on the supporting seat; grating plates are arranged at the two ends and the top of the frame, a plurality of suction foundations are fixed to the bottom of the frame, and data intelligent calculation equipment is arranged in the tank body; a temperature and humidity real-time monitoring sensor and a pressure balance adjusting module are integrated in the tank body, the temperature and humidity real-time monitoring sensor communicates with a cooling system outside the tank body, the heat dissipation efficiency in the tank body is adjusted in a linkage mode according to real-time temperature and humidity data, and the pressure balance adjusting module is used for automatically compensating air pressure in the cabin according to water pressure differences of different depths of the seabed; according to the invention, the structural stability of the seabed is ensured, natural cooling is carried out through low-temperature seawater, the problem of high heat dissipation energy consumption of a traditional data center is solved, and a stable working temperature environment is provided for data intelligent calculation equipment.

The invention discloses multi-parameter test analysis equipment for a complex environment, which belongs to the technical field of chemical or physical test analysis and comprises a test cabin, a comprehensive measurement and control system, a vacuum pumping system, a field environment simulation system and a climate temperature and humidity simulation system. The vacuum pumping system, the field environment simulation system and the climate temperature and humidity simulation system are sequentially arranged on the outer side of the test cabin body and are communicated with the test cabin body. By changing and adjusting the air pressure, the temperature, the humidity, the wind, the ultraviolet radiation, the space range and the air density in the specified range in the test cabin body, the extreme climate environment of any single parameter can be simulated, the special environment of combination, alternation and intersection of multiple parameters can also be simulated, and different types of test pieces can be made to have different functions. Test detection operation under a traditional atmospheric state, atrocious weather and an extreme environment of an outdoor environment is completed in the same space, so that multi-parameter data of different types of test pieces can be obtained.

The present invention discloses a high-precision meteorological sensor, which relates to the technical field of meteorology and includes a rain cover, a fixed disk, a rain shield, an ultrasonic reflector, a hollow support column, an upper housing, a lower housing, a louver, a power supply fixing part, a base, a power supply board, a high-voltage generator, an ion blower, an air condition sensor, an acquisition main board, an ultrasonic sensor, a piezoelectric sensor, etc.; only two of the multiple groups of ion blowers are working at the same time, so it has multiple air circulation modes, which is beneficial to adapt to different seasons and weather; the detection head integrates temperature, humidity and air pressure sensing, and cooperates with the breathable hollow air-permeable head and combines with the air circulation to achieve accurate detection; when the hollow air-permeable head adopts a special-shaped curved surface structure, it has good aerodynamic characteristics, and combined with the air circulation, it will increase the collision area of the air flow and achieve high-precision detection.

The invention discloses a short-term wind power prediction method and system based on meteorological data in a wind power generation system, and the method comprises the following steps: S1, obtaining historical wind power data and historical meteorological data of a prediction region, the meteorological data comprising information such as wind speed, wind direction, temperature, humidity and air pressure; s2, preprocessing the historical data, including data cleaning, normalization processing and feature extraction, to construct a training data set and a test data set; s3, constructing and training a prediction model based on deep learning by using the training data set, wherein the prediction model comprises a long short-term memory network (LSTM), a convolutional neural network (CNN) or a combination model thereof; and S4, inputting the test data set into the trained prediction model, performing short-term wind power prediction, and outputting a prediction result.

The invention discloses a sampling device for geological disaster prevention and monitoring, and relates to the technical field of auxiliary equipment for underground water detection.The sampling device comprises a collecting assembly and a sampling assembly, the collecting assembly comprises a collecting pipe, a throwing assembly is arranged at the top end of the collecting pipe, a sampling cavity and an adjusting cavity are formed in the collecting pipe, and an adjusting assembly is arranged in the adjusting cavity; a monitoring assembly is further arranged on the collecting pipe; the control system is used for receiving a plurality of collection depths input by a user, and controlling the adjusting assembly to keep the top end of the sampling cavity and the reference surface static according to the air pressure in the adjusting cavity; only when the volume of the sampling cavity is equal to the difference value obtained by subtracting the volume of the water sample collected last time from the volume of the sampling cavity last time or the absolute value of acceleration of air pressure in the adjusting cavity is larger than a set value, it is judged that the top wall of the collecting cavity meets the sampling requirement, work of the putting assembly is stopped, the opening and closing assembly is controlled to be closed, and the sampling assembly is controlled to work; therefore, the representativeness of the obtained water samples at different depths is improved.

The invention provides a Beidou-based antarctic ice dome elevation measurement method, and solves the problem that the traditional method cannot obtain the high-precision altitude of the antarctic ice dome. The method comprises the following steps: firstly, erecting a Beidou base station at a South Pole ice dome test point, collecting original observation data of a Beidou satellite, and calculating accurate coordinates and geodetic height of the test point through a post-event precise point positioning technology; then, determining a gravity value of a test point by using ground gravity measurement equipment, reducing the gravity value of the test point to a geoid through various corrections such as instrument null drift, earth tide and atmospheric pressure, obtaining gravity anomaly of the test point in combination with a known normal gravity value of a reference ellipsoid surface, and converting the gravity anomaly into elevation anomaly through a formula; and finally, converting the geodetic height calculated by the test point into the altitude through the conversion relation between the geodetic height and the altitude, and checking and checking the initial altitude calculated by the global gravitational field model. The method can be widely applied to the fields of South Pole scientific research, resource development and the like.

The invention discloses a regional evaporation waveguide prediction method based on path loss inversion, and relates to the technical field of maritime communication. Actual measurement path losses corresponding to the multiple propagation signals are obtained through a point-to-point microwave propagation link, inversion is carried out on the actual measurement path losses corresponding to the multiple propagation signals, and the long-time-sequence evaporation waveguide height is obtained; taking the long-time-sequence evaporation waveguide height and the corresponding long-time-sequence meteorological and hydrological characteristics as a training sample set, training a recurrent neural network, and obtaining an evaporation waveguide height prediction model; the meteorological and hydrological characteristics comprise wind speed, air temperature, humidity, sea surface temperature, evaporation capacity, atmospheric pressure and rainfall capacity; predicting an evaporation waveguide height prediction value of each grid point in the target area through an evaporation waveguide height prediction model; and generating continuous regional evaporation waveguide height distribution through inverse distance weighted interpolation according to the evaporation waveguide height prediction value of each grid point in the target region. The method improves the prediction accuracy of the regional evaporation waveguide.