Multi-meteorological satellite fusion receiving system

Abstract

The invention discloses a receiving system for fusion of multiple meteorological satellites. The receiving system comprises a data receiving subsystem, a data processing and fusion subsystem, a data storage and management subsystem, a data presentation subsystem, a communication and interface subsystem and a satellite signal monitoring and calibration subsystem, the data receiving subsystem comprises an antenna unit, a satellite signal tracking module, a satellite signal demodulation module and a satellite signal decoding module. By integrating a plurality of advanced subsystems, efficient receiving, fusion processing, storage management, presentation display and communication sharing of the multi-source meteorological satellite data are realized, and the requirements of simultaneous receiving and efficient processing of the multi-source heterogeneous meteorological satellite data are met; the problems of poor compatibility and limited fusion processing capability in the prior art are effectively solved, more powerful and comprehensive technical support is provided for development of meteorological services, and the method has remarkable innovativeness and practical value.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of meteorological satellite data receiving and processing, and in particular to a multi-meteorological satellite fusion receiving system. BACKGROUND

[0002] With the continuous development of meteorological satellite technology, various countries have launched a variety of high-performance meteorological satellites, such as China's Fengyun-4, Japan's Himawari satellite, South Korea's Gk2a satellite, etc. These satellites play an important role in earth observation and meteorological data acquisition. Currently, meteorological satellite data receiving equipment is designed for a single satellite or a specific satellite series, making it difficult to meet the simultaneous receiving and efficient processing needs of multi-source heterogeneous meteorological satellite data. Differences in orbital parameters, data formats, encoding methods, transmission protocols, etc. of meteorological satellites from different countries pose many challenges to the development of receiving equipment. In addition, the existing technical means for meteorological data fusion are relatively limited, often focusing on simple fusion at a single data level, and failing to fully leverage the advantages of multi-satellite data, resulting in missing images and significant differences in infrared channel resolution between different satellites, which cannot provide more accurate and comprehensive data support for meteorological operations. In view of the above, the present application proposes a multi-meteorological satellite fusion receiving system. SUMMARY

[0003] Based on the technical problems existing in the background technology, the present application proposes a multi-meteorological satellite fusion receiving system.

[0004] The multi-meteorological satellite fusion receiving system proposed by the present application includes a data receiving subsystem, a data processing and fusion subsystem, a data storage and management subsystem, a data presentation subsystem, a communication and interface subsystem, and a satellite signal monitoring and calibration subsystem.

[0005] The data receiving subsystem includes an antenna unit, a satellite signal tracking module, a satellite signal demodulation module, and a satellite signal decoding module.

[0006] The data processing and fusion subsystem includes a data preprocessing module, a data layer fusion module, a feature layer fusion module, and a decision layer fusion module.

[0007] The data presentation subsystem includes a data presentation subsystem interface, which includes a two-dimensional map display interface, a three-dimensional display interface, a dynamic chart display interface, and a data output option interface.

[0008] The satellite signal monitoring and calibration subsystem includes a signal monitoring module, a signal calibration module, an alarm module, and a data feedback module.

[0009] Preferably, the antenna unit is multiple, which is used for optimizing the design of different meteorological satellite frequency bands and signal characteristics, ensuring stable reception of Fengyun-4, Meteosat, Gk2a satellite data;

[0010] The satellite signal tracking module, satellite signal demodulation module and satellite signal decoding module can automatically identify and lock the target satellite signal, complete the demodulation and decoding processing of the signal, develop the corresponding decoding algorithm for different satellite data encoding and transmission protocol, and realize efficient demodulation and restoration of each satellite data.

[0011] Preferably, the data preprocessing module is used for preprocessing the received multi-source meteorological satellite data, including data cleaning, correction, format conversion operation, eliminating noise and error in the data, and unifying the data format for subsequent fusion processing;

[0012] The data layer fusion module is used for spatio-temporal registration and fusion of observation data of different satellites, using spatial interpolation algorithm and time series analysis method to fuse data of different resolutions and different times, generating a fusion data set with higher spatio-temporal resolution for monitoring rapid changes and fine structure of meteorological elements;

[0013] The feature layer fusion module is used for extracting meteorological feature information in each satellite data, including cloud features, atmospheric water vapor content, and surface temperature, and establishing a feature correlation model for fusion analysis, integrating feature information of multiple satellites to improve the accuracy and reliability of meteorological element inversion;

[0014] The decision layer fusion module generates more accurate meteorological forecast products and disaster warning information based on the fused data and feature information, using meteorological forecast model and decision algorithm, to provide more effective decision support for meteorological business.

[0015] Preferably, the data storage and management subsystem adopts a distributed storage architecture with large capacity and high reliability, capable of storing massive multi-satellite meteorological data and its fusion results, classifying and indexing the data according to data type, time, and satellite source dimensions for quick query and retrieval, while designing data backup and recovery mechanism to back up important data regularly and recover in time when data is damaged or lost, ensuring data security and integrity, and supporting long-term archiving and version management of data to meet the needs of long-term preservation and historical comparative analysis of meteorological data.

[0016] Preferably, the data presentation subsystem develops an intuitive and friendly user interface to present the multi-satellite fused meteorological data in multiple visualization modes, through the set two-dimensional map display interface, three-dimensional display interface, dynamic chart display interface and data output option interface, the user can select different display modes and data layers according to the requirements, conveniently view the spatial and temporal distribution and change of meteorological elements, and support access and display of multiple terminal devices, including computers, mobile phones and tablets, realize convenient sharing and mobile application of meteorological data, and additionally have data output function, can export the fused data in standard format for use by other meteorological business systems or scientific research institutions.

[0017] Preferably, the communication and interface subsystem is equipped with multiple communication interfaces, including Ethernet, optical fiber and satellite communication, to realize interconnection and intercommunication of the receiving device with external networks, meteorological centers and other related devices, transmit the received satellite data and fusion results to the meteorological business platform in time through stable communication links, receive control instructions and task parameters issued by the platform, design a standardized interface protocol to ensure compatibility with devices and systems of different manufacturers, facilitate system integration and expansion, support real-time transmission and remote monitoring of data, facilitate remote management and maintenance of the running state of the receiving device, and support data interaction and sharing with other meteorological observation devices, data processing systems and devices of scientific research institutions, realize seamless connection through the standardized interface protocol, and promote the wide dissemination and application of meteorological data.

[0018] Preferably, the satellite signal monitoring and calibration subsystem monitors the receiving quality of the receiving device to each meteorological satellite signal in real time through the signal monitoring module, including signal strength, signal-to-noise ratio and bit error rate, automatically diagnoses signal abnormal conditions, and issues an alarm in time through the alarm module, analyzes the long-term trend of satellite signals through monitoring data, and feeds back through the data feedback module, provides a reference for satellite operation state evaluation, calibrates the frequency, phase and time parameters of the receiving device through the signal calibration module, ensures the accuracy and synchronization of data reception, and uses high-precision calibration algorithms and external reference signal sources to calibrate the receiving device regularly, and improve data quality.

[0019] The application also provides an implementation method of the multi-meteorological satellite fusion receiving system, comprising the following steps:

[0020] S1: first, the antenna units in the data receiving subsystem simultaneously receive the downlink data signals from the Chinese Fengyun-4, Japanese HImawari and Korean Gk2a satellites, and each antenna unit automatically adjusts the azimuth and angle according to the pre-set parameters and satellite orbit information, to ensure the best reception effect of the satellite signals, and in the process of receiving signals, the communication and interface subsystem ensures stable communication between the receiving device and the external network;

[0021] S2: The satellite signal monitoring and calibration subsystem monitors the reception quality parameters of each satellite signal in real time through the signal monitoring module. When an abnormal signal is detected, an alarm is issued in a timely manner through the alarm module, and appropriate measures are taken automatically to adjust and repair. At the same time, the signal calibration module regularly calibrates the frequency, phase and other parameters of the receiving equipment to ensure the accuracy and synchronization of data reception, providing protection for high-quality meteorological data acquisition;

[0022] S3: After the satellite signal is received by the antenna unit, it is transmitted to the satellite signal tracking module, five-star signal demodulation module and satellite signal decoding module. The satellite signal tracking module, five-star signal demodulation module and satellite signal decoding module cooperate to demodulate and decode the signal according to the data encoding and transmission protocol of each satellite, and restore the original satellite data to usable observation data such as radiation brightness, ground reflectivity, atmospheric temperature and humidity profile, etc.

[0023] S4: The data restored in S3 is sent to the data processing and fusion subsystem. The data preprocessing module cleans, corrects and formats the data, removes abnormal values and noise interference, and unifies the time and spatial resolution format of the data to meet the requirements of fusion processing;

[0024] S5: The preprocessed data in S4 is subjected to integrity detection by the data preprocessing module. If the detected data is incomplete, the data layer fusion module performs time control complementation and reconstruction. If the detected data is complete, the data layer fusion module performs accurate evaluation and weight distribution;

[0025] S6: The high-frequency observation data of FY-4 and the high-resolution image data of the HJ-1 satellite are weighted and fused to generate a fused data set with high temporal resolution and high spatial resolution, which is used to monitor the rapid changes and fine structures of meteorological elements. At the same time, the microwave data of Gk2a satellite and the visible and infrared data of other satellites are fused to fully utilize the advantages of microwave data in cloud and rain area detection and all-weather observation, and to improve the accuracy of meteorological element inversion;

[0026] S7: The feature layer fusion module extracts meteorological feature information from each satellite data, such as cloud optical thickness, particle size distribution, atmospheric water vapor content, wind field information, etc. and performs optical and radar data fusion and infrared and visible light fusion through the feature correlation model. For example, combining the cloud macro feature information of FY-4 with the cloud micro physical parameters of Gk2a, a more comprehensive understanding of the formation, development and dissipation process of clouds is obtained, providing more rich feature information for cloud precipitation physics research and weather forecasting;

[0027] S8: The decision layer fusion module optimizes the fused data and feature information in S6 and S7, and calls the weather forecast model and disaster warning algorithm to generate weather forecast products and meteorological disaster warning information, for example, through comprehensive analysis of precipitation characteristics, atmospheric circulation patterns and terrain conditions and other factors in the fused data, early warning of meteorological disasters such as heavy rain, flood, typhoon and drought is carried out, and a complete cloud picture is generated by comprehensive decision of multi-source information and displayed to the user in the data presentation subsystem, providing strong support for the disaster prevention and mitigation decision of the meteorological department;

[0028] S9: The data storage and management subsystem synchronously stores and manages the original data and the fused data, stores the data in distributed storage nodes according to satellite types, time sequences, data types and other classification methods, and establishes index and metadata information, which facilitates user query and retrieval of historical data, at the same time, data is backed up regularly, and when the system detects data anomalies, the recovery program is started in time to ensure the safety and integrity of the data;

[0029] S10: The data presentation subsystem provides an intuitive and convenient data display interface for users, users can access receiving equipment through computer clients, mobile phone APPs and other terminal devices to view multi-satellite fused meteorological data, on the two-dimensional map interface, the user can intuitively see the distribution of different meteorological elements such as cloud coverage, precipitation intensity and temperature distribution; in the three-dimensional display interface mode, the vertical structure and spatio-temporal evolution process of meteorological elements can be observed more clearly; the dynamic chart display interface can be used to display the time series change and trend analysis of meteorological elements, and users can also customize the display content and parameter settings according to their needs through the data output option interface to meet different business and scientific research needs;

[0030] S11: The communication and interface subsystem transmits the received satellite data and fusion results to the data platform of the meteorological business center in real time through the high-speed Ethernet interface, and receives the work instructions and parameter configuration information issued by the platform.

[0031] Compared with the existing technology, the beneficial effects of the present application are:

[0032] 1. Through the setting of the data receiving subsystem, the data of meteorological satellites of different countries (China Fengyun-4, Japan HImawari satellite, South Korea Gk2a) can be received simultaneously, solving the difference problems of satellite orbital parameters, data format, encoding method and transmission protocol, etc., having wide satellite compatibility, and cooperating with the setting of the communication and interface subsystem, multiple communication interfaces can be equipped to realize stable communication and interconnection between the receiving equipment and external network and related equipment, using standardized interface protocol to ensure the compatibility and scalability of the system;

[0033] 2. Through the setting of the data processing and fusion subsystem, different resolution, different time acquisition multi-source satellite data can be fused to generate higher spatio-temporal resolution fusion data set through spatio-temporal registration and fusion algorithm, more detailed data support can be provided for weather analysis, and meteorological feature information in each satellite data can be extracted and a feature correlation model can be established for fusion analysis, the accuracy and reliability of meteorological element inversion can be improved, the state and change of meteorological elements can be more accurately judged, and more accurate weather forecast products and disaster warning information can be generated based on the fused data and feature information, meteorological forecast model and decision algorithm, more effective decision support can be provided for meteorological business;

[0034] 3. Through the setting of the data storage and management subsystem, a distributed storage architecture is adopted to realize storage, classification, indexing and backup of massive data, support fast query, retrieval, long-term archiving and version management of data, ensure the safety and integrity of data, and in cooperation with the setting of the data presentation subsystem, the needs of users for convenient viewing and analysis of meteorological data can be met, and data output function is supported to facilitate sharing with other systems and institutions;

[0035] 4. Through the setting of the satellite signal monitoring and calibration subsystem, the receiving quality of each satellite signal by the receiving equipment can be monitored in real time, signal abnormalities can be automatically diagnosed and alarms can be sent, and satellite signal calibration function is provided to ensure the accuracy and synchronization of data reception and improve data quality;

[0036] The present application realizes efficient reception, fusion processing, storage management, presentation and sharing of multi-source meteorological satellite data by integrating multiple advanced subsystems, meets the needs of simultaneous reception and efficient processing of multi-source heterogeneous meteorological satellite data, effectively solves the problems of poor compatibility and limited fusion processing capacity in the prior art, provides more powerful and comprehensive technical support for the development of meteorological business, and has significant innovative and practical value. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 The block diagram of the multi-meteorological satellite fusion receiving system proposed in the present application;

[0038] Figure 2 The block diagram of the data receiving subsystem in the multi-meteorological satellite fusion receiving system proposed in the present application;

[0039] Figure 3 The block diagram of the data processing and fusion subsystem in the multi-meteorological satellite fusion receiving system proposed in the present application;

[0040] Figure 4 The interface schematic diagram of the data presentation subsystem in the multi-meteorological satellite fusion receiving system proposed in the present application;

[0041] Figure 5 The block diagram of a satellite signal monitoring and calibration subsystem in a multi-weather satellite fusion receiving system according to the present application is shown in the figure below.

[0042] Figure 6 The flow chart of the steps of operation of a data processing and fusion subsystem in a multi-weather satellite fusion receiving system according to the present application is shown in the figure below. DETAILED DESCRIPTION

[0043] The present application will be further described below with reference to specific embodiments.

[0044] EMBODIMENT

[0045] REFERENCE Figures 1-6 The present embodiment proposes a multi-weather satellite fusion receiving system, which includes a data receiving subsystem, a data processing and fusion subsystem, a data storage and management subsystem, a data presentation subsystem, a communication and interface subsystem, and a satellite signal monitoring and calibration subsystem.

[0046] The data storage and management subsystem adopts a distributed storage architecture, has large-capacity and high-reliability storage capability, can store massive multi-satellite weather data and fusion results, classifies and stores data and indexes management according to data type, time, and satellite source dimension, facilitates fast query and retrieval of data, at the same time, designs data backup and recovery mechanism, regularly backs up important data, and can recover in time when data is damaged or lost, ensures the safety and integrity of data, in addition, supports long-term archiving and version management of data, meets the needs of long-term preservation and historical comparative analysis of weather data.

[0047] The communication and interface subsystem is equipped with multiple communication interfaces, including Ethernet, optical fiber, satellite communication, realizes interconnection and intercommunication of receiving equipment and external network, meteorological center, and other related equipment, through stable communication link, timely transmits received satellite data and fusion results to meteorological business platform, at the same time, receives control instructions and task parameters issued by the platform, in addition, designs standardized interface protocol, ensures compatibility with devices and systems of different manufacturers, facilitates system integration and expansion, supports real-time transmission and remote monitoring of data, facilitates remote management and maintenance of the running state of receiving equipment, at the same time, also supports data interaction and sharing with other meteorological observation equipment, data processing systems, and equipment of scientific research institutions, realizes seamless connection through standardized interface protocol, promotes the widespread dissemination and application of meteorological data.

[0048] The data receiving subsystem includes an antenna unit, a satellite signal tracking module, a satellite signal demodulation module, and a satellite signal decoding module.

[0049] The antenna units are multiple, which are used for optimizing design of different meteorological satellite frequency bands and signal characteristics, ensuring stable reception of Fengyun-4, Fengyun-2, Gk2a satellite data, for example, using high-gain, low-noise antenna technology, and adaptive tuning function to adapt to the frequency changes and intensity differences of different satellite signals;

[0050] The satellite signal tracking module, satellite signal demodulation module and satellite signal decoding module can automatically identify and lock the target satellite signal, complete the demodulation and decoding processing of the signal, develop the corresponding decoding algorithm for different satellite data encoding and transmission protocol, and realize efficient demodulation and restoration of each satellite data;

[0051] The data processing and fusion subsystem includes a data preprocessing module, a data layer fusion module, a feature layer fusion module and a decision layer fusion module;

[0052] The data preprocessing module is used for preprocessing the received multi-source meteorological satellite data, including data cleaning, correction, format conversion operation, eliminating noise and error in the data, and unifying the data format for subsequent fusion processing;

[0053] The data layer fusion module is used for spatio-temporal registration and fusion of observation data of different satellites, using spatial interpolation algorithm and time series analysis method to fuse data of different resolutions and different times together to generate a fusion data set with higher spatio-temporal resolution, which is used for monitoring the rapid change and fine structure of meteorological elements, for example, by fusing the high temporal resolution data of Fengyun-4 with the high spatial resolution data of Fengyun-2, a fusion data with high temporal resolution and high spatial resolution is obtained, which provides a basis for more detailed meteorological analysis;

[0054] The feature layer fusion module is used to extract meteorological feature information in each satellite data, including cloud features, atmospheric water vapor content, and surface temperature, and to establish a feature correlation model for fusion analysis, to integrate the feature information of multiple satellites and improve the accuracy and reliability of meteorological element inversion, for example, combining the cloud phase information of Fengyun-4 with the cloud height information of Gk2a to more accurately judge the type and structure of the cloud;

[0055] The decision layer fusion module generates more accurate meteorological forecast products and disaster warning information based on the fused data and feature information, using meteorological forecast models and decision algorithms, to provide more effective decision support for meteorological business, for example, by analyzing the precipitation characteristics and atmospheric circulation pattern in the fused data, to provide early warning for meteorological disasters such as rainstorm and typhoon, and to provide decision support for disaster prevention and reduction;

[0056] The data presentation subsystem comprises a data presentation subsystem interface, which comprises a two-dimensional map display interface, a three-dimensional display interface, a dynamic chart display interface and a data output option interface; the data presentation subsystem develops an intuitive and friendly user interface to present the meteorological data fused by multiple satellites in multiple visual modes, and through the two-dimensional map display interface, the three-dimensional display interface, the dynamic chart display interface and the data output option interface, the user can select different display modes and data layers according to the requirements, conveniently view the spatial and temporal distribution and change of the meteorological elements, and support access and display of multiple terminal devices, including computers, mobile phones and tablets, realize convenient sharing and mobile application of meteorological data, and additionally have a data output function to export the fused data in a standard format for use by other meteorological business systems or scientific research institutions;

[0057] The satellite signal monitoring and calibration subsystem comprises a signal monitoring module, a signal calibration module, an alarm module and a data feedback module;

[0058] The satellite signal monitoring and calibration subsystem monitors the receiving quality of the receiving equipment for each meteorological satellite signal in real time through the signal monitoring module, including signal strength, signal-to-noise ratio and bit error rate, automatically diagnoses signal abnormal conditions, and timely issues an alarm through the alarm module, analyzes the long-term trend of the satellite signal through the monitoring data, and feeds back through the data feedback module to provide a reference for satellite operation state evaluation, calibrates the frequency, phase and time parameters of the receiving equipment through the signal calibration module to ensure the accuracy and synchronization of data reception, and uses high-precision calibration algorithms and external reference signal sources to calibrate the receiving equipment regularly to improve data quality;

[0059] The embodiment realizes efficient receiving, fusion processing, storage management, presentation and display and communication sharing of multi-source meteorological satellite data by integrating multiple advanced subsystems, meets the requirements of simultaneous receiving and efficient processing of multi-source heterogeneous meteorological satellite data, effectively solves the problems of poor compatibility and limited fusion processing capacity in the prior art, provides more powerful and comprehensive technical support for the development of meteorological business, and has significant innovative and practical value.

[0060] In the embodiment, the specific implementation steps of the multi-meteorological satellite fusion receiving system are as follows:

[0061] S1: First, the antenna units in the data receiving subsystem simultaneously receive the downlink data signals from the Chinese Fengyun-4, Japanese HImawari and Korean Gk2a satellites, and each antenna unit automatically adjusts the azimuth and angle according to the pre-set parameters and satellite orbit information to ensure the best receiving effect of the satellite signals, and in the process of receiving the signals, the communication and interface subsystem ensures stable communication between the receiving equipment and the external network;

[0062] S2: The satellite signal monitoring and calibration subsystem monitors the reception quality parameters of each satellite signal in real time through the signal monitoring module. When an abnormal signal is detected, an alarm is issued in a timely manner through the alarm module, and appropriate measures are taken automatically to adjust and repair. At the same time, the signal calibration module regularly calibrates the frequency, phase and other parameters of the receiving equipment to ensure the accuracy and synchronization of data reception and provide protection for high-quality meteorological data acquisition;

[0063] S3: After the satellite signal is received by the antenna unit, it is transmitted to the satellite signal tracking module, five-star signal demodulation module and satellite signal decoding module. The satellite signal tracking module, five-star signal demodulation module and satellite signal decoding module cooperate to demodulate and decode the signal according to the data encoding and transmission protocol of each satellite, and restore the original satellite data to usable observation data such as radiation brightness, ground reflectivity, atmospheric temperature and humidity profile, etc.

[0064] S4: The data restored in S3 is sent to the data processing and fusion subsystem. The data preprocessing module cleans, corrects and formats the data, removes abnormal values and noise interference, and unifies the time and spatial resolution format of the data to meet the requirements of fusion processing;

[0065] S5: The preprocessed data in S4 is subjected to integrity detection by the data preprocessing module. If the detected data is incomplete, the data layer fusion module performs time control complementation and reconstruction. If the detected data is complete, the data layer fusion module performs accurate evaluation and weight distribution;

[0066] In addition, the specific logical steps for time control complementation and reconstruction are as follows:

[0067] S5011: Spatio-temporal coverage optimization: By fusing low-orbit and high-orbit satellite data, the revisit period is shortened from several hours for a single satellite to minutes;

[0068] S5012: Inter-satellite data complementation: When certain satellite data is missing due to cloud cover or equipment failure, the same type of data from other satellites at the same time is automatically called to fill in the missing data;

[0069] S5013: Missing area reconstruction: image data reconstruction based on Shearlet transform, the specific steps are as follows:

[0070] S50131: Multi-scale Shearlet decomposition of complete area satellite image to obtain low frequency and high frequency coefficients;

[0071] S50132: Extract the low frequency information of the corresponding area from the same period data of other satellites, and fuse the top layer mean value and the bottom layer gradient maximum value through Laplacian pyramid;

[0072] S50133: the most clear details are selected by information entropy and standard deviation of high frequency part;

[0073] The specific logical steps in precise evaluation and weight distribution are as follows:

[0074] S5021: a precision evaluation model is constructed, and quantitative indicators are performed, including spatial resolution, signal-to-noise ratio, and radiation calibration error;

[0075] S5022: weight distribution is performed by using weighted average method, and the weight distribution formula is: Wherein, Resi is the resolution, the smaller the value is, the higher the weight is, and SNR is the signal-to-noise ratio;

[0076] S6: the high frequency observation data of FY-4 processed in S5 and the high resolution image data of HJ-1 are fused by weighting, to generate a fused data set with high time resolution and high spatial resolution, which is used to monitor the rapid change and fine structure of meteorological elements, and the microwave data of Gk2a satellite and the visible light and infrared data of other satellites are fused, to give full play to the advantages of microwave data in cloud and rain area detection and all-weather observation, and improve the accuracy of meteorological element inversion;

[0077] The specific logical steps in weighted fusion are as follows:

[0078] S601: the information entropy E, average gradient G and standard deviation σ of each satellite image are calculated by using fusion algorithm;

[0079] S602: the product of the three after normalization in S601 is taken as the maximum value of the fusion subgraph, and the formula used is: Fhigh=argmax(Enorm×Gnorm×σnorm);

[0080] S603: the optimal subgraph is nonlinearly enhanced, and the edge contrast is adjusted by using Sigm function;

[0081] S7: meteorological feature information in each satellite data is extracted by feature layer fusion module, such as cloud optical thickness, particle size distribution, atmospheric water vapor content, wind field information, etc., and optical and radar data fusion and infrared and visible light fusion are performed by feature correlation model, for example, the cloud macro feature information of FY-4 is combined with the cloud micro physical parameters of Gk2a, to more comprehensively understand the formation, development and dissipation process of cloud, and provide more rich feature information for cloud precipitation physical research and weather forecast;

[0082] The specific steps of optical and radar data fusion are as follows:

[0083] S7011: Improved normalized water index is extracted from optical data, and VH polarization backscattering coefficient is extracted from SAR data;

[0084] S7012: Otsu algorithm is used to segment water body and non-water body, and consistency is evaluated by Kappa coefficient;

[0085] S7013: Expert knowledge model is introduced in rice field vegetation area to correct SAR scattering error;

[0086] The specific steps of infrared and visible light fusion are as follows:

[0087] S6021: Histogram equalization is performed on each channel;

[0088] S6022: The histogram of each channel is decomposed into low frequency and high frequency;

[0089] S6023: The low frequency takes the mean value, and the high frequency takes the maximum subgraph of standard deviation;

[0090] S8: The decision layer fusion module optimizes the data and feature information fused in S6 and S7, and calls meteorological prediction model and disaster warning algorithm to generate weather forecast products and meteorological disaster warning information, for example, through comprehensive analysis of precipitation characteristics, atmospheric circulation situation and terrain conditions and other factors in the fused data, early warning of meteorological disasters such as heavy rain, flood, typhoon and drought is carried out, and complete cloud image is generated by comprehensive decision of multi-source information to show users in data presentation subsystem, which provides strong support for disaster prevention and mitigation decision of meteorological department;

[0091] Optimization includes expert system embedding and Kalman filter dynamic optimization, the expert system embedding includes adjusting cloud water vapor content model in typhoon monitoring combined with ground meteorological station temperature and humidity data, Kalman filter dynamic optimization is state prediction and error correction for continuous time series cloud image, which improves the tracking accuracy of moving cloud cluster;

[0092] S9: The data storage and management subsystem synchronously stores and manages the original data and the data after fusion processing, stores the data in distributed storage nodes according to satellite type, time sequence, data type and other classification methods, establishes index and metadata information, facilitates user to query and retrieve historical data, at the same time, regularly backs up data, and when the system detects data anomaly, starts recovery program in time to ensure the safety and integrity of data;

[0093] S10: The data presentation subsystem provides an intuitive and convenient data display interface for the user. The user can access the receiving device through a computer client, a mobile phone APP, and other terminal devices to view the multi-satellite fused meteorological data. On a two-dimensional map interface, the user can intuitively see the distribution of different meteorological elements, such as cloud coverage, precipitation intensity, and temperature distribution. In a three-dimensional display interface mode, the user can more clearly observe the vertical structure and spatio-temporal evolution process of meteorological elements. The dynamic chart display interface can be used to display the time series change and trend analysis of meteorological elements. The user can also customize the display content and parameter settings according to the requirements through the data output option interface to meet different business and research needs.

[0094] S11: The communication and interface subsystem transmits the received satellite data and fusion results to the data platform of the meteorological business center in real time through a high-speed Ethernet interface, and receives the work instructions and parameter configuration information issued by the platform.

[0095] The above is only the preferred specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can make equivalent replacements or changes within the technical scope disclosed in the present application according to the technical solution and inventive concept of the present application, which should be covered within the protection scope of the present application.

Claims

1. A receiving system integrating multiple meteorological satellites, characterized in that, It includes a data receiving subsystem, a data processing and fusion subsystem, a data storage and management subsystem, a data presentation subsystem, a communication and interface subsystem, and a satellite signal monitoring and calibration subsystem; The data receiving subsystem includes an antenna unit, a satellite signal tracking module, a satellite signal demodulation module, and a satellite signal decoding module; The data processing and fusion subsystem includes a data preprocessing module, a data layer fusion module, a feature layer fusion module, and a decision layer fusion module. The data presentation subsystem includes a data presentation subsystem interface, which includes a two-dimensional map display interface, a three-dimensional stereoscopic display interface, a dynamic chart display interface, and a data output option interface. The satellite signal monitoring and calibration subsystem includes a signal monitoring module, a signal calibration module, an alarm module, and a data feedback module.

2. The multi-meteorological satellite fusion receiving system according to claim 1, characterized in that, The antenna unit comprises multiple units, which are used to optimize the design of different meteorological satellite frequency bands and signal characteristics to ensure stable reception of data from Fengyun-4, Kuihua, and Gk2a satellites. The satellite signal tracking module, satellite signal demodulation module, and satellite signal decoding module can automatically identify and lock the target satellite signal, and complete the demodulation and decoding processing of the signal. Corresponding decoding algorithms have been developed for different satellite data encoding and transmission protocols to achieve efficient demodulation and restoration of data from various satellites.

3. The multi-meteorological satellite fusion receiving system according to claim 1, characterized in that, The data preprocessing module is used to preprocess the received multi-source meteorological satellite data, including data cleaning, correction, and format conversion operations, to eliminate noise and errors in the data and unify the data format in preparation for subsequent fusion processing. The data layer fusion module is used to perform spatiotemporal registration and fusion of observation data from different satellites. By using spatial interpolation algorithms and time series analysis methods, it fuses data acquired at different resolutions and times to generate a fused dataset with higher spatiotemporal resolution, which is used to monitor the rapid changes and fine structure of meteorological elements. The feature layer fusion module is used to extract meteorological feature information from each satellite data, including cloud features, atmospheric water vapor content, and surface temperature, and to establish a feature association model for fusion analysis. By integrating the feature information of multiple satellites, the accuracy and reliability of meteorological element inversion are improved. The decision-level fusion module, based on the fused data and feature information, utilizes meteorological forecasting models and decision-making algorithms to generate more accurate meteorological forecast products and disaster early warning information, providing more effective decision support for meteorological operations.

4. The multi-meteorological satellite fusion receiving system according to claim 1, characterized in that, The data storage and management subsystem adopts a distributed storage architecture, possessing large-capacity and high-reliability storage capabilities. It can store massive amounts of multi-satellite meteorological data and their fusion results. Based on data type, time, and satellite source dimensions, the data is classified, stored, and indexed for easy and rapid querying and retrieval. A data backup and recovery mechanism is also designed to regularly back up important data and ensure timely recovery in case of data corruption or loss, guaranteeing data security and integrity. Furthermore, it supports long-term data archiving and version management, meeting the needs for long-term preservation and historical comparative analysis of meteorological data.

5. The multi-meteorological satellite fusion receiving system according to claim 1, characterized in that, The data presentation subsystem features an intuitive and user-friendly interface that presents multi-satellite fusion meteorological data in various visualization methods. Through a set two-dimensional map display interface, a three-dimensional stereoscopic display interface, a dynamic chart display interface, and a data output option interface, users can select different display modes and data layers according to their needs, making it convenient to view the spatiotemporal distribution and changes of meteorological elements. It also supports access and display on various terminal devices, including computers, mobile phones, and tablets, enabling convenient sharing and mobile applications of meteorological data. In addition, it has a data output function, which can export the fusion data in a standard format for use by other meteorological business systems or research institutions.

6. The multi-meteorological satellite fusion receiving system according to claim 1, characterized in that, The communication and interface subsystem is equipped with multiple communication interfaces, including Ethernet, fiber optic, and satellite communication, enabling interconnection between the receiving device and external networks, meteorological centers, and other related equipment. Through a stable communication link, it promptly transmits received satellite data and fusion results to the meteorological operational platform, while simultaneously receiving control commands and task parameters from the platform. Furthermore, a standardized interface protocol is designed to ensure compatibility with equipment and systems from different manufacturers, facilitating system integration and expansion. It supports real-time data transmission and remote monitoring, enabling remote management and maintenance of the receiving device's operational status. It also supports data interaction and sharing with other meteorological observation equipment, data processing systems, and research institutions, achieving seamless integration through standardized interface protocols and promoting the widespread dissemination and application of meteorological data.

7. The multi-meteorological satellite fusion receiving system according to claim 1, characterized in that, The satellite signal monitoring and calibration subsystem monitors the reception quality of meteorological satellite signals in real time through the signal monitoring module, including signal strength, signal-to-noise ratio, and bit error rate. It automatically diagnoses signal anomalies and issues timely alarms through the alarm module. By analyzing the long-term trend of satellite signal changes through monitoring data, it provides feedback through the data feedback module, providing a reference for satellite operation status assessment. The signal calibration module performs precise calibration of the frequency, phase, and time parameters of the receiving equipment to ensure the accuracy and synchronization of data reception. It also uses high-precision calibration algorithms and external reference signal sources to periodically calibrate the receiving equipment to improve data quality.

8. The implementation method of the multi-meteorological satellite fusion receiving system according to any one of claims 1-7, characterized in that, Includes the following steps: S1: First, the antenna unit in the data receiving subsystem simultaneously receives downlink data signals from China's Fengyun-4, Japan's Himawari, and South Korea's Gk2a satellites. At the same time, each antenna unit automatically adjusts its azimuth and angle according to the preset parameters and satellite orbit information to ensure the best reception effect of satellite signals. During the signal reception process, the communication and interface subsystem ensures stable communication between the receiving equipment and the external network. S2: The satellite signal monitoring and calibration subsystem monitors the reception quality parameters of each satellite signal in real time through the signal monitoring module. When an abnormal signal is detected, the alarm module promptly issues an alarm and automatically takes corresponding measures to adjust and repair. At the same time, the signal calibration module periodically calibrates the frequency, phase and other parameters of the receiving equipment to ensure the accuracy and synchronization of data reception, thus providing a guarantee for the acquisition of high-quality meteorological data. S3: After the satellite signal is received by the antenna unit, it is transmitted to the satellite signal tracking module, the five-satellite signal demodulation module, and the satellite signal decoding module. The satellite signal tracking module, the five-satellite signal demodulation module, and the satellite signal decoding module work together to demodulate and decode the signal according to the data encoding and transmission protocol of each satellite, and restore the original satellite data into usable observation data, such as radiance, surface reflectance, atmospheric temperature and humidity profiles, etc. S4: The restored data in S3 is sent to the data processing and fusion subsystem. The data preprocessing module cleans, corrects and converts the data to remove outliers and noise interference, and unifies the time and spatial resolution format of the data to meet the requirements of fusion processing. S5: The data preprocessed in S4 is checked for integrity by the data preprocessing module. If the data is incomplete, the data fusion module performs time-controlled complementarity and reconstruction. If the data is complete, the data fusion module performs accurate evaluation and weight allocation. S6: The high-frequency observation data from Fengyun-4 processed in S5 is weighted and fused with the high-resolution image data from the Himawari satellite to generate a fused dataset with both high temporal and spatial resolution. This dataset is used to monitor the rapid changes and fine structure of meteorological elements. At the same time, microwave data from the Gk2a satellite is fused with visible light and infrared data from other satellites to give full play to the advantages of microwave data in cloud and rain area detection and all-day observation, thereby improving the accuracy of meteorological element inversion. S7: The feature layer fusion module extracts meteorological feature information from various satellite data, such as cloud optical thickness, particle size distribution, atmospheric water vapor content, wind field information, etc., and performs optical and radar data fusion and infrared and visible light fusion through feature association model. For example, by combining the macroscopic cloud feature information of Fengyun-4 and the microscopic cloud physical parameters of Gk2a, we can gain a more comprehensive understanding of the formation, development and dissipation process of clouds, and provide richer feature information for cloud precipitation physics research and weather forecasting. S8: The decision-making fusion module optimizes the fused data and feature information from S6 and S7, and calls meteorological forecast models and disaster early warning algorithms to generate weather forecast products and meteorological disaster early warning information. For example, through comprehensive analysis of factors such as precipitation characteristics, atmospheric circulation patterns and topographic conditions in the fused data, it provides early warnings for meteorological disasters such as rainstorms, floods, typhoons, and droughts. It also generates a complete cloud map by integrating multi-source information and displays it to users in the data presentation subsystem, providing strong support for meteorological departments' disaster prevention and mitigation decisions. S9: The data storage and management subsystem synchronously stores and manages the raw data and the fused data. According to the classification methods such as satellite type, time series, and data type, the data is stored in distributed storage nodes, and indexes and metadata information are established to facilitate users to query and retrieve historical data. At the same time, the data is backed up regularly, and when the system detects data anomalies, the recovery program is started in time to ensure the security and integrity of the data. S10: The data presentation subsystem provides users with an intuitive and convenient data display interface. Users can access the receiving device through terminal devices such as computer clients and mobile APPs to view meteorological data after multi-satellite fusion. On the two-dimensional map interface, the distribution of different meteorological elements, such as cloud coverage, precipitation intensity, and temperature distribution, can be seen intuitively. In the three-dimensional display interface mode, the vertical structure and spatiotemporal evolution of meteorological elements can be observed more clearly. The dynamic chart display interface can be used to display the time series changes and trend analysis of meteorological elements. Users can also customize the display content and parameter settings according to their needs through the data output option interface to meet different business and scientific research needs. S11: The communication and interface subsystem transmits the received satellite data and fusion results to the meteorological business center's data platform in real time via a high-speed Ethernet interface, while also receiving work instructions and parameter configuration information issued by the platform.

Images