A method and system for correcting the brightness temperature of a spaceborne one-dimensional synthetic aperture microwave radiometer.

Abstract

This application provides a method and system for correcting the brightness temperature of a spaceborne one-dimensional integrated aperture microwave radiometer. The method includes: acquiring two-dimensional observed brightness temperature data O along the vertical satellite orbit and along the satellite orbit for different ascent and descent orbits of the microwave radiometer; acquiring external data such as atmospheric profiles, surface data, and sea surface salinity along the radiation transmission path to obtain simulated Earth radiation brightness temperature data B, and removing outlier data; subtracting the observed brightness temperature data from the simulated brightness temperature data to obtain O-B data for multiple single orbits, and removing outlier data; taking the median of the O-B data to obtain the average difference in O-B brightness temperature and the two-dimensional corrected brightness temperature; dividing the average difference in O-B brightness temperature by the observed brightness temperatures in the corresponding two vertical directions to obtain two-dimensional relative brightness temperature correction coefficients based on different ascent and descent orbits; and correcting the observed brightness temperature using the two-dimensional relative brightness temperature correction coefficients or the two-dimensional corrected brightness temperature. The advantage of this application is that the established two-dimensional correction coefficients have a better correction effect.

Description

Technical Field

[0001] This application belongs to the fields of atmospheric science and remote sensing technology, and specifically relates to a method and system for correcting the brightness temperature of a spaceborne one-dimensional integrated aperture microwave radiometer. Background Technology

[0002] Ocean salinity is a crucial ocean dynamic parameter influencing the water cycle, atmospheric circulation, and global climate. L-band microwave radiometers are widely recognized as the most suitable instruments for microwave remote sensing measurements of soil moisture and ocean salinity. However, microwave radiometer salinity detection still faces many challenges, including:

[0003] 1. Radiometers have low sensitivity to salinity measurements when measuring brightness temperature; the brightness temperature fluctuation caused by salinity changes is minimal (only 4K in the typical range of 32-37 psu), and the sensitivity decreases further at low temperatures. A measurement accuracy of 0.1 psu requires microwave radiometer calibration accuracy better than 0.1K. For example, the SMAP satellite improved the calibration accuracy to 0.08K through digital gain compensation technology, but in actual observations, complex algorithms are still needed to separate the salinity signal from other noise, making it difficult to achieve the required accuracy for application and research.

[0004] 2. Radio Frequency Interference (RFI): The L-band (1.4 GHz) where the satellite primarily operates overlaps with civilian frequency bands used for mobile communications and BeiDou navigation, resulting in significant man-made signal interference. For example, China's first ocean salinity detection satellite needs to use a spectrum analyzer to "identify the location of interference sources" and combine this with algorithms to eliminate interference. If not effectively filtered, interference can significantly increase the error in brightness temperature measurement.

[0005] 3. The Influence of High Sea States and Atmosphere: High sea states can lead to foaming at the sea surface, affecting microwave radiation and scattering signals. Water vapor, oxygen, and clouds in the atmosphere absorb or scatter microwave signals. For example, high sea states or precipitation can cause brightness temperature measurement errors exceeding 1K, while the uncertainty of water vapor path delay can cause salinity inversion errors to reach 1 psu. Although partial corrections are currently achieved through multi-band joint inversion (such as C and K band auxiliary temperature measurements), significant errors still exist in areas such as wind speed and precipitation.

[0006] Therefore, there is an urgent need for a brightness temperature correction method for microwave radiometers to accurately measure ocean salinity. Summary of the Invention

[0007] The purpose of this application is to overcome the inaccuracy of existing spaceborne microwave radiometers in measuring ocean radiation brightness temperature.

[0008] To achieve the above objectives, this application proposes a method for correcting the brightness temperature of a spaceborne one-dimensional synthetic aperture microwave radiometer, comprising:

[0009] Step S1: Obtain the two-dimensional brightness temperature data O of the satellite one-dimensional integrated aperture microwave radiometer at different ascent and descent orbits at a set time, namely the two vertical directions TX and TY of a single pass; wherein TX is the Earth scan brightness temperature data perpendicular to the satellite orbit flight direction, and TY is the brightness temperature data along the satellite orbit flight direction.

[0010] Step S2: Based on the latitude and longitude of the Earth's orbital projection, obtain the atmospheric profile, surface data, and sea surface salinity data at that latitude and longitude to obtain the brightness temperature data B for simulating Earth's radiation.

[0011] Step S3: Remove outlier data from the simulated brightness temperature data B;

[0012] Step S4: Subtract the observed brightness temperature data O from the simulated brightness temperature data B to obtain OB data for multiple passes;

[0013] Step S5: Based on the 3σ standard, remove outlier data from multiple passes of OB data;

[0014] Step S6: Take the median of the OB data of multiple passes to obtain the average difference of OB brightness temperature based on the pass, and the two-dimensional corrected brightness temperature based on different riser / faller rail passes;

[0015] Step S7: Divide the average difference in OB brightness temperature based on the pass by the corresponding TX+TY brightness temperature to obtain the two-dimensional relative brightness temperature correction coefficient based on different lifting rail passes.

[0016] Step S8: Apply the two-dimensional relative brightness temperature correction coefficient or the two-dimensional corrected brightness temperature to the observed brightness temperature of different passes to correct the observed brightness temperature.

[0017] As an improvement to the above method, the atmospheric profile and surface data include data provided by the European Centre for Medium-Range Weather Forecasts.

[0018] As an improvement to the above method, the sea surface salinity data includes sea surface salinity data from a mixed coordinate ocean model or a world ocean atlas.

[0019] As an improvement to the above method, the abnormal data in step S3 includes: wind speeds higher than 15 m / s, and rainfall with a liquid water content exceeding 0.1% or low temperature data with a temperature below 273.15 K.

[0020] This application also provides a brightness temperature correction system for a spaceborne one-dimensional integrated aperture microwave radiometer, implemented based on the above method, the system comprising:

[0021] The module for acquiring observation brightness temperature data is used to acquire different ascending and descending orbits of the satellite's one-dimensional integrated aperture microwave radiometer at a set time, namely, the two-dimensional observation brightness temperature data O of TX and TY in a single pass; wherein TX is the Earth scan brightness temperature data perpendicular to the satellite's orbital flight direction, and TY is the brightness temperature data along the satellite's orbital flight direction.

[0022] The module for acquiring simulated brightness temperature data is used to obtain atmospheric profile, surface data, and sea surface salinity data at the latitude and longitude of the satellite orbit Earth projection, and to obtain brightness temperature data B for simulating Earth radiation.

[0023] The module for removing abnormal simulated brightness temperature data is used to remove abnormal data from simulated brightness temperature data B.

[0024] The OB data acquisition module is used to subtract the observed brightness temperature data O from the simulated brightness temperature data B to obtain OB data for multiple passes.

[0025] The OB abnormal data removal module is used to remove abnormal data from OB data across multiple passes according to the 3σ standard.

[0026] The two-dimensional brightness temperature correction module is used to take the median of OB data from multiple passes to obtain the average difference in OB brightness temperature based on the pass, and the two-dimensional brightness temperature correction based on different lifting rails.

[0027] The brightness temperature correction coefficient module is used to divide the average difference of OB brightness temperature based on the pass by the corresponding TX+TY brightness temperature to obtain the two-dimensional relative brightness temperature correction coefficient based on different lifting rail passes.

[0028] The brightness temperature correction module is used to apply the two-dimensional relative brightness temperature correction coefficient to the brightness temperature of different passes, thereby correcting the brightness temperature of the observations.

[0029] Compared with existing technologies, the advantages of this application are:

[0030] 1. Compared with the existing one-dimensional coefficient that only selects the vertical flight direction, the method of this application takes into account the radiation difference to the latitude of the earth, and the established two-dimensional correction coefficient or two-dimensional correction brightness temperature has a better correction effect.

[0031] 2. Existing methods only select specific sea areas for brightness temperature correction under clear sky conditions. The method in this application is based on global sea area statistics, and the obtained correction method has more statistical characteristics, thus ensuring the correction quality.

[0032] 3. Existing methods use the difference between observed and simulated brightness temperature to correct brightness temperature. The method in this application divides the difference between observed and simulated brightness temperature by the brightness temperatures of TX and TY to obtain the correction brightness temperature coefficient. This method applies different correction brightness temperatures to different levels of observed brightness temperature, resulting in more effective results. Attached Figure Description

[0033] Figure 1 The diagram shows a flowchart of a method for correcting the brightness temperature of a spaceborne one-dimensional integrated aperture microwave radiometer. Detailed Implementation

[0034] The technical solution of this application will be described in detail below with reference to the accompanying drawings.

[0035] This application applies to the correction of brightness temperature for spaceborne L-band microwave radiometers operating in sun-synchronous orbits. The spaceborne microwave radiometer receives the brightness temperature of Earth's radiation; due to the different dielectric constants of different ground features, it enables the observation of various ground features. A complete ascent or descent orbit observation is called a pass, or single pass.

[0036] Example 1

[0037] like Figure 1 As shown, the method for correcting the brightness temperature of a spaceborne one-dimensional synthetic aperture microwave radiometer provided in this application includes:

[0038] Step 1: Acquire the TX and TY two-dimensional observation brightness temperature data O(a,b) of different ascending and descending orbits (single pass) of the long-term satellite one-dimensional integrated aperture microwave radiometer, where TX is the Earth scan brightness temperature data perpendicular to the satellite orbit flight direction, TY is the brightness temperature data from south to north along the satellite orbit flight direction, and a and b represent the amount of data in the perpendicular and along the satellite orbit flight direction of one pass.

[0039] Step 2: Based on the satellite orbit Earth projection latitude and longitude data, obtain atmospheric profile and surface data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and sea surface salinity data from the Hybrid Coordinate Ocean Model (HYCOM) or the World Ocean Atlas (WOA);

[0040] Step 3: Simulate the brightness temperature data of Earth's radiation based on the data from Step 2;

[0041] Step 4: Remove high wind speeds (above 15 m / s), rainfall with liquid water content exceeding 0.1%, and low temperature data (below 273.15 K) from the simulation data in Step 3 to obtain high-quality two-dimensional brightness temperature data B for simulating Earth's radiation.

[0042] Step 5: Subtract the observed brightness temperature (O) and simulated brightness temperature (B) from those in Steps 1 and 4 to obtain the OB dataset for multiple passes;

[0043] Step 6: Based on the 3σ standard, remove outlier data from the OB datasets of multiple passes in Step 5;

[0044] Step 7: Take the median of the OB data of multiple passes in Step 6 to obtain the average difference in OB brightness temperature based on the pass, and the two-dimensional corrected brightness temperature based on different riser / faller rail passes.

[0045] Step 8: Divide the average difference in OB brightness temperature based on the pass in Step 7 by the corresponding TX+TY brightness temperature to obtain the two-dimensional relative brightness temperature correction coefficient based on different lifting rail passes.

[0046] Step 9: Apply the two-dimensional relative brightness temperature correction coefficient or two-dimensional corrected brightness temperature obtained in Step 8 to the observed brightness temperature of different passes to correct the observed brightness temperature of the passes.

[0047] The brightness temperature correction method for a spaceborne one-dimensional integrated aperture microwave radiometer based on a single track proposed in this application is the first to establish a relative brightness temperature correction coefficient method based on two-dimensional pass data, which has better correction effect.

[0048] Example 2

[0049] This application also provides a brightness temperature correction system for a spaceborne one-dimensional integrated aperture microwave radiometer, implemented based on the above method, the system comprising:

[0050] The module for acquiring observation brightness temperature data is used to acquire different ascending and descending orbits of the satellite's one-dimensional integrated aperture microwave radiometer at a set time, namely, the two-dimensional observation brightness temperature data O of TX and TY in a single pass; wherein TX is the Earth scan brightness temperature data perpendicular to the satellite's orbital flight direction, and TY is the brightness temperature data along the satellite's orbital flight direction.

[0051] The module for acquiring simulated brightness temperature data is used to obtain atmospheric profile, surface data, and sea surface salinity data at the latitude and longitude of the satellite orbit Earth projection, and to obtain brightness temperature data B for simulating Earth radiation.

[0052] The module for removing abnormal simulated brightness temperature data is used to remove abnormal data from simulated brightness temperature data B.

[0053] The OB data acquisition module is used to subtract the observed brightness temperature data O from the simulated brightness temperature data B to obtain OB data for multiple passes.

[0054] The OB abnormal data removal module is used to remove abnormal data from OB data across multiple passes according to the 3σ standard.

[0055] The two-dimensional brightness temperature correction module is used to take the median of OB data from multiple passes to obtain the average difference in OB brightness temperature based on the pass, and the two-dimensional brightness temperature correction based on different lifting rails.

[0056] The brightness temperature correction coefficient module is used to divide the average difference of OB brightness temperature based on the pass by the corresponding TX+TY brightness temperature to obtain the two-dimensional relative brightness temperature correction coefficient based on different lifting rail passes.

[0057] The brightness temperature correction module is used to apply the two-dimensional relative brightness temperature correction coefficient to the brightness temperature of different passes, thereby correcting the brightness temperature of the observations.

[0058] This application may also provide a computer device, including: at least one processor, memory, at least one network interface, and a user interface. The various components in this device are coupled together via a bus system. It is understood that the bus system is used to implement communication between these components. In addition to a data bus, the bus system also includes a power bus, a control bus, and a status signal bus.

[0059] The user interface can include a display, keyboard, or clicking device. Examples include a mouse, trackball, touchpad, or touchscreen.

[0060] It is understood that the memory in the embodiments disclosed in this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate Synchronous DRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memories described herein are intended to include, but are not limited to, these and any other suitable types of memory.

[0061] In some implementations, the memory stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating systems and applications.

[0062] The operating system includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application programs include various applications, such as media players and browsers, used to implement various application functions. Programs implementing the methods of the embodiments of this disclosure can be included in the application programs.

[0063] In the above embodiments, the processor can also invoke programs or instructions stored in memory, specifically programs or instructions stored in an application program, for the following purposes:

[0064] Follow the steps described above.

[0065] The above methods can be applied to or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above methods can be completed by integrated logic circuits in the processor's hardware or by software instructions. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the disclosed methods, steps, and logic block diagrams. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the disclosed methods can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0066] It is understood that the embodiments described in this application can be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in this application, or combinations thereof.

[0067] For software implementation, the technology of this application can be implemented by executing the functional modules (e.g., procedures, functions, etc.) of this application. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or externally.

[0068] This application may also provide a non-volatile storage medium for storing a computer program. When the computer program is executed by a processor, it can implement the steps in the above method embodiments.

[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of this application do not depart from the spirit and scope of the technical solutions of this application, and should all be covered within the scope of the claims of this application.

Claims

1. A method for correcting the brightness temperature of a spaceborne one-dimensional synthetic aperture microwave radiometer, comprising: Step S1: Obtain the two-dimensional brightness temperature data O of the satellite one-dimensional integrated aperture microwave radiometer at different ascent and descent orbits at a set time, namely the two vertical directions TX and TY of a single pass; wherein TX is the Earth scan brightness temperature data perpendicular to the satellite orbit flight direction, and TY is the brightness temperature data along the satellite orbit flight direction. Step S2: Based on the latitude and longitude of the Earth's orbital projection, obtain the atmospheric profile, surface data, and sea surface salinity data at that latitude and longitude to obtain the brightness temperature data B for simulating Earth's radiation. Step S3: Remove outlier data from the simulated brightness temperature data B; Step S4: Subtract the observed brightness temperature data O from the simulated brightness temperature data B to obtain OB data for multiple passes; Step S5: Based on the 3σ standard, remove outlier data from multiple passes of OB data; Step S6: Take the median of the OB data of multiple passes to obtain the average difference of OB brightness temperature based on the pass, and the two-dimensional corrected brightness temperature based on different riser / faller rail passes; Step S7: Divide the average difference in OB brightness temperature based on the pass by the corresponding TX+TY brightness temperature to obtain the two-dimensional relative brightness temperature correction coefficient based on different lifting rail passes. Step S8: Apply the two-dimensional relative brightness temperature correction coefficient or the two-dimensional corrected brightness temperature to the observed brightness temperature of different passes to correct the observed brightness temperature.

2. The method for correcting the brightness temperature of a spaceborne one-dimensional synthetic aperture microwave radiometer according to claim 1, characterized in that, The atmospheric profile and surface data include data provided by the European Centre for Medium-Range Weather Forecasts.

3. The method for correcting the brightness temperature of a spaceborne one-dimensional synthetic aperture microwave radiometer according to claim 1, characterized in that, The sea surface salinity data includes sea surface salinity data from mixed coordinate ocean models or world ocean atlases.

4. The method for correcting the brightness temperature of a spaceborne one-dimensional synthetic aperture microwave radiometer according to claim 1, characterized in that, Abnormal data in step S3 includes: wind speeds higher than 15 m / s, and rainfall with a liquid water content exceeding 0.1% or low temperature data below 273.15 K.

5. A correction system for the brightness temperature of a spaceborne one-dimensional synthetic aperture microwave radiometer, implemented based on the method described in any one of claims 1-4, characterized in that, The system includes: The module for acquiring observation brightness temperature data is used to acquire different ascending and descending orbits of the satellite's one-dimensional integrated aperture microwave radiometer at a set time, namely, the two-dimensional observation brightness temperature data O of TX and TY in a single pass; wherein TX is the Earth scan brightness temperature data perpendicular to the satellite's orbital flight direction, and TY is the brightness temperature data along the satellite's orbital flight direction. The module for acquiring simulated brightness temperature data is used to obtain atmospheric profile, surface data, and sea surface salinity data at the latitude and longitude of the satellite orbit Earth projection, and to obtain brightness temperature data B for simulating Earth radiation. The module for removing abnormal simulated brightness temperature data is used to remove abnormal data from simulated brightness temperature data B. The OB data acquisition module is used to subtract the observed brightness temperature data O from the simulated brightness temperature data B to obtain OB data for multiple passes. The OB abnormal data removal module is used to remove abnormal data from OB data across multiple passes according to the 3σ standard. The two-dimensional brightness temperature correction module is used to take the median of OB data from multiple passes to obtain the average difference in OB brightness temperature based on the pass, and the two-dimensional brightness temperature correction based on different lifting rails. The brightness temperature correction coefficient module is used to divide the average difference in OB brightness temperature based on the pass by the corresponding TX+TY brightness temperature to obtain the two-dimensional relative brightness temperature correction coefficient based on different riser / faller rail passes; and The brightness temperature correction module is used to apply the two-dimensional relative brightness temperature correction coefficient or the two-dimensional corrected brightness temperature to the brightness temperature of different passes, thereby correcting the brightness temperature of the observations.

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