A sub-band brightness temperature-based synthetic aperture radiometer radio frequency interference detection method and system

Abstract

The application provides a sub-band brightness temperature-based synthetic aperture radiometer radio frequency interference detection method and system, which comprises the following steps: sequentially ordering all brightness temperature data along sub-bands; traversing all sub-bands, performing fixed threshold detection on each sub-band brightness temperature data, and marking the detected radio frequency interference as abnormal; traversing all sub-bands, performing two-dimensional spatial radio frequency interference detection on each sub-band brightness temperature, and marking the detected radio frequency interference as abnormal; centering each sub-band brightness temperature, and then performing threshold detection on the absolute value of each sub-band centered brightness temperature data to obtain sub-band brightness temperature after radio frequency interference suppression. The application has the advantages that it can be embedded in a real-time radio frequency interference detection module of a satellite-borne synthetic aperture radiometer, the brightness temperature data of multiple sub-bands are jointly processed, it has the advantages of simple steps and strong detection capability, and it can effectively detect most radio frequency interferences presented by sub-band brightness temperature.

Description

Technical Field

[0001] This application belongs to the field of passive microwave remote sensing signal processing, specifically relating to a method and system for detecting radio frequency interference in a comprehensive aperture radiometer based on sub-band brightness temperature. Background Technology

[0002] Radio frequency interference (RFI) poses a serious challenge to passive microwave remote sensing, particularly in the L-band (1.4 GHz) used for soil moisture and ocean salinity retrieval. With the development of global communication and radar technologies, the intensity and number of RFI sources have increased dramatically, severely degrading the quality of remote sensing data. SMAP (Soil Moisure Active and Passive) satellite observations indicate that approximately 30% of the global observation area is contaminated by RFI, with antenna temperature deviations exceeding 50 K in some areas, increasing soil moisture retrieval errors by 10%–20%.

[0003] To address radio frequency interference (RF) issues, many spaceborne real aperture microwave radiometers have developed engineered solutions for RF interference mitigation. In 2011, NASA's Aquarius payload performed fast sampling of observational data, transmitting antenna temperature data integrated in 10 ms to the ground for RF interference mitigation. In 2015, NASA's SMAP payload performed fast sampling and channelization of on-orbit data, obtaining the fourth moment of the signal. After transmitting the data to the ground, it used antenna temperature, kurtosis data, and the third and fourth Stokes parameters for RF interference detection. In 2018, NASA's CubeRRT (Cubesat Radiometer Radio Frequency Interference Technology validation mission) payload was specifically designed for on-orbit RF interference detection and removal, implementing all RF interference detection and mitigation techniques on-orbit using antenna temperature.

[0004] Compared to a true aperture radiometer, which uses a single large-aperture antenna to directly observe power in the spatial domain, a synthetic aperture radiometer uses a sparsely distributed array of small antennas to perform interferometric measurements in the spatial frequency domain. After obtaining the visibility function, brightness temperature is reconstructed using an inverse Fourier transform. The SMOS (Soil Moisture and Ocean Salinity) satellite, launched by the European Space Agency in 2009, carried a two-dimensional synthetic aperture radiometer. However, due to insufficient consideration of radio frequency interference (RF) issues at launch, it primarily focused on locating and suppressing RF interference using ground-based brightness temperature snapshots, with less than ideal results. The MICAP (Microwave Imager Combined Active and Passive) payload, carried by the China Ocean Salinity Satellite, was successfully launched in 2024. Its L-band one-dimensional synthetic aperture radiometer underwent channelization and RF interference detection and suppression in orbit. However, even after on-orbit RF interference suppression, some residual RF interference still requires further processing on the ground.

[0005] Spaceborne integrated aperture microwave radiometers need to use subband brightness temperature data for radio frequency interference detection and suppression, and existing processing methods are insufficient to meet this requirement. Summary of the Invention

[0006] The purpose of this invention is to fully exploit subband brightness temperature information, jointly process multi-subband brightness temperature data, and achieve high-performance radio frequency interference detection. A method and system for radio frequency interference detection based on subband brightness temperature using a comprehensive aperture radiometer are proposed. This method can utilize subband brightness temperature data for real-time detection of radio frequency interference signals, and features multi-domain joint processing, simple steps, and strong detection capabilities.

[0007] To achieve the above objectives, this application proposes a method for detecting radio frequency interference using a synthetic aperture radiometer based on sub-band brightness temperature, comprising: Step 1: Sort all brightness temperature data sequentially along the sub-bands; Step 2: Traverse all sub-bands, perform fixed threshold detection on the brightness temperature data of each sub-band, and mark the detected radio frequency interference as abnormal; Step 3: Traverse all sub-bands, perform two-dimensional spatial radio frequency interference detection on the brightness temperature of each sub-band, and mark the detected radio frequency interference as abnormal; Step 4: Center the brightness temperature of each sub-band, and then perform threshold detection on the absolute value of the centered brightness temperature data of each sub-band to obtain the brightness temperature of the sub-band after RF interference suppression.

[0008] As an improvement to the above-mentioned method, step 1 includes: Subband number is The number of intersecting directions is The number of items in the same direction is Brightness temperature data Sort according to the sub-band order from smallest to largest, that is ;in ;in For sub-band index, ; Spatial index for the direction of intersection. ; For spatial indexing along the orbital direction. .

[0009] As an improvement to the above-mentioned method, step 2 includes: Set a fixed threshold as Mark all sub-band brightness temperatures outside the range as abnormal: ,in Data marked as abnormal will not be included in subsequent radio frequency interference detection.

[0010] As an improvement to the aforementioned methods, for global scene data, a The range of values ​​is , b The range of values ​​is For pure ocean scene data, a The range of values ​​is , b The range of values ​​is For purely land-based scene data, a The range of values ​​is , b The range of values ​​is .

[0011] As an improvement to the above-mentioned method, step 3 includes: Using the time index of the fast-collected data to be detected as Cache time index arrive All brightness temperature data of the same subband Calculate the mean of the cached data and standard deviation To perform spatial radio frequency interference detection, ,in For two-dimensional spatial domain algorithm window length coefficients, Threshold coefficients for two-dimensional spatial domain algorithms.

[0012] As an improvement to the above-mentioned system method , .

[0013] As an improvement to the above-mentioned method, step 4 includes: Average the brightness temperature of all sub-bands at each spatial location: The average value is subtracted from the brightness temperatures of all sub-bands at that location to obtain the centered sub-band brightness temperature. Then, threshold detection is performed by iterating through the absolute brightness temperature of each centralized sub-band, and the detected radio frequency interference is marked as abnormal. The subband brightness temperature after removing radio frequency interference was obtained, where Threshold coefficients are used for the centered subband algorithm.

[0014] As an improvement to the above-mentioned system method .

[0015] This application also provides a radio frequency interference detection system for a comprehensive aperture radiometer based on sub-band brightness temperature, implemented using the above method. The system includes: The data sorting module is used to sort all brightness temperature data sequentially along the sub-bands; The fixed threshold detection module is used to traverse the brightness temperature data of each sub-band and perform fixed threshold detection, marking the detected radio frequency interference as abnormal; The two-dimensional spatial radio frequency interference detection module traverses all sub-bands, performs two-dimensional spatial radio frequency interference detection on the brightness temperature of each sub-band, and marks the detected radio frequency interference as abnormal. The sub-band brightness temperature centralization module is used to centralize the brightness temperature of each sub-band. The centralized brightness temperature detection module is used to perform threshold detection on the absolute value of the centralized brightness temperature data of each sub-band.

[0016] Compared with existing technologies, the advantages of this application are: 1. It can perform real-time radio frequency interference processing on sub-band brightness temperature data.

[0017] 2. It can be embedded in the real-time radio frequency interference detection module of a spaceborne integrated aperture radiometer, and jointly process the brightness temperature data of multiple sub-bands. It has the advantages of multi-domain joint processing, simple steps and strong detection capabilities, and is especially suitable for integrated aperture radiometers. Attached Figure Description

[0018] Figure 1 The diagram shows a flowchart of a method for detecting radio frequency interference using a synthetic aperture radiometer based on sub-band brightness temperature. Figure 2 The image shows the brightness temperature of the subband to be detected for radio frequency interference. Figure 3 The image shows the brightness temperature of the centered subband. Figure 4 The image shows the subband brightness temperature after radio frequency interference detection. Detailed Implementation

[0019] The technical solution of this application will be described in detail below with reference to the accompanying drawings.

[0020] This invention relates to the field of passive microwave remote sensing signal processing, and more particularly to a method and system for detecting radio frequency interference in a synthetic aperture radiometer based on sub-band brightness temperature. The method includes: (1) Sort all brightness temperature data along the sub-band order; (2) Traverse all sub-bands, perform fixed threshold detection on the brightness temperature data of each sub-band, and mark the detected radio frequency interference as abnormal; (3) Traverse all sub-bands, perform two-dimensional spatial radio frequency interference detection on the brightness temperature of each sub-band, and mark the detected radio frequency interference as abnormal; (4) The brightness temperature of each sub-band is centered, and then the absolute value of the centered brightness temperature data of each sub-band is thresholded to obtain the brightness temperature of the sub-band after radio frequency interference suppression.

[0021] This invention can be embedded in the real-time radio frequency interference detection module of a spaceborne integrated aperture radiometer to detect radio frequency interference of multi-subband brightness temperature. It has the advantages of multi-domain joint operation, simplified steps, and strong detection capability, and can effectively detect most radio frequency interference presented by subband brightness temperature.

[0022] Example 1 The embodiments shown in this invention are illustrated with reference to... Figure 1 This paper presents a method for detecting radio frequency interference using a synthetic aperture radiometer based on sub-band brightness temperature.

[0023] In this embodiment, L1B level brightness temperature data observed using the MICAP payload are used, such as... Figure 2 As shown. Specifically, the method for detecting radio frequency interference using a synthetic aperture radiometer based on sub-band brightness temperature comprises the following steps: Subband number is The number of intersecting directions is The number of items in the same direction is Brightness temperature data Sort according to the sub-band order from smallest to largest, that is ;in ;in For sub-band index, ; Spatial index for the direction of intersection. ; For spatial indexing along the orbital direction. In this embodiment, , , .

[0024] Set a fixed threshold as Mark all sub-band brightness temperatures outside the range as abnormal. For global scenario data, For pure ocean scene data, For purely land-based scene data, ;in Data marked as anomalous will not participate in subsequent radio frequency interference detection. In this embodiment, due to the mixed land and sea scenario, , .

[0025] Using the time index of the fast-collected data to be detected as Cache time index arrive All brightness temperature data of the same subband Calculate the mean of the cached data and standard deviation Perform spatial radio frequency interference detection. ,in It is the configured window length coefficient for the two-dimensional spatial domain algorithm. These are the detection threshold coefficients for the configured two-dimensional spatial domain algorithm. In this embodiment, wherein... , .

[0026] Calculate the average brightness temperature of all sub-bands at each spatial location. The average value is subtracted from the brightness temperatures of all sub-bands at that location to obtain the centered sub-band brightness temperature. ,like Figure 3 As shown; then, threshold detection is performed by traversing the absolute brightness temperature of each centralized sub-band, and the detected radio frequency interference is marked as abnormal. This yields the subband brightness temperature after removing radio frequency interference, such as... Figure 4 As shown. Among them. The configured centralized subband algorithm detection threshold coefficient, in this embodiment, .

[0027] Example 2 The radio frequency interference detection system for a synthetic aperture radiometer based on sub-band brightness temperature provided by this invention is implemented based on the above method. The system includes: The data sorting module is used to sort all brightness temperature data sequentially along the sub-bands; The fixed threshold detection module is used to traverse the brightness temperature data of each sub-band and perform fixed threshold detection, marking the detected radio frequency interference as abnormal; The two-dimensional spatial radio frequency interference detection module is used to traverse all sub-bands, perform two-dimensional spatial radio frequency interference detection on the brightness temperature of each sub-band, and mark the detected radio frequency interference as abnormal. The sub-band brightness temperature centralization module is used to centralize the brightness temperature of each sub-band. The centralized brightness temperature detection module is used to perform threshold detection on the absolute value of the centralized brightness temperature data of each sub-band.

[0028] The data sorting module is used to sort all brightness temperature data sequentially along the sub-bands; the specific process includes: sorting the sub-bands by number of... The number of intersecting directions is The number of items in the same direction is Brightness temperature data Sort according to the sub-band order from smallest to largest, that is ;in ;in For sub-band index, ;in Spatial index for the direction of intersection. ;in For spatial indexing along the orbital direction. .

[0029] The fixed threshold detection module is used to traverse the brightness temperature data of each sub-band and perform fixed threshold detection, marking the detected radio frequency interference as abnormal; its specific process includes: setting the fixed threshold as... Mark all sub-band brightness temperatures outside the range as abnormal. For global scenario data, For pure ocean scene data, For purely land-based scene data, ;in Data marked as abnormal will not be included in subsequent radio frequency interference detection.

[0030] The two-dimensional spatial radio frequency interference detection module is used to traverse all sub-bands, perform two-dimensional spatial radio frequency interference detection on the brightness temperature of each sub-band, and mark the detected radio frequency interference as abnormal. The specific process includes: using the time index of the fast-collected data to be detected as... Cache time index arrive All brightness temperature data of the same subband Calculate the mean of the cached data and standard deviation Perform spatial radio frequency interference detection. ,in It is the configured window length coefficient for the two-dimensional spatial domain algorithm. It is the threshold coefficient for the configured two-dimensional spatial domain algorithm detection.

[0031] The sub-band brightness temperature centering module is used to center the brightness temperature of each sub-band; its specific process includes: averaging the brightness temperatures of all sub-bands at each spatial location along the spatial dimension. Then, the average value is subtracted from the brightness temperatures of all sub-bands at that location to obtain the centered sub-band brightness temperature. .

[0032] The centralized brightness temperature detection module is used to perform threshold detection on the absolute value of the centralized brightness temperature data for each sub-band. The specific process includes: traversing the absolute value of the brightness temperature of each centralized sub-band, performing threshold detection, and marking detected radio frequency interference as abnormal. This yields the subband brightness temperature after removing radio frequency interference, where... It is the threshold coefficient for the centralized sub-band algorithm detection.

[0033] 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.

[0034] The user interface can include a display, keyboard, or clicking device. Examples include a mouse, trackball, touchpad, or touchscreen.

[0035] 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 SDRAM (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.

[0036] 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.

[0037] 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.

[0038] 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: Follow the steps described above.

[0039] 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 methods, steps, and logic diagrams disclosed above. 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 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.

[0040] 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.

[0041] 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 outside the processor.

[0042] 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.

[0043] 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 detecting radio frequency interference in a synthetic aperture radiometer based on sub-band brightness temperature, comprising: Step 1: Sort all brightness temperature data sequentially along the sub-bands; Step 2: Traverse all sub-bands, perform fixed threshold detection on the brightness temperature data of each sub-band, and mark the detected radio frequency interference as abnormal; Step 3: Traverse all sub-bands, perform two-dimensional spatial radio frequency interference detection on the brightness temperature of each sub-band, and mark the detected radio frequency interference as abnormal; Step 4: Center the brightness temperature of each sub-band, and then perform threshold detection on the absolute value of the centered brightness temperature data of each sub-band to obtain the brightness temperature of the sub-band after RF interference suppression; Step 1 includes: Subband number is The number of intersecting directions is The number of items in the same direction is Brightness temperature data Sort according to the sub-band order from smallest to largest, that is ;in ;in For sub-band index, ; Spatial index for the direction of intersection. ; For spatial indexing along the orbital direction. ; Step 3 includes: Using the time index of the fast-collected data to be detected as Cache time index arrive All brightness temperature data of the same subband Calculate the mean of the cached data and standard deviation To perform spatial radio frequency interference detection, ,in For two-dimensional spatial domain algorithm window length coefficients, Threshold coefficients for two-dimensional spatial domain algorithms.

2. The method for detecting radio frequency interference of a synthetic aperture radiometer based on sub-band brightness temperature according to claim 1, characterized in that, Step 2 includes: Set a fixed threshold as Mark all subband brightness temperatures outside the range as abnormal: ,in Data marked as abnormal will not be included in subsequent radio frequency interference detection.

3. The method for detecting radio frequency interference of a synthetic aperture radiometer based on sub-band brightness temperature according to claim 2, characterized in that, For global scenario data, a The range of values ​​is , b The range of values ​​is For pure ocean scene data, a The range of values ​​is , b The range of values ​​is For purely land-based scene data, a The range of values ​​is , b The range of values ​​is .

4. The method for detecting radio frequency interference of a synthetic aperture radiometer based on sub-band brightness temperature according to claim 1, characterized in that, ， 。 5. The method for detecting radio frequency interference of a synthetic aperture radiometer based on sub-band brightness temperature according to claim 1, characterized in that, Step 4 includes: Average the brightness temperature of all sub-bands at each spatial location: The average value is subtracted from the brightness temperatures of all sub-bands at that location to obtain the centered sub-band brightness temperature. Then, threshold detection is performed by iterating through the absolute brightness temperature of each centralized sub-band, and the detected radio frequency interference is marked as abnormal. The subband brightness temperature after removing radio frequency interference was obtained, where Threshold coefficients are used to detect the centered subband algorithm.

6. The method for detecting radio frequency interference of a synthetic aperture radiometer based on sub-band brightness temperature according to claim 5, characterized in that, 。 7. A radio frequency interference detection system for a comprehensive aperture radiometer based on sub-band brightness temperature, implemented according to the method described in any one of claims 1-6, characterized in that, The system includes: The data sorting module is used to sort all brightness temperature data sequentially along the sub-bands; The fixed threshold detection module is used to traverse the brightness temperature data of each sub-band and perform fixed threshold detection, marking the detected radio frequency interference as abnormal; The two-dimensional spatial radio frequency interference detection module traverses all sub-bands, performs two-dimensional spatial radio frequency interference detection on the brightness temperature of each sub-band, and marks the detected radio frequency interference as abnormal. The sub-band brightness temperature centralization module is used to centralize the brightness temperature of each sub-band; and The centralized brightness temperature detection module is used to perform threshold detection on the absolute value of the centralized brightness temperature data of each sub-band.

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