Radiation performance evaluation method and device of satellite sensor based on stable target

Abstract

The invention provides a radiation performance evaluation method and device of a satellite sensor based on a stable target, provides a novel cross radiation calibration mechanism for a cross radiation calibration target of atmospheric top reflectivity, and can be combined with a high-precision second satellite sensor to evaluate the radiation performance of the satellite sensor. The high-precision radiation performance evaluation in the aspect of the atmospheric top reflectivity is performed on the first satellite sensor, so that the atmospheric top reflectivity acquired by the first satellite sensor can be corrected with high precision.

Description

Technical Field

[0001] The present application relates to the field of satellites, and in particular to a method and device for evaluating the radiation performance of a satellite sensor based on a stable target. Background Art

[0002] At present, the methods for monitoring the radiation performance of satellite sensors on in-orbit satellites mainly include on-board calibration and on-orbit replacement calibration. Among them, the on-board calibrator often produces a certain degree of attenuation due to the harsh space environment and strong solar radiation and other conditions, and cannot be used for radiation calibration; on-orbit replacement calibration can be further subdivided, including field calibration method, cross-calibration method, etc.

[0003] Site calibration is based on measured data and requires synchronous measurement on the ground and by satellite. It is greatly affected by natural conditions such as weather, consumes a lot of manpower and material resources, and the frequency of calibration is very limited.

[0004] Cross-calibration uses a sensor with high radiometric calibration accuracy as a reference sensor to establish a relationship with the sensor to be calibrated, thereby tracking and correcting changes in the radiometric performance of the sensor to be calibrated. However, cross-calibration strictly limits the observation geometry and transit time of the two sensors, resulting in too little remote sensing image data using a single scene.

[0005] That is to say, for satellite sensors, existing cross-calibration schemes have the problems of poor practicality and lack of processing accuracy.

[0006] Take the satellite sensor Moderate Resolution Spectral Imager II (MERSI-II) as an example. MERSI-II is one of the main payloads of the FY3D satellite. Before the launch of the satellite carrying MERSI-II, the radiation calibration will be carried out accurately in the laboratory. However, as the satellite is launched and operated in orbit, its own characteristics will change during this process. At the same time, the harsh space environment will cause the sensor components to age and the sensitivity to decrease, affecting its radiation performance. Therefore, it is very necessary to monitor and calibrate the radiation performance of MERSI-II carried on the satellite in orbit.

[0007] Moreover, it was found in practice that the onboard calibration system of satellites equipped with MERSI-II is imperfect and mainly relies on field calibration, with a slow update frequency and great influence from weather, making it impossible to monitor changes in sensor performance in a timely manner. In addition, satellites equipped with MERSI-II have been in operation for more than five years, and their calibration performance has not been fully studied, limiting their wide quantitative application. Therefore, it is necessary to optimize the existing cross-calibration scheme for MERSI-II. Summary of the invention

[0008] The present application provides a method and device for evaluating the radiation performance of a satellite sensor based on a stable target. Aiming at the cross-radiation calibration target of the top-of-atmosphere reflectivity, the present application provides a novel cross-radiation calibration mechanism, which can be combined with a high-precision second satellite sensor to perform a high-precision radiation performance evaluation of the top-of-atmosphere reflectivity for the first satellite sensor, thereby performing a high-precision correction for the top-of-atmosphere reflectivity collected by the first satellite sensor.

[0009] In a first aspect, the present application provides a method for evaluating the radiation performance of a satellite sensor based on a stable target, characterized in that the method comprises:

[0010] Acquire first radiation performance remote sensing data of a first satellite sensor for evaluating radiation performance in a historical time period, and acquire second radiation performance remote sensing data of a second satellite sensor for reference in a historical time period;

[0011] Extracting a first top-of-atmosphere reflectivity corresponding to a stable target from the first radiation property remote sensing data, and extracting a second top-of-atmosphere reflectivity corresponding to a stable target from the second radiation property remote sensing data, wherein the stable target is a selected geographical area;

[0012] Spectra of the first top-of-atmosphere reflectance and the second top-of-atmosphere reflectance are adjusted by a spectral matching factor to reduce the difference between the spectral channels of the two sensors;

[0013] A bidirectional reflectance distribution function correction is performed on the adjusted first top-of-atmosphere reflectance to reduce the impact of observed top-of-atmosphere reflectance changes on the temporal trend due to differences in observation geometry;

[0014] Calculate the ratio of the original first atmosphere top reflectance and the first atmosphere top reflectance corrected by the bidirectional reflectance distribution function as the normalized atmosphere top reflectance;

[0015] Based on the normalized top-of-atmosphere reflectivity, the radiation performance of the first satellite sensor is quantified through preset quantitative indicators.

[0016] In a second aspect, the present application provides a radiation performance evaluation device for a satellite sensor based on a stable target, the device comprising:

[0017] An acquisition unit, used to acquire first radiation performance remote sensing data of a first satellite sensor to be evaluated for radiation performance in a historical time period, and to acquire second radiation performance remote sensing data of a second satellite sensor as a reference in a historical time period;

[0018] An extraction unit, configured to extract a first top-of-atmosphere reflectivity corresponding to a stable target from the first radiation performance remote sensing data, and to extract a second top-of-atmosphere reflectivity corresponding to the second radiation performance remote sensing data, wherein the stable target is a selected geographical area;

[0019] An adjustment unit, used for performing spectral adjustment of the first atmosphere top reflectance and the second atmosphere top reflectance by a spectral matching factor, so as to reduce the difference between the spectral channels of the two sensors;

[0020] a correction unit for performing a bidirectional reflectance distribution function correction on the adjusted first top of atmosphere reflectance to reduce the influence of the observed top of atmosphere reflectance change on the time trend caused by the difference in observation geometry;

[0021] A calculation unit, used for calculating the ratio of the original first atmosphere top reflectance and the first atmosphere top reflectance corrected by the bidirectional reflectance distribution function as the normalized atmosphere top reflectance;

[0022] The quantification unit is used to quantify the radiation performance of the first satellite sensor through a preset quantitative index based on the normalized atmospheric top reflectivity.

[0023] In a third aspect, the present application provides a processing device, including a processor and a memory, wherein a computer program is stored in the memory, and when the processor calls the computer program in the memory, the method provided in the first aspect of the present application or any possible implementation method of the first aspect of the present application is executed.

[0024] In a fourth aspect, the present application provides a computer-readable storage medium, which stores multiple instructions, and the instructions are suitable for a processor to load to execute the method provided by the first aspect of the present application or any possible implementation of the first aspect of the present application.

[0025] From the above content, it can be concluded that the present application has the following beneficial effects:

[0026] For the cross-radiation calibration target of the top of atmosphere reflectivity, the present application first obtains the first radiation performance remote sensing data of the first satellite sensor to be evaluated for radiation performance in a historical time period, and obtains the second radiation performance remote sensing data of the second satellite sensor as a reference in a historical time period, and then extracts the first top of atmosphere reflectivity corresponding to the first radiation performance remote sensing data and the stable target, and extracts the second top of atmosphere reflectivity corresponding to the second radiation performance remote sensing data and the stable target, wherein the stable target is a selected geographical area, at this time, the spectrum of the first top of atmosphere reflectivity and the second top of atmosphere reflectivity are adjusted by the spectral matching factor to reduce the difference in the spectral channels of the two sensors, and then the adjusted first top of atmosphere reflectivity is adjusted. The bidirectional reflectance distribution function is corrected for the rate to reduce the impact of the change in the observed atmospheric top reflectance on the time trend caused by the difference in the observed geometric shape, and then the ratio of the original first atmospheric top reflectance and the first atmospheric top reflectance corrected by the bidirectional reflectance distribution function is calculated as the normalized atmospheric top reflectance. At this time, on the basis of the normalized atmospheric top reflectance, the radiation performance of the first satellite sensor is quantified by a preset quantitative indicator. In this way, the present application provides a novel cross-radiance calibration mechanism, which can be combined with a high-precision second satellite sensor to perform a high-precision radiation performance evaluation of the atmospheric top reflectance for the first satellite sensor, and further can perform a high-precision correction for the atmospheric top reflectance collected by the first satellite sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A schematic diagram of a flow chart of a radiation performance evaluation method of a satellite sensor based on a stable target in this application;

[0029] Figure 2 A schematic diagram of the structure of a radiation performance evaluation device for a satellite sensor based on a stable target in the present application;

[0030] Figure 3 A schematic diagram of the structure of the processing equipment of this application. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0032] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The naming or numbering of steps in this application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The process steps that have been named or numbered can change the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved.

[0033] The division of modules in this application is a logical division. There may be other division methods when it is implemented in actual applications. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection between modules can be electrical or other similar forms, which are not limited in this application. In addition, the modules or submodules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed in multiple circuit modules, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present application.

[0034] Before introducing the radiation performance evaluation method of a satellite sensor based on a stable target provided by the present application, the background content involved in the present application is first introduced.

[0035] The radiation performance evaluation method, device and computer-readable storage medium of a satellite sensor based on a stable target provided in the present application can be applied to a processing device. With respect to the cross-radiation calibration target of the top of atmosphere reflectivity, the present application provides a novel cross-radiation calibration mechanism, which can be combined with a high-precision second satellite sensor to perform a high-precision radiation performance evaluation of the top of atmosphere reflectivity for the first satellite sensor, thereby performing a high-precision correction for the top of atmosphere reflectivity collected by the first satellite sensor.

[0036] The radiation performance evaluation method of a satellite sensor based on a stable target mentioned in the present application can be performed by a radiation performance evaluation device of a satellite sensor based on a stable target, or a server, a physical host, or a user equipment (UE) or other different types of processing equipment that integrates the radiation performance evaluation device of a satellite sensor based on a stable target. Among them, the radiation performance evaluation device of a satellite sensor based on a stable target can be implemented in hardware or software, and the UE can be a terminal device such as a smart phone, a tablet computer, a laptop computer, a desktop computer, or a personal digital assistant (PDA), and the processing device can be set in a device cluster.

[0037] It can be understood that the data processing involved in the radiation performance evaluation method of satellite sensors based on stable targets in the present application is data processing carried out on the basis of the radiation performance remote sensing data obtained by the satellite sensors carried on the in-orbit satellite during / after the data collection process. Therefore, for the processing equipment that executes the radiation performance evaluation method of satellite sensors based on stable targets provided in the present application, or the processing equipment equipped with the application service corresponding to the radiation performance evaluation method of satellite sensors based on stable targets provided in the present application, in actual circumstances, it is only necessary to have the required data processing capabilities.

[0038] If it is also necessary to involve the generation and processing of analysis of radiation performance remote sensing data, it can be achieved by adjusting the composition structure of the processing equipment. For example, the processing equipment can specifically be a satellite control system capable of generating radiation performance remote sensing data. For example, the processing equipment can include a processing equipment body for executing the contents of the scheme other than generating radiation performance remote sensing data, and a satellite control system that itself has the ability to generate radiation performance remote sensing data. In this way, the existing satellite control system can be linked to obtain the radiation performance remote sensing data required for the scheme of this application.

[0039] Of course, in actual situations, the present application solution usually only needs to involve existing photovoltaic power station images, and does not need to involve specific collection operations for photovoltaic power station images. The collection of photovoltaic power station images can be handled by the data source.

[0040] Next, the radiation performance evaluation method of a satellite sensor based on a stable target provided by the present application is introduced.

[0041] First, see Figure 1 , Figure 1 A schematic flow chart of the radiation performance evaluation method of a satellite sensor based on a stable target provided by the present application is shown. The radiation performance evaluation method of a satellite sensor based on a stable target provided by the present application may specifically include the following steps S101 to S106:

[0042] Step S101, obtaining first radiation performance remote sensing data of a first satellite sensor for evaluating radiation performance in a historical time period, and obtaining second radiation performance remote sensing data of a second satellite sensor for reference in a historical time period;

[0043] It should be understood that the data processing performed by this application is carried out within the time range of a preset historical time period, such as the historical time period of 2019-2021.

[0044] Based on the time range determined by the historical time period, radiation performance remote sensing data of a first satellite sensor for radiation performance to be evaluated and a second satellite sensor as a reference are obtained and recorded as first radiation performance remote sensing data and second radiation performance remote sensing data respectively.

[0045] Among them, the specific purpose of this application is to evaluate the radiation performance of the first satellite sensor in terms of the top of atmosphere reflectivity (Top Of Atmosphere, TOA). In this way, the radiation performance remote sensing data can directly include the data required to calculate the top of atmosphere reflectivity, or can directly include the already calculated top of atmosphere reflectivity, which is adjusted according to the specific data product of the data source.

[0046] As an example, the first satellite sensor involved in the present application can be a medium-resolution spectral imager type II (MERSI-II). In actual circumstances, it can be the medium-resolution spectral imager type II (MERSI-II) on the Fengyun-3D (FY3D) series satellites, or it can also be other satellite sensors that need or can only be evaluated through cross-calibration, such as other Fengyun series polar-orbiting satellite sensors; the second satellite sensor can be a satellite sensor such as the stable and high-precision Moderate-resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite.

[0047] In addition, it should be noted that starting from the radiation performance remote sensing data obtained here, the series of data involved itself contains data content of variable factors such as different locations, different bands, and different times, rather than just one parameter.

[0048] Step S102, extracting a first atmospheric top reflectivity corresponding to a stable target from the first radiation performance remote sensing data, and extracting a second atmospheric top reflectivity corresponding to a stable target from the second radiation performance remote sensing data, wherein the stable target is a selected geographical area;

[0049] It can be understood that, corresponding to the different ways of how the radiation performance remote sensing data obtained by the present application characterize the reflectivity of the top of the atmosphere as introduced above, an adapted extraction method is required here to obtain the corresponding reflectivity of the top of the atmosphere.

[0050] In addition, it should be noted that the atmospheric top reflectivity extracted here is specifically limited to the stable target focused on by this application, that is, a specific geographical area. For this stable target, this application believes that it can more accurately reflect the difference between the atmospheric reflectivity collected by the first satellite sensor and the second satellite sensor, so that the radiation performance of the first satellite sensor in terms of atmospheric reflectivity can be more accurately evaluated through cross-radiation calibration.

[0051] Specifically, the stable targets involved here, as an exemplary embodiment, may include four targets in total, namely, a selected desert area, a glacier area, a deep convective cloud area and an ocean current area.

[0052] That is to say, the present application believes that the radiation performance of the first satellite sensor in terms of atmospheric reflectivity can be better evaluated through four stable targets or four types of geographical areas, namely desert areas, glacier areas, deep convective cloud areas and ocean current areas, compared with other geographical areas and combinations of geographical areas.

[0053] Furthermore, as an exemplary embodiment, for the four targets focused on by this application, based on the above specific types, this application also provides more specific configuration content to obtain better observation data, so as to further improve the effect of the solution to be achieved by this application focusing on the four stable targets.

[0054] Specifically, the observation condition restrictions imposed on the four targets in this application are:

[0055] 1) For the desert area (which can be denoted as DH), a unified area of ​​20 km × 20 km centered on the corresponding first observation site is selected, and the first solar zenith angle is restricted to be less than 65° and the first observation zenith angle is less than 40° to reduce data fluctuations under high solar angles, and the standard deviation of the average reflectance of the first top of atmosphere is less than 2% (to check the spatial homogeneity of the stable target pixels extracted in the defined 20 km × 20 km area);

[0056] 2) For the glacier area (which can be denoted as DomeC), a unified range of 20 km × 20 km centered on the corresponding second observation site is selected, and the second solar zenith angle is limited to less than 70° and the standard deviation of the second atmospheric top reflectance average value is less than 2% (to eliminate the influence of clouds);

[0057] 3) For the deep convective cloud region (which can be denoted as DCC), the threshold of brightness temperature of the infrared channel of 10.78μm-11.28μm (this range also corresponds to the 31st band of MODIS) and 10.8μm (this range also corresponds to the 24th band of MERSI-II) is selected as a prerequisite for identifying potential deep convective cloud pixels in the tropical region of 20°S-20°N and 85°E–125°E (this range is given in the standard longitude and latitude coordinate system). The third solar zenith angle and the third observation zenith angle are both required to be less than 40°. In addition, in order to avoid the influence of thin clouds and cloud edges, improve the accuracy of deep convective cloud target identification, and eliminate interference noise, the standard deviation of 3×3 pixels in the visible-near infrared channel is less than 3%, and the standard deviation of brightness temperature in the infrared channel is less than 1K;

[0058] 4) For the ocean current region (which can be denoted as TNP), the circulation region in the range of 10°S–20°N and 150°E–160°E is selected, and the fourth observation zenith angle and solar flare angle are both required to be less than 40°.

[0059] It can be seen that this provides a set of specific implementation solutions for how to configure the four stability targets, which has great practical significance.

[0060] Step S103, performing spectral adjustment of the first atmosphere top reflectance and the second atmosphere top reflectance by using a spectral matching factor to reduce the difference between the spectral channels of the two sensors;

[0061] After obtaining two sets of atmospheric top reflectance data of the first satellite sensor and the second satellite sensor, the difference between the two sets of data and the spectral channels of the two sensors can be reduced by a spectral adjustment operation based on a spectral band adjustment factor (SBAF), so as to facilitate a better evaluation of the radiation performance of the first satellite sensor in the future.

[0062] Specifically, as an exemplary embodiment, the spectral adjustment of the first atmosphere top reflectance and the second atmosphere top reflectance by the spectral matching factor may include:

[0063] 1) interpolating the spectral sampling intervals of the spectral response functions of the first satellite sensor and the second satellite sensor to 1 nm;

[0064] It can be seen that the interpolation processing here not only improves the resolution (accuracy), but also aligns the spectral sampling intervals (spectral resolution) of the spectral response functions of the first satellite sensor and the second satellite sensor for subsequent processing.

[0065] 2) resample the top-of-atmosphere reflectance of the third satellite sensor with a spectral sampling interval (i.e., hyperspectral) of the spectral response function of 10 nm to 1 nm;

[0066] It can be understood that here, through resampling, the top atmosphere reflectance of the third satellite sensor is resampled from the original 10nm spectral resolution to 1nm, and aligned with the spectral sampling of the spectral response functions of the first satellite sensor and the second satellite sensor of the previous 1nm for subsequent processing.

[0067] The third satellite sensor may specifically be EO-1Hyperion.

[0068] The top atmospheric reflectivity of the third satellite sensor is obtained by processing the original third radiation performance remote sensing data of the third satellite sensor in the historical time period, wherein the processing involved can refer to the processing involved in the previous first radiation performance remote sensing data and the second radiation performance remote sensing data.

[0069] 3) The atmospheric top reflectance of the third satellite sensor at 1 nm is convolved with the channel spectral response functions of the first satellite sensor and the second satellite sensor respectively using the following formula, and the ratio of the two is fitted to obtain the spectral matching factor:

[0070]

[0071]

[0072] in, is the atmospheric top reflectance of other satellite sensors simulated by the third satellite sensor. In the same case, the value range of λ is 1 or 2, corresponding to the first satellite sensor or the second satellite sensor. ρ represents the atmospheric top reflectance of the third satellite sensor. SRF λ represents the spectral response function of the first satellite sensor or the second satellite sensor of the corresponding channel of the top atmosphere reflectance of the third satellite sensor, SBAF represents the spectral matching factor, represents the top-of-atmosphere reflectivity of the second satellite sensor generated using ρ simulation, represents the top-of-atmosphere reflectivity of the first satellite sensor generated using ρ simulation, represents the reflectance of the top of the first atmosphere adjusted by the spectral matching factor to match the reflectance of the top of the second atmosphere.

[0073] It can be understood that here, in order to determine the spectral matching factor related to the first satellite sensor and the second satellite sensor, the top atmosphere reflectance of the third satellite sensor is introduced, and combined with interpolation processing, a specific implementation scheme is provided.

[0074] Step S104, performing a bidirectional reflectance distribution function correction on the adjusted first atmosphere top reflectance to reduce the influence of the observed atmosphere top reflectance change on the time trend caused by the difference in the observed geometry;

[0075] It can be understood that after performing spectral adjustment to reduce the difference between the spectral channels of the two sensors, the first top atmosphere reflectivity can continue to be corrected by bidirectional reflectance distribution function (BRDF) to further reduce the impact of changes in observed top atmosphere reflectivity on the time trend caused by differences in observation geometry (angle parameters).

[0076] The present application considers that the bidirectional reflectance distribution function effect and the surface type, therefore, corresponding to the above four targets, there is a corresponding bidirectional reflectance distribution function correction process. Specifically, as an exemplary embodiment, the bidirectional reflectance distribution function correction model involved in the bidirectional reflectance distribution function correction of the adjusted first top atmosphere reflectivity can be:

[0077] 1) Corresponding to the desert area and the ocean current area, there are:

[0078] R(θ s ,θv ,φ)=k0+k1f1(θ s ,θ v ,φ)+k2f2(θ s ,θ v ,φ),

[0079]

[0080] cosξ=cosθ s cosθ v +sinθ s sinθ v cosφ,

[0081] Among them, R(θ s ,θ v ,φ) represents the atmospheric top reflectivity after model correction, θ s represents the solar zenith angle, θ v represents the observation zenith angle, φ represents the relative azimuth, f1(θ s ,θ v ,φ) represents the volume scattering component, f2(θ s ,θ v ,φ) represents the components of surface scattering and geometric projection, k0, k1 and k2 represent different model coefficients related to the surface type, and cosξ represents an intermediate quantity;

[0082] 2) Corresponding to the glacier area, there are:

[0083] R(θ s ,θ v ,φ)=c1+c2cos(π―φ)+c3cos[2(π―φ)],

[0084] c1=a0+a1(1―cosθ v ),c2=a2(1―cosθ v ),c3=a3(1―cosθ v ),

[0085] a i =b 0i +b 1i cosθ s +b 2i cos 2 θ s ,i=0,1,2,

[0086] Among them, a i Indicates the intermediate quantity, b 0i represents the different model coefficients of the model corresponding to the glacier area;

[0087] 3) For deep convective cloud regions, the Clouds and the Earth's Radiant Energy System (CERES) has established a deep convective cloud angle distribution model for different cloud amounts and different cloud optical thicknesses (cloud parameters, aerosols) based on high-calibration precision observation data from satellites such as Aqua, Terra, and TRMM. This model has been widely used in the field of sensor radiation calibration research based on deep convective cloud targets. The model is a bidirectional reflectance distribution function calibration parameter lookup table. The bidirectional reflectance distribution function correction factor in each deep convective cloud pixel can be obtained by looking up a set of solar zenith angles, observation zenith angles, and relative azimuth angles given by the lookup table. Correspondingly, a lookup table with cloud amounts greater than 99.9% and cloud optical thickness greater than 50 is selected, and the following can be obtained:

[0088]

[0089] Among them, F BRDF (θ s ,θ v ,φ) represents the bidirectional reflectance distribution function correction factor of this geometric angle at a certain set of solar zenith angle, observation zenith angle and relative azimuth angle, ρ TOA (θ s ,θ v ,φ) represents the reflectivity of the top of the atmosphere at the said geometric angle.

[0090] It should be noted that the series of parameters of the three models here are provided by the data of the first atmosphere top reflectance after spectral adjustment.

[0091] Thus, a specific implementation scheme is provided here for how the present application realizes the bidirectional reflection distribution function correction.

[0092] Step S105, calculating the ratio of the original first atmosphere top reflectivity and the first atmosphere top reflectivity corrected by the bidirectional reflectance distribution function as the normalized atmosphere top reflectivity;

[0093] After completing the bidirectional reflectance distribution function correction for the reflectance of the first atmosphere top after the spectrum adjustment, the reflectance of the first atmosphere top after the bidirectional reflectance distribution function correction can be obtained.

[0094] At this time, corresponding to the subsequent radiation performance evaluation processing, the ratio of the original first atmosphere top reflectance (that is, the first atmosphere top reflectance before spectral adjustment and bidirectional reflectance distribution function correction, the observed value is the output value of step S102) and the first atmosphere top reflectance after bidirectional reflectance distribution function correction can be calculated, that is, the former is used as the numerator and the latter is used as the denominator, and the obtained ratio is recorded as the normalized atmosphere top reflectance.

[0095] To facilitate understanding of the ratio calculation process here, it can also be expressed by the following formula:

[0096]

[0097] Among them, R TOA represents the normalized top-of-atmosphere reflectivity, ρ TOA represents the original first atmosphere top reflectivity, R(θ s ,θ v ,φ) represents the reflectivity of the first top of atmosphere after bidirectional reflectance distribution function correction.

[0098] Once the normalized atmospheric top reflectivity is obtained, it can be used as input for subsequent radiation performance quantification processing to achieve the radiation performance evaluation goal.

[0099] Step S106, based on the normalized atmospheric top reflectivity, the radiation performance of the first satellite sensor is quantified by a preset quantitative index.

[0100] It can be understood that after the normalized top-of-atmosphere reflectivity is obtained, the radiation performance of the first satellite sensor can be effectively quantified according to the quantitative indicators preset in this application (corresponding to the corresponding specific indicator calculation formula / strategy).

[0101] Specifically, as an exemplary embodiment, here, based on the normalized atmospheric top reflectivity, the radiation performance of the first satellite sensor is quantified by a preset quantitative index, which may include:

[0102] Based on the normalized top-of-atmosphere reflectivity, the radiation performance of the first satellite sensor is quantified through three quantitative indicators: total attenuation rate, annual average attenuation rate, and P value verification.

[0103] 1) The total attenuation rate, which characterizes the overall degradation of radiation performance, can be expressed by the following formula:

[0104]

[0105] The atmospheric reflectance on the 15th of each month is used to represent the atmospheric reflectance of the month. start Indicates the 15th of the first month in the historical time period, x end Indicates the 15th of the last month in the historical period, R TOA (x start ) represents the normalized top-of-atmosphere reflectance on the 15th day of the first month, R TOA (x end ) represents the normalized top-of-atmosphere reflectance on the 15th day of the last month;

[0106] 2) The annual average attenuation rate, which characterizes the annual average degradation degree of radiation performance, can be expressed by the following formula:

[0107]

[0108] Among them, D year represents the average annual decay rate, D all represents the total decay rate;

[0109] 3) In order to characterize the stability of radiation performance, a linear regression can be performed on the long-term trend of the reflectivity of each channel. The slope of the regression line can indicate the stability of the sensor radiation calibration. Among them, the common method for testing the slope of the regression line is the P value test, which can be expressed by the following formula:

[0110] R TOA (x i )=β0+β1x i ,

[0111] H0:β1=0,

[0112] H1:β1≠0,

[0113] If β1=0, R TOA (x i )=β0,

[0114] Among them, x i represents the i-th observation time, R TOA (x i ) represents the i-th normalized atmospheric top reflectance, β0 represents the intercept of the regression line, β1 represents the slope of the regression line, H0 represents the null hypothesis, H1 represents the alternative hypothesis,

[0115] The original hypothesis indicates that the slope of the long-term trend of the radiation performance of the (sensor) in each band is 0, indicating that the radiation performance of the (sensor) in the current band is stable and has not degraded.

[0116] The alternative assumptions indicate that the radiation performance is unstable and may be degraded in the current band.

[0117] The P value is used to reject or explain the null hypothesis.

[0118] If the P value is < 0.05, the null hypothesis is rejected.

[0119] If the P value is ≥ 0.05, the null hypothesis cannot be rejected.

[0120] As an example, the calculated total decay rate and annual decay rate can be shown in the following table:

[0121] Table 1 - Quantitative Indicator Example 1

[0122]

[0123] Among them, band represents the band number, WV represents the specific band value, DH, DomeC, DCC and TNP correspond to the four stable targets mentioned above, namely the desert area, glacier area, deep convective cloud area and ocean current area, the COM on the left represents the normalized mean of the top of atmosphere reflectivity of the four stable targets, and the COM on the right represents the normalized mean of the top of atmosphere reflectivity of the four stable targets.

[0124] As another example, the P value verification result can be shown in the following table:

[0125] Table 2 - Quantitative Indicator Example 2

[0126]

[0127] Among them, band represents the band number, WV represents the specific band value, DH, DomeC, DCC and TNP correspond to the four stable targets mentioned above, namely the desert area, glacier area, deep convective cloud area and ocean current area, and Com represents the normalized mean of the top atmospheric reflectivity of the four stable targets.

[0128] It can be understood that after determining the radiation indicators at different locations, different bands, and different times, the preset radiation indicator threshold or standard range can be combined to screen out the substandard bands and their corresponding data. Once the accurate radiation performance evaluation is completed, the corresponding correction (calibration) processing can be continued.

[0129] In this regard, as an exemplary embodiment, after quantifying the radiation performance of the first satellite sensor through a preset quantitative index based on the normalized atmospheric top reflectivity, the radiation performance evaluation method of the satellite sensor based on a stable target of the present application may further include:

[0130] For bands where the quantified results of radiation performance exceed the standard range, correction is performed using the following formula:

[0131]

[0132] Among them, R TOAN It represents the normalized atmospheric top reflectance of the band whose quantification result of radiation performance exceeds the standard range. A and D represent different fitting parameters. t0 represents the starting time, and t represents the time of the data to be corrected (i.e., the time of the satellite image to be processed currently).

[0133] It can be seen that the present application designs a time attenuation model here, which can correct the corresponding data of the substandard bands with better performance.

[0134] As an example, the following table shows:

[0135] Table 3 - Correction Example 1

[0136]

[0137] Among them, band represents the band number, WV represents the specific band value, DH, DomeC, DCC and TNP correspond to the four stable targets mentioned above, namely desert area, glacier area, deep convective cloud area and ocean current area, R 2 AD and RMSE are two commonly used evaluation indicators in the field of mathematical statistics. It can be seen that the numerical level is low, which means that the prediction result is very good.

[0138] Furthermore, the positive changes brought about by the correction processing here can be more vividly understood by combining the total decay rate and annual decay rate mentioned above, as shown in another example below:

[0139] Table 4 - Correction Example 2

[0140]

[0141] band represents the band number, WV represents the specific band value, DH, DomeC, DCC and TNP correspond to the four stable targets mentioned above, namely the desert area, glacier area, deep convective cloud area and ocean current area, and COM represents the normalized mean of the top of atmosphere reflectivity of the four stable targets.

[0142] At the same time, for the processing of the above stages, the corresponding images of the processing process / results can be presented in a visual interface through tabulation / charting, so as to more vividly reflect the effect of the scheme made by the present application, which may also involve the processing device itself having a display screen, the processing device using an external display screen device, or the processing device linking with other devices with display screens.

[0143] Regarding the above scheme content, in general, for the cross-radiation calibration target of the top of atmosphere reflectivity, the present application first obtains the first radiation performance remote sensing data of the first satellite sensor to be evaluated for radiation performance in a historical time period, and obtains the second radiation performance remote sensing data of the second satellite sensor as a reference in a historical time period, and then extracts the first top of atmosphere reflectivity corresponding to the first radiation performance remote sensing data and the stable target, and extracts the second top of atmosphere reflectivity corresponding to the second radiation performance remote sensing data and the stable target, wherein the stable target is a selected geographical area, at this time, the spectra of the first top of atmosphere reflectivity and the second top of atmosphere reflectivity are adjusted by the spectral matching factor to reduce the difference in the spectral channels of the two sensors, and then the adjusted The first top of atmosphere reflectivity is corrected by a bidirectional reflectance distribution function to reduce the impact of changes in the observed top of atmosphere reflectivity on the time trend caused by differences in observed geometric shapes, and then the ratio of the original first top of atmosphere reflectivity and the first top of atmosphere reflectivity corrected by the bidirectional reflectance distribution function is calculated as the normalized top of atmosphere reflectivity. At this time, based on the normalized top of atmosphere reflectivity, the radiation performance of the first satellite sensor is quantified by a preset quantitative indicator. Thus, the present application provides a novel cross-radiation calibration mechanism, which can be combined with a high-precision second satellite sensor to perform a high-precision radiation performance evaluation of the top of atmosphere reflectivity for the first satellite sensor, and further can perform a high-precision correction for the top of atmosphere reflectivity collected by the first satellite sensor.

[0144] Among them, the effect of this application scheme can also be reflected in the following four aspects:

[0145] 1) By setting up four stable targets, the radiation performance of the first satellite sensor in the visible light, near-infrared and short-wave infrared bands was comprehensively evaluated, and the bands with attenuated radiation performance could be corrected, which greatly improved its radiation calibration accuracy and provided a basis for its quantitative application in global change detection.

[0146] 2) It provides a reference for the coordinated application of the first satellite sensor and the second satellite sensor (such as MERSI-II and MODIS).

[0147] 3) Four different stable targets designed specifically for the assessment (desert area, glacier area, deep convective cloud area and ocean current area) have good consistency and can be well applied to the radiometric calibration of the first satellite sensors (such as MERSI-II).

[0148] 4) In actual situations, in addition to being applicable to the radiation performance evaluation of MERSI-II, it is also applicable to the radiation performance evaluation of other satellite sensors such as the Fengyun series polar-orbiting satellite sensors.

[0149] The above is an introduction to the radiation performance evaluation method of a satellite sensor based on a stable target provided by the present application. In order to facilitate better implementation of the radiation performance evaluation method of a satellite sensor based on a stable target provided by the present application, the present application also provides a radiation performance evaluation device of a satellite sensor based on a stable target from the perspective of functional modules.

[0150] See also Figure 2 , Figure 2 This is a schematic diagram of a structure of a radiation performance evaluation device of a satellite sensor based on a stable target in the present application. In the present application, the radiation performance evaluation device 200 of a satellite sensor based on a stable target may specifically include the following structure:

[0151] An acquisition unit 201 is used to acquire first radiation performance remote sensing data of a first satellite sensor to be evaluated for radiation performance in a historical time period, and to acquire second radiation performance remote sensing data of a second satellite sensor as a reference in a historical time period;

[0152] An extraction unit 202 is used to extract a first top of atmosphere reflectivity corresponding to a stable target from the first radiation performance remote sensing data, and to extract a second top of atmosphere reflectivity corresponding to a stable target from the second radiation performance remote sensing data, wherein the stable target is a selected geographical area;

[0153] An adjustment unit 203, configured to perform spectral adjustment of the first atmosphere top reflectance and the second atmosphere top reflectance by using a spectral matching factor to reduce the difference between spectral channels of the two sensors;

[0154] A correction unit 204, configured to perform a bidirectional reflectance distribution function correction on the adjusted first top of atmosphere reflectivity to reduce the influence of the observed top of atmosphere reflectivity change on the time trend caused by the difference in the observed geometry;

[0155] A calculation unit 205 is used to calculate the ratio of the original first atmosphere top reflectivity and the first atmosphere top reflectivity corrected by the bidirectional reflectance distribution function as the normalized atmosphere top reflectivity;

[0156] The quantification unit 206 is used to quantify the radiation performance of the first satellite sensor through a preset quantitative index based on the normalized atmospheric top reflectivity.

[0157] In yet another exemplary embodiment, the stable targets specifically include four targets, namely, a selected desert area, a glacier area, a deep convective cloud area, and an ocean current area.

[0158] In another exemplary embodiment, the observation condition restrictions imposed on the four targets are:

[0159] For desert areas, a unified area of ​​20 km × 20 km centered on the corresponding first observation site was selected, and the first solar zenith angle was restricted to be less than 65°, the first observation zenith angle to be less than 40°, and the standard deviation of the mean value of the first top of atmosphere reflectivity to be less than 2%;

[0160] For the glacier area, a uniform range of 20 km × 20 km centered on the corresponding second observation site was selected, and the second solar zenith angle was restricted to be less than 70° and the standard deviation of the mean value of the second top of atmosphere reflectivity was less than 2%;

[0161] For deep convective cloud regions, the threshold of brightness temperature less than 205 K in the 10.78 μm–11.28 μm and 10.8 μm infrared channels was selected as a prerequisite for identifying potential deep convective cloud pixels in the tropical region with a range of 20°S–20°N and 85°E–125°E. Both the third solar zenith angle and the third observation zenith angle needed to be less than 40°, the standard deviation of 3 × 3 pixels in the visible-near infrared channel was less than 3%, and the standard deviation of brightness temperature in the infrared channel was less than 1 K;

[0162] For the ocean current area, the circulation area in the range of 10°S–20°N and 150°E–160°E is selected, and the fourth observation zenith angle and solar flare angle are both required to be less than 40°.

[0163] In another exemplary embodiment, a bidirectional reflectance distribution function correction model involved in performing bidirectional reflectance distribution function correction on the adjusted first atmosphere top reflectance is:

[0164] Corresponding to the desert area and the ocean current area, there are:

[0165] R(θ s ,θ v ,φ)=k0+k1f1(θ s ,θ v ,φ)+k2f2(θ s ,θ v ,φ),

[0166]

[0167] cosξ=cosθ s cosθ v +sinθ s sinθ v cosφ,

[0168] Among them, R(θ s ,θ v ,φ) represents the atmospheric top reflectivity after model correction, θ s represents the solar zenith angle, θ vrepresents the observation zenith angle, φ represents the relative azimuth, f1(θ s ,θ v ,φ) represents the volume scattering component, f2(θ s ,θ v ,φ) represents the components of surface scattering and geometric projection, k0, k1 and k2 represent different model coefficients related to the surface type, and cosξ represents an intermediate quantity;

[0169] Corresponding to the glacier area, there are:

[0170] R(θ s ,θ v ,φ)=c1+c2cos(π―φ)+c3cos[2(π―φ)],

[0171] c1=a0+a1(1―cosθ v ),c2=a2(1―cosθ v ),c3=a3(1―cosθ v ),

[0172] a i =b 0i +b 1i cosθ s +b 2i cos 2 θ s ,i=0,1,2,

[0173] Among them, a i Indicates the intermediate quantity, b 0i represents the different model coefficients of the model corresponding to the glacier area;

[0174] Corresponding to the deep convective cloud area, we have:

[0175]

[0176] Among them, F BRDF (θ s ,θ v ,φ) represents the bidirectional reflectance distribution function correction factor of this geometric angle at a certain set of solar zenith angle, observation zenith angle and relative azimuth angle, ρ TOA (θ s ,θ v ,φ) represents the reflectivity of the top of the atmosphere at the said geometric angle.

[0177] In another exemplary embodiment, the spectrum matching factor includes the following processing contents:

[0178] 1) interpolating the spectral sampling intervals of the spectral response functions of the first satellite sensor and the second satellite sensor to 1 nm;

[0179] 2) resample the top-of-atmosphere reflectance of the third satellite sensor with a spectral sampling interval of 10 nm spectral response function to 1 nm;

[0180] 3) The atmospheric top reflectance of the third satellite sensor at 1 nm is convolved with the channel spectral response functions of the first satellite sensor and the second satellite sensor respectively using the following formula, and the ratio of the two is fitted to obtain the spectral matching factor:

[0181]

[0182] ρ*2=ρ1×SBAF,

[0183] in, is the atmospheric top reflectance of other satellite sensors simulated by the third satellite sensor. In the same case, the value range of λ is 1 or 2, corresponding to the first satellite sensor or the second satellite sensor. ρ represents the atmospheric top reflectance of the third satellite sensor. SRF λ represents the spectral response function of the first satellite sensor or the second satellite sensor of the corresponding channel of the top atmosphere reflectance of the third satellite sensor, SBAF represents the spectral matching factor, represents the top-of-atmosphere reflectivity of the second satellite sensor generated using ρ simulation, represents the top-of-atmosphere reflectivity of the first satellite sensor generated using ρ simulation, represents the reflectance of the top of the first atmosphere adjusted by the spectral matching factor to match the reflectance of the top of the second atmosphere.

[0184] In another exemplary embodiment, the quantization unit 206 specifically includes:

[0185] Based on the normalized top-of-atmosphere reflectivity, the radiation performance of the first satellite sensor is quantified through three quantitative indicators: total attenuation rate, annual average attenuation rate, and P value verification.

[0186] The total attenuation rate is expressed by the following formula:

[0187]

[0188] The atmospheric reflectance on the 15th of each month is used to represent the atmospheric reflectance of the month. start Indicates the 15th of the first month in the historical time period, x end Indicates the 15th of the last month in the historical period, R TOA (x start ) represents the normalized top-of-atmosphere reflectance on the 15th day of the first month, R TOA (x end) represents the normalized top-of-atmosphere reflectance on the 15th day of the last month;

[0189] The annual average decay rate is expressed by the following formula:

[0190]

[0191] Among them, D year represents the average annual decay rate, D all represents the total decay rate;

[0192] For the P value check, it is expressed by the following formula:

[0193] R TOA (x i )=β0+β1x i ,

[0194] H0:β1=0,

[0195] H1:β1≠0,

[0196] If β1=0, R TOA (x i )=β0,

[0197] Among them, x i represents the i-th observation time, R TOA (x i ) represents the i-th normalized atmospheric top reflectance, β0 represents the intercept of the regression line, β1 represents the slope of the regression line, H0 represents the null hypothesis, H1 represents the alternative hypothesis,

[0198] The original hypothesis indicates that the slope of the long-term trend of the radiation performance in each band is 0, indicating that the radiation performance in the current band is stable and has not degraded.

[0199] The alternative assumptions indicate that the radiation performance is unstable and may be degraded in the current band.

[0200] If the P value is < 0.05, the null hypothesis is rejected.

[0201] If the P value is ≥ 0.05, the null hypothesis cannot be rejected.

[0202] In another exemplary embodiment, the normalized top of atmosphere reflectivity involves different wavebands, and the apparatus further includes a correction unit 207, configured to:

[0203] For bands where the quantified results of radiation performance exceed the standard range, correction is performed using the following formula:

[0204]

[0205] Among them, R TOANIt represents the normalized top-of-atmosphere reflectivity of the band whose quantification result of radiation performance exceeds the standard range. A and D represent different fitting parameters. t0 represents the starting time, and t represents the time of the data to be corrected.

[0206] This application also provides a processing device from the perspective of hardware structure, see Figure 3 , Figure 3 301, a memory 302, and an input / output device 303. The processor 301 is used to execute the computer program stored in the memory 302 to implement the following Figure 1 The steps of the method for evaluating the radiation performance of a satellite sensor based on a stable target in the corresponding embodiment; or, the processor 301 is used to execute the computer program stored in the memory 302 to implement the following Figure 2 Corresponding to the functions of each unit in the embodiment, the memory 302 is used to store the processor 301 executing the above Figure 1 The computer program required for the radiation performance evaluation method of a satellite sensor based on a stable target in the corresponding embodiment.

[0207] Exemplarily, the computer program may be divided into one or more modules / units, one or more modules / units are stored in the memory 302, and executed by the processor 301 to complete the present application. One or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the computer device.

[0208] The processing device may include, but is not limited to, a processor 301, a memory 302, and an input / output device 303. Those skilled in the art will appreciate that the illustration is merely an example of a processing device and does not constitute a limitation on the processing device, and may include more or fewer components than shown in the illustration, or a combination of certain components, or different components. For example, the processing device may also include a network access device, a bus, etc., and the processor 301, the memory 302, the input / output device 303, etc. are connected via a bus.

[0209] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the processing device, and uses various interfaces and lines to connect various parts of the entire device.

[0210] The memory 302 can be used to store computer programs and / or modules. The processor 301 implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory 302 and calling the data stored in the memory 302. The memory 302 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the processing device, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0211] When the processor 301 is used to execute the computer program stored in the memory 302, the following functions can be implemented:

[0212] Acquire first radiation performance remote sensing data of a first satellite sensor for evaluating radiation performance in a historical time period, and acquire second radiation performance remote sensing data of a second satellite sensor for reference in a historical time period;

[0213] Extracting a first top-of-atmosphere reflectivity corresponding to a stable target from the first radiation property remote sensing data, and extracting a second top-of-atmosphere reflectivity corresponding to a stable target from the second radiation property remote sensing data, wherein the stable target is a selected geographical area;

[0214] Spectra of the first top-of-atmosphere reflectance and the second top-of-atmosphere reflectance are adjusted by a spectral matching factor to reduce the difference between the spectral channels of the two sensors;

[0215] A bidirectional reflectance distribution function correction is performed on the adjusted first top-of-atmosphere reflectance to reduce the impact of observed top-of-atmosphere reflectance changes on the temporal trend due to differences in observation geometry;

[0216] Calculate the ratio of the original first atmosphere top reflectance and the first atmosphere top reflectance corrected by the bidirectional reflectance distribution function as the normalized atmosphere top reflectance;

[0217] Based on the normalized top-of-atmosphere reflectivity, the radiation performance of the first satellite sensor is quantified through preset quantitative indicators.

[0218] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the above-described stable target based satellite sensor radiation performance evaluation device, processing equipment and corresponding units can refer to the following. Figure 1 The description of the radiation performance evaluation method of the satellite sensor based on the stable target in the corresponding embodiment will not be repeated here in detail.

[0219] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0220] To this end, the present application provides a computer-readable storage medium, in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the present application as follows: Figure 1 The steps of the radiation performance evaluation method of the satellite sensor based on the stable target in the corresponding embodiment, the specific operation can refer to the following Figure 1 The description of the radiation performance evaluation method of the satellite sensor based on the stable target in the corresponding embodiment will not be repeated here.

[0221] The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0222] Due to the instructions stored in the computer-readable storage medium, the present application can be executed. Figure 1 The steps of the radiation performance evaluation method of the satellite sensor based on the stable target in the corresponding embodiment, therefore, the present application can be implemented as follows Figure 1 The beneficial effects that can be achieved by the radiation performance evaluation method of a satellite sensor based on a stable target in the corresponding embodiment are detailed in the previous description and will not be repeated here.

[0223] The above is a detailed introduction to the radiation performance evaluation method, device, processing equipment and computer-readable storage medium of the satellite sensor based on stable targets provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for evaluating the radiation performance of a satellite sensor based on a stable target, characterized in that: The method comprises: Acquire first radiation performance remote sensing data of a first satellite sensor for evaluating radiation performance in a historical time period, and acquire second radiation performance remote sensing data of a second satellite sensor for reference in the historical time period; Extracting a first top-of-atmosphere reflectivity corresponding to a stable target from the first radiation property remote sensing data, and extracting a second top-of-atmosphere reflectivity corresponding to the stable target from the second radiation property remote sensing data, wherein the stable target is a selected geographical area; Performing spectral adjustment of the first atmosphere top reflectance and the second atmosphere top reflectance by a spectral matching factor to reduce the difference between spectral channels of two sensors; Performing a bidirectional reflectance distribution function correction on the adjusted first top of atmosphere reflectivity to reduce the influence of the observed top of atmosphere reflectivity change on the time trend caused by the difference in observation geometry; Calculating a ratio of the original first atmosphere top reflectivity and the first atmosphere top reflectivity corrected by the bidirectional reflectance distribution function as a normalized atmosphere top reflectivity; Based on the normalized top-of-atmosphere reflectivity, the radiation performance of the first satellite sensor is quantified by a preset quantitative index.

2. The method according to claim 1, characterized in that The stable targets specifically include four targets, namely, selected desert areas, glacier areas, deep convective cloud areas and ocean current areas.

3. The method according to claim 2, characterized in that The observation condition restrictions imposed on the four targets are: For the desert area, a unified area of ​​20 km × 20 km centered on the corresponding first observation site is selected, and the first solar zenith angle is limited to be less than 65°, the first observation zenith angle is less than 40°, and the standard deviation of the average reflectance of the first top of the atmosphere is less than 2%; For the glacier area, a uniform range of 20 km × 20 km centered on the corresponding second observation site was selected, and the second solar zenith angle was restricted to be less than 70° and the standard deviation of the mean value of the second top of atmosphere reflectivity was less than 2%; For deep convective cloud regions, the threshold of brightness temperature less than 205 K in the 10.78 μm–11.28 μm and 10.8 μm infrared channels was selected as a prerequisite for identifying potential deep convective cloud pixels in the tropical region with a range of 20°S–20°N and 85°E–125°E. Both the third solar zenith angle and the third observation zenith angle needed to be less than 40°, the standard deviation of 3 × 3 pixels in the visible-near infrared channel was less than 3%, and the standard deviation of brightness temperature in the infrared channel was less than 1 K; For the ocean current area, the circulation area within the range of 10°S–20°N and 150°E–160°E is selected, and the fourth observation zenith angle and solar flare angle are both required to be less than 40°.

4. The method according to claim 3, characterized in that The bidirectional reflectance distribution function correction model involved in performing bidirectional reflectance distribution function correction on the adjusted first atmosphere top reflectance includes: Corresponding to the desert area and the ocean current area, there are: R(θ s ,i v ,φ)=k0+k1f1(θ s ,i v ,φ)+k2f2(θ s ,i v ,φ), cosξ=cosθ s cosθ v +sinθ s sinth v cosφ, Among them, R(θ s ,θ v ,φ) represents the atmospheric top reflectivity after model correction, θ s represents the solar zenith angle, θ v represents the observation zenith angle, φ represents the relative azimuth, f1(θ s ,θ v ,φ) represents the volume scattering component, f2(θ s ,θ v ,φ) represents the components of surface scattering and geometric projection, k0, k1 and k2 represent different model coefficients related to the surface type, and cosξ represents an intermediate quantity; Corresponding to the glacier area, there are: R(θ s ,i v ,φ)=c1+c2cos(π―φ)+c3cos[2(π―φ)], c1=a0+a1(1―cosθ v ),c2=a2(1―cosθ v ),c3=a3(1―cosθ v ), a i =b 0i +b 1i cosθ s +b 2i cos 2 i s ,i=0,1,2, Among them, a i Indicates the intermediate quantity, b 0i represents the different model coefficients of the model corresponding to the glacier area; Corresponding to the deep convective cloud area, there are: Among them, F BRDF (θ s ,θ v ,φ) represents the bidirectional reflectance distribution function correction factor of this geometric angle at a certain set of solar zenith angle, observation zenith angle and relative azimuth angle, ρ TOA (θ s ,θ v ,φ) represents the reflectivity of the top of the atmosphere at the said geometric angle.

5. The method according to claim 1, characterized in that The spectral matching factor includes the following processing contents: 1) interpolating the spectral sampling intervals of the spectral response functions of the first satellite sensor and the second satellite sensor to 1 nm; 2) resample the top-of-atmosphere reflectance of the third satellite sensor with a spectral sampling interval of 10 nm spectral response function to 1 nm; 3) The atmospheric top reflectance of the third satellite sensor at 1 nm is convolved with the channel spectral response functions corresponding to the first satellite sensor and the second satellite sensor respectively using the following formula, and the ratio of the two is fitted to obtain the spectral matching factor: in, is the atmospheric top reflectance of other satellite sensors simulated and generated by the third satellite sensor. In the same case, the value range of λ is 1 or 2, corresponding to the first satellite sensor or the second satellite sensor. ρ represents the atmospheric top reflectance of the third satellite sensor. SRF λ represents the spectral response function of the first satellite sensor or the second satellite sensor of the channel corresponding to the atmospheric top reflectance of the third satellite sensor, SBAF represents the spectral matching factor, represents the top-of-atmosphere reflectivity of the second satellite sensor generated using ρ simulation, represents the top-of-atmosphere reflectivity of the first satellite sensor generated using ρ simulation, represents the first atmosphere top reflectance adjusted by the spectral matching factor to match the second atmosphere top reflectance.

6. The method according to claim 1, characterized in that The step of quantifying the radiation performance of the first satellite sensor based on the normalized top of atmosphere reflectivity by using a preset quantitative index includes: Based on the normalized top of atmosphere reflectivity, the radiation performance of the first satellite sensor is quantified by verifying three quantitative indicators, namely, total attenuation rate, annual average attenuation rate and P value; The total attenuation rate is expressed by the following formula: The atmospheric reflectance on the 15th of each month is used to represent the atmospheric reflectance of the month. start Indicates the 15th of the first month in the historical period, x end Indicates the 15th of the last month in the historical period, R TOA (x start ) represents the normalized atmospheric top reflectance on the 15th day of the first month, R TOA (x end ) represents the normalized top-of-atmosphere reflectance on the 15th day of the last month; The annual average decay rate is expressed by the following formula: Among them, D year represents the average annual decay rate, D all represents the total attenuation rate; The P value check is expressed by the following formula: R TOA (x i )=β0+β1x i , H0:β1＝0， H1:β1≠0， ifβ1=0,R TOA (x i )=β0, Among them, x i represents the i-th observation time, R TOA (x i ) represents the normalized atmospheric top reflectance of the ith, β0 represents the intercept of the regression line, β1 represents the slope of the regression line, H0 represents the null hypothesis, H1 represents the alternative hypothesis, The original hypothesis indicates that the slope of the long-term trend of the radiation performance in each band is 0, indicating that the radiation performance in the current band is stable and has not degraded. The alternative assumption states that the radiated performance is not stable and may be degraded in the current band described. If the P value is < 0.05, the null hypothesis is rejected. If the P value is ≥ 0.05, the null hypothesis cannot be rejected.

7. The method according to claim 1, characterized in that The normalized top of atmosphere reflectance involves different bands. After quantifying the radiation performance of the first satellite sensor by a preset quantitative index based on the normalized top of atmosphere reflectance, the method further includes: For bands where the quantified results of radiation performance exceed the standard range, correction is performed using the following formula: Among them, R TOAN The normalized top-of-atmosphere reflectivity of the band where the quantified result of radiation performance exceeds the standard range, A and D represent different fitting parameters, t0 represents the starting time, and t represents the time at which the data is to be corrected.

8. A radiation performance evaluation device for a satellite sensor based on a stable target, characterized in that: The device comprises: An acquisition unit, configured to acquire first radiation performance remote sensing data of a first satellite sensor for evaluating radiation performance in a historical time period, and to acquire second radiation performance remote sensing data of a second satellite sensor for reference in the historical time period; an extraction unit, configured to extract a first top-of-atmosphere reflectivity corresponding to a stable target from the first radiation performance remote sensing data, and to extract a second top-of-atmosphere reflectivity corresponding to the second radiation performance remote sensing data, wherein the stable target is a selected geographical area; an adjustment unit, configured to perform spectral adjustments of the first atmosphere top reflectance and the second atmosphere top reflectance by using a spectral matching factor, so as to reduce a difference between spectral channels of two sensors; a correction unit, configured to perform a bidirectional reflectance distribution function correction on the adjusted first top of atmosphere reflectivity to reduce the influence of the observed top of atmosphere reflectivity change on the time trend caused by the difference in observation geometry; a calculation unit, used for calculating a ratio of an original first atmosphere top reflectance and the first atmosphere top reflectance corrected by the bidirectional reflectance distribution function as a normalized atmosphere top reflectance; The quantification unit is used to quantify the radiation performance of the first satellite sensor based on the normalized top of atmosphere reflectivity through a preset quantitative index.

9. A processing device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program, and the processor executes the method according to any one of claims 1 to 7 when calling the computer program in the memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the method according to any one of claims 1 to 7.

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