CN114218786A - On-orbit polarization radiation characteristic inversion method for non-polarization satellite sensor - Google Patents
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Abstract
The embodiment of the invention provides an on-orbit polarization radiation characteristic inversion method for a non-polarization satellite sensor. The method comprises the following steps: acquiring satellite observation data of an ocean surface scene area acquired by a non-polarized satellite sensor after orbit as a ground object observation target; preprocessing the satellite observation data; acquiring environment data of the ocean surface scene area and preprocessing the environment data to obtain ocean surface environment data; constructing an ocean surface three-dimensional model by using the ocean surface environment data; and simulating the polarization radiation state of the ocean surface by combining Fresnel reflection law based on the ocean surface three-dimensional model. The method can invert and analyze the polarization radiation characteristic of the non-polarization satellite sensor after the orbit to obtain the polarization radiation state of the atmospheric cap; the polarization sensitivity of the instrument is analyzed along with the observation geometry and environmental conditions, the change rule of the polarization radiation of the instrument along with different conditions is obtained, and the method has guiding significance for the polarization correction and radiation calibration of the subsequent non-polarization satellite sensor.
Description
Technical Field
The invention relates to the technical field of satellite remote sensing, in particular to an on-orbit polarization radiation characteristic inversion method of a non-polarization satellite sensor.
Background
In remote sensing detection, the radiation polarization state of a ground object target can be used for inverting wind speed, aerosol type, optical thickness and the like, and related radiation polarization detectors are carried on satellites at home and abroad for detecting and analyzing polarization information. However, for a non-polarized satellite sensor, polarization is interference information, the polarization sensitivity of a radiation transmission link affects the accuracy of remote sensing observation data and subsequent application thereof, and inversion analysis and quantitative removal need to be performed on the polarization sensitivity of an instrument to improve radiometric calibration accuracy.
The on-orbit polarized radiation correction of the instrument is mainly carried out by combining the polarization sensitivity of the instrument obtained by laboratory measurement before emission and the atmospheric top polarized radiation state of an observation target simulated by a radiation transmission simulation tool. However, since some domestic satellite instruments in the past do not measure the polarization sensitivity of the laboratory before launching, and the on-orbit characteristics of the instruments often deviate from the state of the laboratory before launching, it is necessary to perform on-orbit polarization radiation characteristic inversion on the instruments by using the acquired specific remote sensing scene for the non-polarization satellite sensors after the on-orbit, and analyze the polarization sensitivity of the instruments, so as to more accurately perform on-orbit polarization radiation correction and calibration on the instruments.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide an on-orbit polarized radiation characteristic inversion method for a non-polarized satellite sensor, which can be used for modeling, inverting and analyzing the polarized radiation response of a radiation link of a non-polarized instrument so as to more accurately correct the on-orbit polarized radiation of the instrument.
In order to achieve the above object, the present application provides an in-orbit polarization radiation characteristic inversion method for a non-polarized satellite sensor, comprising the following steps:
s1, selecting an ocean surface scene remote sensing image obtained after the non-polarized satellite sensor is in orbit as a ground object observation target;
s2, preprocessing satellite observation data of the ocean surface scene area;
s3, selecting and preprocessing the environmental data of the ocean surface scene area;
s4, constructing an ocean surface three-dimensional model by using the ocean surface environment data;
s5, simulating the polarization radiation state of the real ocean surface by combining the Fresnel reflection law;
s6, analyzing the influence of atmospheric scattering on the radiation polarization state based on a radiation transmission simulation tool, and establishing an atmospheric radiation polarization state lookup table;
s7, coupling the radiation state of the ocean surface with the radiation transmission state of the atmosphere to obtain the atmospheric top polarization radiation state of the ocean surface scene;
and S8, analyzing the polarization radiation characteristics of the sensor in a specific wave band for different observation geometries and different environments to obtain the change rule of the polarization sensitivity of the sensor, and realizing the inversion of the on-orbit polarization radiation characteristics of the non-polarization sensor.
In some optional embodiments, the ocean surface scene remote sensing image selected in step S1 is obtained by selecting an ocean surface with a large area through orbit prediction, and obtaining Level1 data of a solar reflection band of the ocean surface scene remote sensing image.
Further, the preprocessing of the satellite observation data of the ocean surface scene area in step S2 includes:
performing reflectivity calibration on satellite observation data of the selected ocean surface scene area;
carrying out cloud detection processing on the calibrated satellite observation data;
and combining the processed multiple 5-minute satellite observation data into complete one-orbit data.
In some optional embodiments, the data is subjected to reflectivity calibration by using a calibration method of a national satellite meteorological center and determining specific coefficients.
In some optional embodiments, the cloud detection adopts a threshold determination algorithm for a specific channel reflectivity variation coefficient, where the variation coefficient is equal to a standard deviation/an average value thereof, and if the variation coefficient of some specific channel is greater than a fixed threshold, the specific channel is considered as a cloud; mature cloud detection products may also be employed.
Further, the selecting and preprocessing the environment data of the ocean surface scene area in step S3 includes:
the environmental data mainly comprises aerosol optical thickness and wind speed and direction;
according to the longitude and latitude of the satellite observation data, searching environment data corresponding to a longitude and latitude grid;
aerosol optical thickness was obtained from MODIS grade 3 atmospheric 8 day global association product MYD08_ E3;
wind speed and wind direction use 10m wind field data in global atmosphere reanalysis data of a European middle weather forecast center (ECMWF), and a group of data which is closest to satellite observation time and has the highest spatial resolution is selected;
and matching the geographic positions of the environmental data and the satellite observation data.
In some optional embodiments, the three-dimensional model of the ocean surface in step S4 is a probability density function distribution model of a three-dimensional wave slope determined only by the wind speed and the wind direction of the ocean surface, which is established by Cox & Munk et al.
In some alternative embodiments, the polarized radiation state of the ocean surface in step S5 includes reflectivity, polarized reflectivity, and degree of polarization for a particular observation geometry.
In some optional embodiments, the radiation transmission simulation tool in step S6 is a 6SV vector model, and the atmospheric radiation polarization state lookup table is a table of polarization degrees and polarization reflectivities of rayleigh scattering and aerosol scattering corresponding to the observation geometry (solar zenith angle, solar azimuth angle, satellite zenith angle, satellite azimuth angle) and the aerosol optical thickness.
In some optional embodiments, the polarization sensitivity variation law in step S8 is a lookup table of atmospheric top polarized radiation states established according to observation geometry and environmental conditions.
Compared with the prior art, the method has the following beneficial effects:
(1) the application provides an in-orbit polarization radiation characteristic inversion method for a non-polarization satellite sensor, which can invert and analyze the polarization radiation characteristic of the in-orbit non-polarization satellite sensor to obtain the polarization radiation state of an atmospheric cap.
(2) The polarization sensitivity of the instrument is analyzed along with the observation geometry and environmental conditions, the change rule of the polarization radiation of the instrument along with different conditions is obtained, and the method has guiding significance for the polarization correction and radiation calibration of the subsequent non-polarization satellite sensor.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments with reference to the attached drawings in which:
fig. 1 is a schematic flow chart of an in-orbit polarization radiation characteristic inversion method for a non-polarization satellite sensor according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of an inversion result of polarization radiation characteristics based on a MERSI 412nm channel according to an embodiment of the present invention;
in the figure: (a) the observed value, (b) the inverted value, and (c) the difference value.
FIG. 3 shows the polarization sensitivity variation law of MERSI provided by the embodiment of the present invention in different observation geometries (aerosol optical thickness is 0.15, wind speed is 15m/s, wind direction angle is 150 °);
in the figure: (a) (c) is the change in degree of polarization; (b) and (d) is a change in reflectance.
Fig. 4 shows a change rule of polarization sensitivity of the MERSI at different wind speeds and wind directions (a solar zenith angle is 30 °, a relative azimuth angle is 120 °, and an optical thickness of the aerosol is 0.15) provided by the embodiment of the present invention;
in the figure: (a) (c) is the change in degree of polarization; (b) and (d) is a change in reflectance.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
As shown in fig. 1, an in-orbit polarization radiation characteristic inversion method for a non-polarization satellite sensor includes the following steps:
and S1, selecting the ocean surface scene remote sensing image obtained by the non-polarized satellite sensor after orbit as a ground object observation target.
In the embodiment of the invention, the ocean surface scene remote sensing image is selected as the ocean surface with large area through orbit prediction, and the Level1 data of the solar reflection wave band is obtained. Because the pacific ocean is wider, the embodiment of the invention selects Level1 data of the MERSI sensor in the solar reflection band of the pacific ocean surface.
S2, preprocessing the satellite observation data of the ocean surface scene area, which specifically comprises the following steps:
performing reflectivity calibration on satellite observation data of the selected ocean surface scene area;
carrying out cloud detection processing on the calibrated satellite observation data;
and combining the processed multiple 5-minute satellite observation data into complete one-orbit data.
In the embodiment of the invention, the data is subjected to reflectivity calibration by adopting a calibration method of a national satellite meteorological center and determining a specific coefficient. The cloud detection adopts a threshold judgment algorithm of a specific channel reflectivity variation coefficient, the variation coefficient is equal to a standard deviation/an average value thereof, and if the reflectivity of a 650nm channel is more than 0.15 and the variation coefficient at 1380nm is more than a fixed threshold value of 0.01, the cloud is judged to exist.
S3, selecting and preprocessing the environmental data of the ocean surface scene area, specifically including:
the environmental data mainly comprises aerosol optical thickness and wind speed and direction;
according to the longitude and latitude of the satellite observation data, searching environment data corresponding to a longitude and latitude grid;
aerosol optical thickness was obtained from MODIS grade 3 atmospheric 8 day global association product MYD08_ E3;
wind speed and wind direction use 10m wind field data in global atmosphere reanalysis data of a European middle weather forecast center (ECMWF), and a group of data which is closest to satellite observation time and has the highest spatial resolution is selected;
and matching the geographic positions of the environmental data and the satellite observation data.
S4, constructing an ocean surface three-dimensional model by utilizing the ocean surface environment data, wherein the ocean surface three-dimensional model is a probability density function distribution model of a three-dimensional wave slope which is only determined by the wind speed and the wind direction of the ocean surface and is established by Cox & Munk and the like.
In the embodiment of the invention, in the probability density function distribution model of the three-dimensional wave slope determined by the wind speed and the wind direction of the ocean surface, the inclination of the wave slope surface along the crosswind direction and the upwind direction is ZxAnd ZyAre respectively represented as
Wherein the content of the first and second substances,
respectively a solar zenith angle, a satellite zenith angle, a solar azimuth angle and a satellite azimuth angle; χ is azimuth from sun phisAzimuth angle phi to wind directionwAngle of rotation of (x ═ phi-s-φw。
The probability density function P of a rough sea surface slope may be expressed as
For clean surfaces, ξ and η in the formula are expressed as
Wherein sigmax、σyAre each Zx,ZyThe root mean square value of; skewness coefficient C21And C03And peak intensity coefficient C40，C22And C04From Cox&Munk is defined as follows
By using the probability density function P (Zx, Zy) of the sea surface slope in the ocean surface three-dimensional model, the reflectivity rho under a specific observation geometric condition can be obtainedgAnd polarized reflectance
Wherein, thetanIs the direction of incidence (theta)s,φsIs reflected to the reflecting surface (theta)v,φv) The slope of the wave surface of (a); n is the refractive index of seawater; r (n, theta)s,φs,θv,φv) And Rpol(n,θs,φs,θv,φv) Respectively fresnel reflection coefficient and polarization reflection coefficient.
And S5, simulating the polarized radiation state of the real ocean surface by combining Fresnel reflection law, wherein the polarized radiation state comprises the reflectivity, the polarized reflectivity and the polarization degree under specific observation geometric conditions.
Incident angle theta in fresnel reflection theoryiAnd angle of reflection thetatRepresented by the formula
Wherein n is1And n2The refractive indices of air and seawater, respectively.
According to fresnel's law, the incident light electric vector is decomposed into two components, one parallel to the incident plane and the other perpendicular to the incident plane. If note r//And r⊥Respectively, the reflectivity of the two components, the fresnel equation can be written as
Since the direct solar light is natural light (unpolarized light) and the amplitude components in each direction are equal, the total reflectance ρ and the polarized reflectance ρ are equalpolIs composed of
The degree of polarization can be expressed as
And S6, analyzing the influence of atmospheric scattering on the radiation polarization state based on the radiation transmission simulation tool, and establishing an atmospheric radiation polarization state lookup table.
In the embodiment of the invention, the radiation transmission simulation tool is a 6SV vector model, and the atmospheric radiation polarization state lookup table is the polarization degree and the polarization reflectivity of Rayleigh scattering and aerosol scattering under the corresponding observation geometry (solar zenith angle, solar azimuth angle, satellite zenith angle and satellite azimuth angle) and the aerosol optical thickness.
The parameters needing point-by-point input for establishing the lookup table by using the 6SV model mainly comprise observation geometry (solar zenith angle, solar azimuth angle, satellite zenith angle and satellite azimuth angle) and aerosol optical thickness (AOD), and the main parameter intervals of the constructed lookup table are shown in table 1:
table 1 atmospheric lookup table main input parameters
Table 1Main parameters in lookup table
Other parameters are set as fixed values, including atmospheric model, aerosol type, target altitude, spectral information, etc. The output parameters of the lookup table constructed by the model mainly comprise the polarization degree, the polarization reflectivity, the Stokes vector and the like of Rayleigh scattering and aerosol scattering.
And S7, coupling the radiation state of the sea surface with the radiation transmission state of the atmosphere to obtain the atmospheric top polarization radiation state of the ocean surface scene.
After calculating the polarized radiation states of the sea table and the atmosphere according to S5 and S6, respectively, the polarized radiation states of the atmosphere cap are obtained by coupling the polarized radiation states together. Obtaining a calculation formula of the atmospheric top reflectivity and the polarization reflectivity:
in the formula, ρgAnd
the sea surface reflectivity and the polarization reflectivity are 2.3 sections; rhom、
And ρa、
The reflectivity and the polarized reflectivity of the rayleigh scattering and the aerosol scattering, respectively, are found by the 6SV lookup table. RhowCorresponding to the radiation leaving the water, pfCorresponding to the foam reflectance; m is the air quality factor and δ is the total optical thickness of the atmosphere. Since foam reflectivity is typically small (less than 0.001), the amount of water-leaving radiation is related to chlorophyll concentration in sea water, etc., the default choice of sea in this document is a relatively "clean" deep sea, and therefore water-leaving radiation ρ is ignoredwAnd foam reflectance ρfThe reflectivity and polarization degree of the atmospheric dome can be reduced to the following formula for calculation
By combining the steps, the polarized radiation state of a specific sea surface target reaching the atmospheric cap under specific environmental conditions on a specific date can be obtained, and the polarized radiation state is represented by the following steps in 2018, 4, 3, 23: and (3) carrying out simulation under the condition of observing the Pacific at a ratio of 00-23: 30, carrying out polarization radiation characteristic inversion on the non-polarization satellite sensor MERSI, wherein the results are shown in figure 2, and the simulation values and the observation values of the reflectivity and the polarization degree MERSI are relatively consistent in overall distribution. The absolute value of the reflectivity error of simulation and observation is basically less than 5%, and the correctness and the effectiveness of the method are verified.
And S8, analyzing the polarization radiation characteristics of the sensor in a specific wave band for different observation geometries and different environments to obtain the change rule of the polarization sensitivity, namely, establishing a look-up table of the atmospheric top polarization radiation state according to the observation geometries and the environment conditions to realize the inversion of the on-orbit polarization radiation characteristics of the non-polarization sensor.
In the embodiment of the invention, the sensor is a non-biased load MERSI, the specific wave band is 412nm, the observation geometry is a solar zenith angle, a satellite zenith angle and a relative azimuth angle, and the different environments are wind speed and wind direction.
Fig. 3 shows polarization sensitivity of MERSI to observation geometry, showing simulated polarization and reflectivity as a function of satellite zenith angle (VZA) at different relative azimuth angles (PHI) and Solar Zenith Angles (SZA). It can be seen that the polarization radiation state of the atmospheric dome is much more dependent on the solar zenith angle than the relative azimuth angle. The relative azimuth only weakly affects the absolute values of the reflectivity and the polarization degree, and the change rule of the relative azimuth cannot be changed along with the change of the satellite zenith angle. The solar zenith angle can completely change the polarization degree, and the polarization degree changes along with the satellite zenith angle; the reflectivity is affected differently by different solar zenith angles, and changes in reflectivity are also significant when the satellite zenith angle is large (greater than 40 °).
FIG. 4 is a plot of the degree of polarization and reflectivity of the atmospheric dome as a function of satellite zenith angle for different wind speeds and wind direction angles. It can be seen that the wind speed and the wind direction have almost no influence on the polarization degree and have weak influence on the reflectivity.
The embodiment has the following beneficial effects:
(1) the application provides an in-orbit polarization radiation characteristic inversion method for a non-polarization satellite sensor, which can invert and analyze the polarization radiation characteristic of the in-orbit non-polarization satellite sensor to obtain the polarization radiation state of an atmospheric cap.
(2) The polarization sensitivity of the instrument is analyzed along with the observation geometry and environmental conditions, the change rule of the polarization radiation of the instrument along with different conditions is obtained, and the method has guiding significance for the polarization correction and radiation calibration of the subsequent non-polarization satellite sensor.
The foregoing describes a specific embodiment of the present invention. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes and modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention.
Claims (9)
1. An on-orbit polarization radiation characteristic inversion method for a non-polarization satellite sensor is characterized by comprising the following steps of:
step 1, selecting an ocean surface scene remote sensing image obtained after an on-orbit non-polarization satellite sensor as a ground object observation target;
step 2, preprocessing satellite observation data of the ocean surface scene area;
step 3, selecting and preprocessing the environmental data of the ocean surface scene area;
step 4, constructing an ocean surface three-dimensional model by utilizing ocean surface environment data;
step 5, simulating the polarization radiation state of the real ocean surface by combining the Fresnel reflection law;
step 6, analyzing the influence of atmospheric scattering on the radiation polarization state based on a radiation transmission simulation tool, and establishing an atmospheric radiation polarization state lookup table;
step 7, coupling the radiation state of the sea surface with the radiation transmission state of the atmosphere to obtain the atmospheric top polarization radiation state of the ocean surface scene;
and 8, analyzing the polarization radiation characteristics of the sensor in a specific wave band for different observation geometries and different environments to obtain the change rule of the polarization sensitivity of the sensor, and realizing the inversion of the on-orbit polarization radiation characteristics of the non-polarization sensor.
2. The method for inverting the on-orbit polarized radiation characteristic of the non-polarized satellite sensor according to claim 1, wherein the ocean surface scene remote sensing image selected in the step 1 is an ocean surface with a large area selected through orbit prediction, and Level1 data of a solar reflection band of the ocean surface scene remote sensing image are obtained.
3. The method for inverting the in-orbit polarized radiation characteristic of the unpolarized satellite sensor according to claim 1, wherein the preprocessing of the satellite observation data of the ocean scene area in the step 2 includes:
performing reflectivity calibration on satellite observation data of the selected ocean surface scene area;
carrying out cloud detection processing on the calibrated satellite observation data;
and combining the processed multiple 5-minute satellite observation data into complete one-orbit data.
4. The method for inverting the in-orbit polarized radiation characteristic of the unpolarized satellite sensor according to claim 1, wherein the selecting and preprocessing the environmental data of the ocean surface scene area in step 3 comprises:
the environmental data mainly comprises aerosol optical thickness and wind speed and direction;
according to the longitude and latitude of the satellite observation data, searching environment data corresponding to a longitude and latitude grid;
and matching the geographic positions of the environmental data and the satellite observation data.
5. The method for inverting the in-orbit polarization radiation characteristic of the unpolarized satellite sensor according to claim 1, wherein the three-dimensional model of the ocean surface in the step 4 is a probability density function distribution model of a three-dimensional wave slope determined only by the wind speed and the wind direction of the ocean surface.
6. The method for inverting in-orbit polarized radiation characteristics of a non-polarized satellite sensor according to claim 1, wherein the polarized radiation state of the ocean surface in the step 5 comprises reflectivity, polarized reflectivity and polarization degree under a specific observation geometry.
7. The method for inverting the in-orbit polarized radiation characteristics of the unpolarized satellite sensor according to claim 1, wherein the radiation transmission simulation tool in the step 6 is a 6SV vector model, and the atmospheric radiation polarization state lookup table is the degree of polarization and the polarized reflectance of Rayleigh scattering and aerosol scattering corresponding to the observation geometry (solar zenith angle, solar azimuth angle, satellite zenith angle, satellite azimuth angle) and the aerosol optical thickness.
8. The method for inverting in-orbit polarization radiation characteristics of the unpolarized satellite sensor according to claim 1, wherein the coupling manner of the sea surface radiation state and the atmospheric radiation transmission state in the step 7 is addition.
9. The method for inverting the in-orbit polarized radiation characteristic of the unpolarized satellite sensor according to claim 1, wherein the polarization sensitivity variation law in the step 8 is a lookup table of atmospheric top polarized radiation states established according to observation geometry and environmental conditions.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116148189A (en) * | 2023-04-14 | 2023-05-23 | 自然资源部第二海洋研究所 | Aerosol layer height acquisition method based on passive polarized satellite data |
| CN117313564A (en) * | 2023-11-30 | 2023-12-29 | 自然资源部第二海洋研究所 | Method, device and storage medium for inverting ocean-atmosphere optical parameters |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116148189A (en) * | 2023-04-14 | 2023-05-23 | 自然资源部第二海洋研究所 | Aerosol layer height acquisition method based on passive polarized satellite data |
| CN116148189B (en) * | 2023-04-14 | 2023-07-21 | 自然资源部第二海洋研究所 | Aerosol layer height acquisition method based on passive polarized satellite data |
| CN117313564A (en) * | 2023-11-30 | 2023-12-29 | 自然资源部第二海洋研究所 | Method, device and storage medium for inverting ocean-atmosphere optical parameters |
| CN117313564B (en) * | 2023-11-30 | 2024-04-12 | 自然资源部第二海洋研究所 | Method, device and storage medium for inverting ocean-atmosphere optical parameters |
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