CN117574044B - Inversion method and system for physical temperature distribution of secondary shielding moon permanent shadow area - Google Patents
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Abstract
The invention provides a physical temperature distribution inversion method and system for a secondary shielding moon permanent shadow area, and belongs to the technical field of remote sensing. The technical key points are as follows: the method comprises the following steps: step one: constructing a heat conduction model of a secondary shielding moon permanent shadow area to obtain infrared bright temperature data; step two, constructing a microwave radiation model, and calculating to obtain microwave bright temperature according to the infrared bright temperature data; and thirdly, performing fusion inversion on the obtained infrared brightness temperature and microwave brightness temperature to obtain an optimal temperature distribution solution. Aiming at the problems of model and inversion difficulty in the detection of the physical temperature distribution of the secondary shielding moon permanent shadow area, the invention provides a method for inverting the more accurate physical temperature distribution of the secondary shielding moon permanent shadow area under remote sensing data such as the back-flying microwave radiation bright temperature, the LRO infrared radiation bright temperature, the laser height count elevation and the like by introducing a radiation transmission model supporting the secondary shielding effect and bulk scattering and combining with the combination and optimization of an inversion method.
Description
Technical Field
The invention relates to the technical field of satellite remote sensing, in particular to a method and a system for inverting physical temperature distribution of a secondary shielding moon permanent shadow area.
Background
The lunar water ice resources mainly exist in lunar soil of a lunar permanent shadow area with extremely low temperature, the existence form is complex, the resource collection work is carried out in a polar region in the future, firstly, the temperature distribution of the surface and the inside of the lunar permanent shadow area is required to be researched to obtain 'water trap' distribution, and then the total amount and the distribution of the water ice resources are evaluated in combination with other remote sensing data. The adoption of the heat flow probe measurement is the most direct mode for obtaining the temperature of the high-precision lunar surface, but the temperature of a lunar region, particularly a permanent shadow region, is extremely low, and direct measurement is difficult to realize. Therefore, remote sensing measurement is the main mode for detecting the physical temperature of a permanently hatched area of the moon at present, an infrared radiometer can only acquire the temperature distribution of the surface, and the remote sensing detection of the deeper temperature requires a microwave radiometer, and the number of channels of the microwave radiometer is limited, particularly the regional temperature is greatly influenced by the terrain, so that strong seasonal change is shown, and more reliable physical temperature of the lunar surface can be acquired by utilizing detection data of a plurality of detection tasks. Therefore, the study of the physical temperature distribution of the secondary shielded moon permanent shadow area necessarily requires the combination of microwave and infrared bright temperature data and the like.
In a secondary shielding moon permanent shadow area, as the temperature of the moon surface is few in-place measuring points, the common inversion method mainly comprises boundary searching, combination inversion, statistical inversion and the like. The existing temperature distribution inversion method is mostly based on a microwave passive radiation model, and is not fully applied to increment priori information brought by other detectors such as infrared radiation measurement. Temperature inversion typically defines a temperature profile function, which reduces inversion difficulty and may limit inversion results.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention provides a inversion method and a system for physical temperature distribution of a secondary shielding moon permanent shadow area, and a method for inverting more accurate physical temperature distribution of the secondary shielding moon permanent shadow area under remote sensing data such as the back-flying to-back microwave radiation bright temperature, the LRO moon survey orbit device infrared radiation bright temperature, the laser height count word elevation and the like is explored by introducing a radiation transfer model supporting the secondary shielding effect and bulk scattering and combining with the combination and optimization of the inversion method.
According to a first aspect of the present invention, the present invention provides a method for inverting the physical temperature distribution of a permanently shaded moon region, comprising:
step one, constructing a heat conduction model of a secondary shielding moon permanent shadow area to acquire infrared brightness temperature data;
step two, constructing a microwave radiation model, and calculating to obtain microwave bright temperature according to the infrared bright temperature data;
and thirdly, performing fusion inversion on the obtained infrared brightness temperature and microwave brightness temperature to obtain an optimal temperature distribution solution.
On the basis of the technical scheme, the invention can also make the following improvements.
Optionally, the constructing the heat conduction model of the secondary shielding moon permanent shadow area specifically comprises:
firstly, obtaining lunar surface irradiance according to a VSOP87 planetary motion theory and an ELP2000-82 lunar orbit semi-analytical theory;
then, according to the situation of terrain shielding, establishing a real-time effective solar irradiance model of a moon permanent shadow area and a surrounding area thereof under secondary shielding;
and finally, calculating the adjacent area radiation received by the surface of the permanent shadow area according to the effective solar irradiance model.
Alternatively, the infrared bright temperature can be solved by the following equation:
in the method, in the process of the invention,infrared bright temperature->Is the surface temperature, ++>Is the infrared radiation of the adjacent surface element, epsilon is the surface emissivity,is the boltzmann constant.
Optionally, the constructing the microwave radiation model includes:
according to the observation position and the view field, calculating the radiation brightness temperature of the lunar dust layer, the lunar soil layer and the lunar rock layer based on the antenna caliber; meanwhile, the scattering coefficient is calculated according to the particle size and the compactness of water ice or stone substances to evaluate the bulk scattering influence, and the method is applied to calculation of reflection and transmission fields of each layer to construct a flexible reconstruction microwave radiation model.
Optionally, the calculating the microwave brightness temperature according to the infrared brightness temperature data includes:
in a microwave radiation model, lunar soil is layered, and the total received microwave brightness temperature is the sum of the radiation brightness temperatures of all layers and is expressed as:
wherein,the attenuation factor is used for representing the influence of volume scattering, roughness and the like on the brightness temperature; besides solving by adopting a traditional incoherent method, coarse surface scattering and bulk scattering are introduced, wherein the coarse surface scattering comprises Mie scattering and Rayleigh scattering, and the attenuation factor is solved; /> i Is the total lighting temperature of microwave, < >>Is the radiant brightness temperature of each layer->Upward microwave bright temperature->Is the downward microwave bright temperature.
Optionally, the microwave and infrared fusion inversion is divided into research of high-low frequency band multichannel combination inversion and research of a Markov chain Monte Carlo method based on differential evolution, and the method is used for solving the Bayesian problem of temperature posterior distribution.
Optionally, the microwave and infrared fusion inversion specifically includes the following steps:
firstly, utilizing measured data of a multi-band microwave radiometer and an infrared radiometer, removing values of brightness temperature less than 30K and greater than 400K in the measured data through data anomaly detection, fitting and interpolating, and then performing time normalization to convert time data into a unified format, so as to obtain preliminary prior parameter distribution of microwave brightness temperature and infrared brightness temperature;
and then performing high-frequency multi-channel brightness Wen Fanyan, namely inputting the temperature distribution solved by the heat conduction model into the microwave radiation model as an initial value, and solving a Bayesian problem by utilizing the actually measured high-frequency microwave brightness temperature data to obtain the optimal solution of the temperature posterior distribution in the shallow layer, namely the high fluctuation area.
Optionally, the microwave and infrared fusion inversion further includes:
and then carrying out low-frequency band multichannel brightness Wen Fanyan, taking the obtained shallow temperature distribution as a priori value, and obtaining an optimal temperature distribution solution by using a Markov chain Monte Carlo method based on differential evolution.
Alternatively, the solution of the optimal value adopts a Markov chain Monte Carlo method based on differential evolution, and the solution objective function can be expressed as follows:
where Nobs represents the number of observations, SSR represents the sum of squares of residuals, and L represents the posterior distribution.
According to a second aspect of the present invention, there is provided a physical temperature distribution inversion system for a secondarily-shaded moon permanent shading region, comprising:
the infrared bright temperature acquisition module is used for constructing a heat conduction model of a secondary shielding moon permanent shadow area to acquire infrared bright temperature data;
the microwave bright temperature acquisition module is used for constructing a microwave radiation model and calculating to obtain the microwave bright temperature according to the infrared bright temperature data;
and the fusion inversion module is used for carrying out fusion inversion on the obtained infrared brightness temperature and the obtained microwave brightness temperature to obtain an optimal temperature distribution solution.
The invention has the technical effects and advantages that:
according to the inversion method and system for physical temperature distribution of the secondary shielding moon permanent shadow area, the detection method of microwave and infrared joint remote sensing is adopted, the accuracy of a radiation model is improved around the accuracy and completeness of the model, and the accuracy of the inversion method is improved by breaking through the utilization rate of priori information. The limitation that the existing temperature distribution inversion method is difficult to be suitable for the combination detection of the microwave and the infrared is broken, the fusion of the multi-source information of the microwave and the infrared detection can be increased to obtain more inversion information, and the inversion result is converged to the global optimal point. And the inversion accuracy of the physical temperature distribution of the secondary shielded moon permanent shadow area is improved by adopting multi-source remote sensing data acquired by a plurality of moon detection plans such as goddess Chang, an infrared radiometer and the like and combining the radiation model and the inversion method, key factors influencing inversion results can be analyzed, and the practical requirements are met.
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FIG. 1 is a schematic flow chart of a method for inverting physical temperature distribution of a permanently shaded area of a secondarily shaded moon according to an embodiment of the present invention;
FIG. 2 is a flow chart of a microwave and infrared fusion inversion method provided by an embodiment of the invention;
FIG. 3 is a flow chart of simulation verification of a microwave and infrared fusion inversion method provided by an embodiment of the invention;
fig. 4 is a flowchart for calculating a physical temperature profile of a permanently shaded area of a secondarily shaded moon according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It can be understood that, based on the defects in the background technology, the embodiment of the invention provides a inversion method for physical temperature distribution of a secondary shielding moon permanent shadow area, as shown in a flow in fig. 1, which specifically comprises the following steps:
step 1: constructing a heat conduction model of a secondary shielding moon permanent shadow area to obtain infrared bright temperature data;
aiming at the heat conduction model of the moon permanent shadow area under secondary shielding, based on a one-dimensional heat conduction equation, surface roughness, multiple scattering under large-scale shielding and internal heat conduction are introduced, the application range of the heat conduction model is expanded, and then the infrared light temperature is obtained.
Further, constructing a secondary shielded moon permanent shadow thermal conduction model includes the steps of:
firstly, obtaining lunar surface irradiance according to a VSOP87 planetary motion theory and an ELP2000-82 lunar orbit semi-analytical theory;
then, according to the situation of terrain shielding, establishing a real-time effective solar irradiance model of a moon permanent shadow area and a surrounding area thereof under secondary shielding;
using this effective solar irradiance model, the near-area radiation received by the permanently shaded area surface is calculated.
The calculation of the adjacent radiation is to divide the adjacent area into grid-shaped rough surface elements by using elevation data of a laser altimeter, and then calculate the adjacent radiation quantity in a final shadow area by using ray tracing.
Since the adjacent radiation is the main thermal contribution of the permanently hatched surface, the boundary conditions of the surface can be established accordingly:
in the method, in the process of the invention,for surface thermal conductivity, ε for surface emissivity, +.>Is Boltzmann constant, & gt>For the radiation of the area in the vicinity,is the moon internal heat flow.
In addition to the lunar interior heat flow, a bottom boundary condition may be established considering that there may be lateral heat conduction inside the lunar soil, i.e., heat flow inside the illuminated area to the shadow area:
wherein,for the bottom thermal conductivity->For lateral heat conduction->Is the moon internal heat flow.
After the boundary condition is established, a finite difference method is adopted to solve. In order to evaluate the possible presence of anisotropic media, the effect of shallow tens of cm of water ice or stones is emphasized in the thermal conductivity parameters, and the effect of deeper media properties on the surface temperature is limited.
By the above improvement measures, an initial temperature profile distribution can be obtained, which will be used as input to the thermal conduction model of the permanently shaded moon under secondary shading for simulating the calculation of the microwave bright temperature in step 2.
Further, to evaluate the infrared radiation condition of the secondary shielded moon permanent shadow, the infrared bright temperature can be solved by the following equation:
in the method, in the process of the invention,infrared bright temperature->Is the surface temperature，/>Is the infrared radiation of the adjacent surface element, epsilon is the surface emissivity,is the boltzmann constant.
Step two, constructing a microwave radiation model, and calculating to obtain microwave bright temperature according to the infrared bright temperature data;
specifically, for a microwave radiation model, according to the observation position and the view field, the radiation brightness temperature of the lunar dust layer, the lunar soil layer and the lunar rock layer is calculated based on the antenna caliber. Meanwhile, substances such as water ice or stones possibly exist in a moon permanent shadow area, bulk scattering can be generated in a microwave frequency band, the scattering coefficient is calculated according to the particle size and the compactness to evaluate the bulk scattering influence, and the method is applied to calculation of reflection and transmission fields of all layers to construct a flexible reconstruction microwave radiation model.
In particular, solutions for microwave radiation processes generally have incoherent and coherent methods. Considering the bright temperature oscillation caused by the calculation of the coherent method, in the calculation of the microwave radiation model, a noncoherent method is adopted. Since the object of investigation is to secondarily shade the permanently shaded area of the moon, the problem of microwave radiation in the presence of water ice or stones needs to be considered. Based on the original dielectric constant, water ice is introduced, and a Lichtenecker formula and a MaxwellGarnett formula are adopted to calculate the mixed dielectric constant. The water ice mixed in the lunar soil may be dispersed in the lunar soil in a granular form, and thus may generate bulk scattering. Similarly, there is a phenomenon of bulk scattering in the presence of stones. Therefore, in the construction of the radiation model, in addition to the conventional incoherent method for solving, coarse surface scattering and volume scattering (including Mie scattering and Rayleigh scattering) are introduced to solve the attenuation factors in this embodiment.
It is worth to say that the key of the microwave radiation model is to accurately solve the attenuation factor and reasonably reflect the radiation characteristics of the real target substance. For volume scattering, mie scattering coefficients or Rayleigh scattering coefficients are to be added to the radiation transfer equation according to particle size; for the surface roughness, the reflectivity is solved according to the statistical characteristics of the rough surface by adopting an integral equation method, attenuation factors are obtained according to the obtained bulk scattering coefficient, reflectivity and the like, and finally the total bright temperature expression is obtained.
Finally, in a microwave radiation model, lunar soil is layered, and the total brightness temperature of microwaves received by a microwave radiometer is the sum of the brightness temperatures of all layers, and is expressed as:
wherein,the attenuation factor is used for representing the influence of volume scattering, roughness and the like on the brightness temperature; /> i Is the total lighting temperature of microwave, < >>Is the radiant brightness temperature of each layer->Upward microwave bright temperature->Is the downward microwave bright temperature.
And thirdly, performing fusion inversion on the obtained infrared brightness temperature and microwave brightness temperature to obtain an optimal temperature distribution solution.
According to the characteristics of shallow high fluctuation and deep low fluctuation of the lunar surface temperature, a microwave and infrared fusion inversion secondary shielding permanent shadow region temperature distribution method is researched, and the prior information and inversion iterative optimization method are started.
FIG. 2 shows a flow chart of a microwave and infrared fusion inversion method. On one hand, the microwave and infrared fusion inversion method is studied, and because the detection depths of different frequency bands are different, the dependence on a temperature profile function can be reduced by utilizing different layering contributions corresponding to the different frequency bands, the shallow layer is gradually iterated to the deep layer during solving, the influence of shallow layer fluctuation on deep layer temperature inversion is eliminated, the temperature distribution of a high fluctuation area and a low fluctuation area is respectively obtained, and the inversion precision is improved; on the other hand, a Markov chain Monte Carlo Method (MCMC) based on differential evolution is researched to solve the Bayesian problem of temperature posterior distribution, and the method has a good effect on solving the complex and high-dimensional posterior distribution problem and can improve the stability of inversion.
Specifically, the microwave and infrared fusion inversion specifically comprises the following steps:
firstly, utilizing measured data of a multi-band microwave radiometer and an infrared radiometer, removing values of brightness temperature smaller than 30K and larger than 400K in the measured data through data anomaly detection, fitting and interpolating, and then performing time normalization to convert time data into a unified format, namely daytime and midnight, 6 points to 18 points in the daytime and 6 points to the next day in the midnight, so as to obtain the prior parameter distribution of the preliminary microwave brightness temperature and the infrared brightness temperature. And then performing high-frequency multi-channel brightness Wen Fanyan, namely inputting the temperature distribution solved by the heat conduction model into the microwave radiation model as an initial value, and solving a Bayesian problem by utilizing the actually measured high-frequency microwave brightness temperature data to obtain the optimal solution of the temperature posterior distribution in the shallow layer, namely the high fluctuation area.
And then performing low-frequency multi-channel brightness Wen Fanyan, namely using a Bayesian network as described above, taking the obtained shallow temperature distribution as a priori value, and obtaining an optimal longitudinal temperature distribution solution by using a Markov chain Monte Carlo Method (MCMC) based on differential evolution.
The solution of the optimal value adopts a Markov chain Monte Carlo method based on differential evolution, and the solving objective function can be expressed as follows:
where Nobs represents the number of observations, SSR represents the sum of squares of residuals, and L represents the posterior distribution.
In the embodiment, the dependence on the temperature profile function during inversion can be reduced theoretically by increasing the number of channels of the multichannel microwave radiometer, and the inversion accuracy is further improved by improving the inversion optimizing solving method.
To verify the performance of the proposed method, a simulation verification experiment as in fig. 3 was designed. In simulation verification, a heat conduction and radiation model module and a microwave and infrared fusion inversion module are respectively verified. When the model is verified, the model proposed in the project is compared with the simulation brightness Wen Chayi of the traditional incoherent multilayer microwave radiation model and the traditional one-dimensional heat conduction model, and is compared with the actually measured bright temperature data and the LRO bright temperature data, so that the accuracy of simulating the bright temperature is further verified. When the microwave and infrared fusion inversion method is verified, the inversion errors of the method provided by the project and other solving algorithms such as a least square method are compared, and the inversion performance of the method provided under the assumed temperature distribution is evaluated. After comparing and verifying each module, verifying the microwave and infrared fusion inversion simulation platform, comparing with inversion of single passive radiation measurement, and verifying the advantages of the inversion method of the project through comparing inversion errors of longitudinal physical temperature distribution.
The main scientific data to be adopted in this embodiment are: four channels of goddess Chang E No. two microwave bright temperature data, iron titanium content data, LRO multichannel infrared bright temperature data and digital elevation data of a laser altimeter. For the secondary shielding moon permanent shadow area, the calculation flow of the physical temperature profile of the lunar surface is shown in fig. 4, and the construction of the dielectric constant model is derived from the iron-titanium content data. The laser altimeter provides digital elevation data for establishing a shielding model, and the LRO infrared bright temperature provides surface temperature priori information during inversion. Substituting each measured data source into a corresponding parameter model, calculating the input parameters of the inversion model, and obtaining the temperature profile of the lunar surface through repeated iterative calculation. Based on the measured temperature profile, the spatial location of the "water trap" can be obtained.
Additionally, the embodiment of the invention also provides a physical temperature distribution inversion system of a secondary shielding moon permanent shadow area, which comprises the following steps:
the infrared bright temperature acquisition module is used for constructing a heat conduction model of a secondary shielding moon permanent shadow area to acquire infrared bright temperature data;
the microwave bright temperature acquisition module is used for constructing a microwave radiation model and calculating to obtain the microwave bright temperature according to the infrared bright temperature data;
the fusion inversion module is used for carrying out fusion inversion on the obtained infrared brightness temperature and the obtained microwave brightness temperature to obtain an optimal temperature distribution solution
It can be understood that the inversion system for physical temperature distribution of the permanently shaded moon provided by the present invention corresponds to the inversion method for physical temperature distribution of the permanently shaded moon provided by the foregoing embodiments, and the relevant technical features of the inversion system for physical temperature distribution of the permanently shaded moon can refer to the relevant technical features of the inversion method for physical temperature distribution of the permanently shaded moon, which are not described herein.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (7)
1. The inversion method of the physical temperature distribution of the secondary shielding moon permanent shadow area is characterized by comprising the following steps of:
step one, constructing a heat conduction model of a secondary shielding moon permanent shadow area to acquire infrared brightness temperature data;
step two, constructing a microwave radiation model, and calculating to obtain microwave bright temperature according to the infrared bright temperature data; comprising the following steps:
layering lunar soil, wherein the total received microwave brightness temperature is the sum of the radiation brightness temperatures of all layers, and is expressed as:
wherein,the attenuation factor is used for representing the influence of volume scattering and roughness on the brightness temperature; besides solving by adopting a traditional incoherent method, coarse surface scattering and bulk scattering are introduced, wherein the coarse surface scattering comprises Mie scattering and Rayleigh scattering, and the attenuation factor is solved; />Is the total lighting temperature of microwave, < >>Is the radiant brightness temperature of each layer->Upward microwave bright temperature->The downward microwave brightness temperature;
thirdly, fusion inversion is carried out on the obtained infrared brightness temperature and the obtained microwave brightness temperature, and an optimal temperature distribution solution is obtained; comprising the following steps: removing values of brightness temperature less than 30K and more than 400K in measured data through data anomaly detection by utilizing measured data of a multi-band microwave radiometer and an infrared radiometer, fitting and interpolating, and then carrying out time normalization to convert time data into a unified format so as to obtain preliminary prior parameter distribution of microwave brightness temperature and infrared brightness temperature;
then, high-frequency multi-channel brightness Wen Fanyan is carried out, namely, temperature distribution solved by a heat conduction model is used as an initial value to be input into a microwave radiation model, and the actually measured high-frequency microwave brightness temperature data is utilized to carry out Bayesian problem solving to obtain the optimal solution of temperature posterior distribution in a shallow layer, namely, a high fluctuation area;
and then carrying out low-frequency band multichannel brightness Wen Fanyan, taking the obtained shallow temperature distribution as a priori value, and obtaining an optimal temperature distribution solution by using a Markov chain Monte Carlo method based on differential evolution.
2. The inversion method of physical temperature distribution of a secondary shielding moon permanent shadow area according to claim 1, wherein the constructing a heat conduction model of the secondary shielding moon permanent shadow area is specifically:
firstly, obtaining lunar surface irradiance according to a VSOP87 planetary motion theory and an ELP2000-82 lunar orbit semi-analytical theory;
then, according to the situation of terrain shielding, establishing a real-time effective solar irradiance model of a moon permanent shadow area and a surrounding area thereof under secondary shielding;
and finally, calculating the adjacent area radiation received by the surface of the permanent shadow area according to the effective solar irradiance model.
3. The inversion method of physical temperature distribution of a permanently shaded moon region according to claim 2, wherein the infrared bright temperature is solved by the following equation:
in the method, in the process of the invention,infrared bright temperature->Is the surface temperature, ++>Is the infrared radiation of the adjacent bin, ε is the surface emissivity,>is the boltzmann constant.
4. The inversion method of physical temperature distribution of a secondary shielded moon permanent shadow area according to claim 1, wherein the constructing a microwave radiation model comprises:
according to the observation position and the view field, calculating the radiation brightness temperature of the lunar dust layer, the lunar soil layer and the lunar rock layer based on the antenna caliber; meanwhile, the scattering coefficient is calculated according to the particle size and the compactness of water ice or stone substances to evaluate the bulk scattering influence, and the method is applied to calculation of reflection and transmission fields of each layer to construct a flexible reconstruction microwave radiation model.
5. The inversion method of physical temperature distribution of a secondary shielding moon permanent shadow area according to claim 1, wherein the microwave and infrared fusion inversion is divided into research of high-low frequency band multi-channel combination inversion and research of a Markov chain Monte Carlo method based on differential evolution, and the method is used for solving the Bayesian problem of temperature posterior distribution.
6. The inversion method of physical temperature distribution of a secondary shielding moon permanent shadow area according to claim 1, wherein the solution of the optimal value adopts a markov chain monte carlo method based on differential evolution, and the solving objective function can be expressed as follows:
where Nobs represents the number of observations, SSR represents the sum of squares of residuals, and L represents the posterior distribution.
7. The utility model provides a physical temperature distribution inversion system of permanently shaded area of secondary shielding moon which characterized in that includes:
the infrared bright temperature acquisition module is used for constructing a heat conduction model of a secondary shielding moon permanent shadow area to acquire infrared bright temperature data;
the microwave bright temperature acquisition module is used for constructing a microwave radiation model and calculating to obtain the microwave bright temperature according to the infrared bright temperature data; comprising the following steps: layering lunar soil, wherein the total received microwave brightness temperature is the sum of the radiation brightness temperatures of all layers, and is expressed as:
wherein,the attenuation factor is used for representing the influence of volume scattering and roughness on the brightness temperature; besides solving by adopting a traditional incoherent method, coarse surface scattering and bulk scattering are introduced, wherein the coarse surface scattering comprises Mie scattering and Rayleigh scattering, and the attenuation factor is solved; />Is the total lighting temperature of microwave, < >>Is the radiant brightness temperature of each layer->Upward microwave bright temperature->The downward microwave brightness temperature;
the fusion inversion module is used for carrying out fusion inversion on the obtained infrared brightness temperature and the obtained microwave brightness temperature to obtain an optimal temperature distribution solution; comprising the following steps: removing values of brightness temperature less than 30K and more than 400K in measured data through data anomaly detection by utilizing measured data of a multi-band microwave radiometer and an infrared radiometer, fitting and interpolating, and then carrying out time normalization to convert time data into a unified format so as to obtain preliminary prior parameter distribution of microwave brightness temperature and infrared brightness temperature; then, high-frequency multi-channel brightness Wen Fanyan is carried out, namely, temperature distribution solved by a heat conduction model is used as an initial value to be input into a microwave radiation model, and the actually measured high-frequency microwave brightness temperature data is utilized to carry out Bayesian problem solving to obtain the optimal solution of temperature posterior distribution in a shallow layer, namely, a high fluctuation area;
and then carrying out low-frequency band multichannel brightness Wen Fanyan, taking the obtained shallow temperature distribution as a priori value, and obtaining an optimal temperature distribution solution by using a Markov chain Monte Carlo method based on differential evolution.
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