A method for estimating dielectric loss in the lunar shallow surface layer by combining radiation brightness temperature and stratigraphic information

Abstract

The present invention relates to a method for estimating dielectric loss in the lunar shallow surface layer by combining radiation brightness temperature and stratigraphic information. The method comprises the following steps: obtaining Chang'e-2 radiation brightness temperature data and determining the local time of observation; obtaining Chang'e-4 lunar radar data and preprocessing it; performing stratigraphic division based on the lunar radar data and extracting lunar regolith data; determining the lunar surface physical temperature; using the lunar regolith thickness at the lunar radar detection point and the detectable depth of the radiation brightness temperature data to eliminate the influence of rock radiation below the regolith on the echo, constructing a lunar shallow surface physical temperature model based on a one-dimensional thermodynamic equation using the lunar surface physical temperature data as a constraint; combining the physical temperature model with the radiation transfer equation to effectively simulate radiation brightness temperatures at different frequencies; and comparing and matching the observed radiation brightness temperature with the radiation brightness temperature inverted under different dielectric loss conditions to determine the dielectric loss range of the shallow surface layer at different frequencies. Compared with existing technologies, the present invention has the advantages of high prediction accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of lunar shallow layer material property inversion, and in particular to a lunar shallow layer dielectric loss estimation method combining radiation brightness temperature and stratum information. Background Art

[0002] The lunar outer layer, composed primarily of loose materials, preserves important clues to the lunar geological history and planetary evolution, deepening our understanding of the evolution of the inner solar system. Based on experiments with lunar samples, scientists have gained a preliminary understanding of the lunar shallow surface. However, these samples were collected from the lunar nearside, failing to characterize the materials in other regions, such as the farside. Therefore, radiometric characterization using orbiting probes is an important means of obtaining broad-scale data on the properties of the lunar shallow surface, such as thermodynamic and dielectric properties. Brightness temperature data generated by passive radars are key to deciphering the thermal behavior of the shallow surface. However, current understanding of the composition of the received radiation primarily hinges on whether the brightness temperature data include information about the rocky material beneath the lunar regolith. Furthermore, differences in the thermodynamic and dielectric properties of lunar regolith and rock significantly impact the analysis of the shallow surface material properties. When estimating the properties of the lunar shallow surface, appropriate stratigraphic models are needed to determine the source of the brightness temperature, which depends primarily on two factors: radar penetration depth and the thickness of the lunar regolith within the survey area. The radar penetration depth can be preliminarily estimated based on the radar frequency, material density, and mineral content. Therefore, lunar soil thickness is key to interpreting the brightness temperature data.

[0003] Optical and radar data can be used to estimate lunar soil thickness in a variety of ways. For optical detection methods, diameter-based crater morphology methods are generally used. By using differences in crater albedo, impact craters are divided into dark halo craters (the ejecta are material below the lunar soil layer) and bright ray craters (the ejecta are fresh lunar soil material). The relationship between diameter and penetration depth can be used to constrain the upper and lower limits of lunar soil thickness. Orbiter-penetrating radar mainly estimates lunar soil thickness by combining it with laser ranging data. However, the resolution of orbiter data is low, making it difficult to accurately estimate lunar soil thickness. This leads to poor accuracy in interpreting orbiter radiation brightness temperature due to inaccurate lunar soil thickness estimates, and thus reduces the accuracy of image dielectric loss estimates. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for estimating the dielectric loss of the lunar shallow surface layer by combining radiation brightness temperature and stratigraphic information, so as to overcome the shortcomings of poor interpretation accuracy of orbiter radiation brightness temperature caused by inaccurate estimation of lunar soil thickness, realize accurate interpretation of orbiter radiation brightness temperature data and estimate the dielectric loss range of shallow lunar soil materials.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A method for estimating dielectric loss in the lunar shallow surface layer by combining radiation brightness temperature and stratum information includes the following steps:

[0007] Step 1) Obtain Chang'e-2 radiation brightness temperature data and determine the local time of observation;

[0008] Step 2) Acquire and pre-process Chang'e-4 lunar radar data;

[0009] Step 3) performing stratigraphic division based on the pre-processed lunar radar data and extracting lunar soil layer data;

[0010] Step 4) obtaining the Lunar Surveyor thermal band 7 data as the lunar surface physical temperature;

[0011] Step 5) Based on the lunar regolith thickness data from lunar radar detection and the detectable depth of the radiation brightness temperature data, the influence of rock radiation below the lunar regolith on the echo is eliminated, and a lunar surface physical temperature model is constructed based on the one-dimensional thermodynamic equation using the lunar surface physical temperature data as a constraint;

[0012] Step 6) Combining the lunar surface physical temperature model and radiation transfer equation to effectively simulate the brightness temperature of radiation at different frequencies;

[0013] Step 7) Compare and match the observed radiation brightness temperature with the radiation brightness temperature inverted under different dielectric loss conditions to determine the dielectric loss range of the shallow layer at different frequencies.

[0014] The local time at the observation time is calculated based on the solar azimuth, incidence angle and latitude of the observation point.

[0015] Assuming the solar incidence angle is i, the solar azimuth is α, and the latitude of the observation point is λ, then the local time corresponding to the observation time is:

[0016]

[0017] Described step 2) comprises the following steps:

[0018] Step 2-1) Acquire Chang'e-4 lunar radar data;

[0019] Step 2-2) Deduplication: remove duplicate data from lunar radar data;

[0020] Step 2-3) Zero time correction: Align each column of data with the echo time of the strong vacuum-lunar soil echo in the radar echo;

[0021] Step 2-4) DC offset correction;

[0022] Step 2-5) background noise suppression;

[0023] Step 2-6) Bandpass filtering to retain information near the center frequency;

[0024] Step 2-7) Echo Gain: Perform amplitude compensation on deep echo based on radar echo time.

[0025] The step 5) comprises the following steps:

[0026] Step 5-1) Dividing the stratigraphic profile obtained by the lunar radar into a lunar soil layer and a non-lunar soil layer based on the amplitude information of the radar echo;

[0027] Step 5-2) Estimate the thickness of the lunar regolith based on the empirical dielectric constant of the lunar regolith. The lowest thickness detected at the landing area is 7 meters.

[0028] Step 5-3) Compare the lowest lunar soil thickness and the highest brightness temperature data detection depth to determine that the brightness temperature data cannot penetrate the lunar soil layer, that is, all data are composed of shallow lunar soil radiation;

[0029] Step 5-4) Use the lunar surface physical temperature data as constraints and rely on one-dimensional thermodynamic equations to construct a lunar shallow surface physical temperature model.

[0030] The physical temperature model of the lunar shallow surface is:

[0031]

[0032] Where ρ is the density of the medium, c is the specific heat capacity, κ is the thermal conductivity, is the radiance, σ is the Stefan-Boltzmann constant, T s is the physical temperature of the lunar surface, Q s is solar radiation, Q g It's geothermal radiation.

[0033] The step 6) comprises the following steps:

[0034] Step 6-1) estimating the power loss coefficient based on the detection frequency, dielectric constant, and loss tangent;

[0035] Step 6-2) Based on the physical temperatures at different depths provided by the lunar shallow surface physical temperature model, combined with the power loss coefficient and the weight of each layer, an effective simulation of the radiation brightness temperature is performed.

[0036] The power loss coefficient is estimated as follows:

[0037]

[0038] Among them, k i is the power loss coefficient of formation i, ∈ iis the dielectric constant of formation i, f is the detection frequency, tanδ is the loss tangent, and β is an adjustable parameter.

[0039] The effective simulation of the radiation brightness temperature T in step 6-2) B The method is:

[0040]

[0041] Among them, T i is the physical temperature at different depths, W i is the weight of each stratum, d i is the thickness of layer i, r i(i+1) is the reflection coefficient of layers i and i+1, ∈ i is the dielectric constant of layer i, k i is the power loss coefficient of formation i.

[0042] The step 7) comprises the following steps:

[0043] Step 7-1) By adjusting the adjustable parameter β, effective simulation of the radiation brightness temperature data under different dielectric loss conditions is achieved;

[0044] Step 7-2) Based on the simulated brightness temperature data, the maximum and minimum daytime brightness temperature curves observed in the Chang'e-2 brightness temperature data are effectively matched and fitted to invert the dielectric loss range of the shallow material in the Von Karman crater at different frequencies.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] (1) The present invention overcomes the shortcoming of low accuracy of lunar soil thickness estimation by orbiter optical and radar equipment. It combines the stratigraphic information detected by the on-site radar with the orbiter radiation brightness temperature data, and uses a thermodynamic and radiation transfer model to achieve limited simulation of lunar radiation brightness temperature data at different frequencies, thus realizing the constraint of dielectric loss of shallow lunar materials.

[0047] (2) The existing interpretation of radiation brightness temperature data does not fully consider the detection depth of the microwave radiometer and the radiation source of the received data. The present invention obtains accurate lunar subsurface information and estimates the thickness of the lunar soil based on the lunar radar. By comparing the maximum detection depth of the microwave detector at different frequencies, the radiation interference of the material below the lunar soil layer is eliminated, thereby improving the interpretation accuracy of the radiation brightness temperature data. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of the method of the present invention;

[0049] Figure 2This is a graph of Chang'e-2's radiation brightness temperature data and Lunar Prospector's lunar surface physical temperature data;

[0050] Figure 3 A map of the subsurface structure and minimum lunar soil thickness at the Chang'e-4 landing site;

[0051] Figure 4 Schematic diagram of physical temperature curve, where (a) is the simulated physical temperature curve of the lunar surface, and (b) is the simulated physical temperature curve at different depths;

[0052] Figure 5 Simulated brightness temperature curves under different dielectric losses. DETAILED DESCRIPTION

[0053] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0054] This embodiment provides a method for estimating dielectric loss of the lunar shallow surface layer by combining radiation brightness temperature and stratum information. Figure 1 As shown, the following steps are included:

[0055] Step 1) Obtain Chang'e-2 radiation brightness temperature data and determine the local time of observation.

[0056] The local time at the time of observation is calculated based on the solar azimuth, incidence angle and latitude of the observation point:

[0057] Assuming the solar incidence angle is i, the solar azimuth is α, and the latitude of the observation point is λ, then the local time corresponding to the observation time is:

[0058]

[0059] Figure 2 (a)-(d) show 14 sets of data aggregated after calculating the local time of the radiation brightness temperature. The highest values ​​of the Chang'e-2 radiation brightness temperature data all appeared in the 9th group (14:00-15:00), while the lowest values ​​corresponding to 7.8, 19.35 and 37 GHz appeared in the 4th group (5:00-6:00), and the lowest value corresponding to 3 GHz appeared in the 5th group (6:00-7:00).

[0060] Step 2) Acquire Chang'e-4 lunar radar data and perform preprocessing.

[0061] Step 2-1) Acquire Chang'e-4 lunar radar data;

[0062] Step 2-2) Deduplication: remove duplicate data from lunar radar data;

[0063] Step 2-3) Zero time correction: Align each column of data with the echo time of the strong vacuum-lunar soil echo in the radar echo;

[0064] Step 2-4) DC offset correction;

[0065] Step 2-5) background noise suppression;

[0066] Step 2-6) Bandpass filtering to retain information near the center frequency;

[0067] Step 2-7) Echo Gain: Perform amplitude compensation on deep echo based on radar echo time.

[0068] Step 3) Perform stratigraphic division based on the preprocessed lunar radar data and extract lunar soil layer data.

[0069] In order to obtain the necessary stratigraphic information for the simulation of radiation brightness temperature data, a subsurface analysis was performed using the data of the first 27 lunar days (~650 meters of movement distance) from the Chang'e-4 lunar radar. Figure 3 The stratigraphic structure is shown by four black dashed lines, with the uppermost (surface) layer generally interpreted as a relatively uniform layer of lunar regolith with weak radar signatures. Within the initial 300-meter range observed by the Yutu-2 rover, the lunar regolith's radar echo time thickness was approximately 150 nanoseconds, gradually decreasing to ~80 nanoseconds at 380 meters, but rapidly increasing to ~200 nanoseconds after 500 meters. Based on lunar regolith dielectric constant data from lunar sample data, we used an empirical value (relative permittivity of 3) as a parameter for the radar echo-to-depth conversion and calculated that the shallowest lunar regolith thickness in the Chang'e-4 landing area was approximately 7 meters, exceeding the ideal maximum penetration depth of the Chang'e-2 microwave radiometer (approximately 3 meters).

[0070] Step 4) Obtain the Lunar Prospector thermal band 7 data as the lunar surface physical temperature.

[0071] Lunar Prospector lunar surface physical temperature, such as Figure 2 As shown in (e), it reaches a maximum value (347K) at 12:00 am and a maximum value (88K) at 4:00 am.

[0072] Step 5) Based on the lunar regolith thickness data from the lunar radar detection site and the detectable depth of the radiation brightness temperature data, the influence of rock radiation below the lunar regolith on the echo is eliminated, and a lunar surface physical temperature model is constructed based on the one-dimensional thermodynamic equation using the lunar surface physical temperature data as a constraint.

[0073] Step 5-1) Dividing the stratigraphic profile obtained by the lunar radar into a lunar soil layer and a non-lunar soil layer based on the amplitude information of the radar echo;

[0074] Step 5-2) Estimate the thickness of the lunar regolith based on the empirical dielectric constant of the lunar regolith. The lowest thickness detected at the landing area is 7 meters.

[0075] Step 5-3) Compare the lowest lunar soil thickness and the highest brightness temperature data detection depth to determine that the brightness temperature data cannot penetrate the lunar soil layer, that is, all data are composed of shallow lunar soil radiation;

[0076] Step 5-4) Using the lunar surface physical temperature data as constraints, a lunar shallow surface physical temperature model is constructed based on the one-dimensional thermodynamic equation:

[0077]

[0078] Where ρ is the density of the medium, c is the specific heat capacity, κ is the thermal conductivity, is the radiance, σ is the Stefan-Boltzmann constant, T s is the physical temperature of the lunar surface, Q s is solar radiation, Q g It's geothermal radiation.

[0079] Figure 4 (a) Comparison of simulated lunar surface physical temperature data and measured data from lunar probes shows relatively consistent overall distributions. During the day, temperature characteristics are primarily influenced by the combined effects of solar radiation and topography, exhibiting large fluctuations. At night, temperature characteristics are primarily influenced by geothermal heat, resulting in relatively small surface physical temperature variations. Figure 4 (b) shows that within the shallow range of a few centimeters, the day-night difference in physical temperature decreases rapidly. In the Chang'e-4 landing area, this depth is mainly within the range of 7 centimeters, while at a depth of 50 centimeters, the day-night physical temperature is approximately a straight line, indicating that the day-night temperature difference changes in the Chang'e-2 radiation brightness temperature data are mainly caused by fluctuations in shallow physical temperature.

[0080] Step 6) Combine the lunar shallow surface physical temperature model and radiation transfer equation to effectively simulate the brightness temperature of radiation at different frequencies.

[0081] Step 6-1) Estimate the power loss coefficient based on the detection frequency, dielectric constant and loss tangent:

[0082]

[0083] Among them, k i is the power loss coefficient of formation i, ∈ i is the dielectric constant of formation i, f is the detection frequency, tanδ is the loss tangent, and β is an adjustable parameter.

[0084] Step 6-2) Based on the physical temperature at different depths provided by the lunar surface physical temperature model, the power loss coefficient and the weight of each layer are combined to effectively simulate the radiation brightness temperature TB :

[0085]

[0086] Among them, T i is the physical temperature at different depths, W i is the weight of each stratum, d i is the thickness of layer i, r i(i+1) is the reflection coefficient of layers i and i+1, ∈ i is the dielectric constant of layer i, k i is the power loss coefficient of formation i.

[0087] Step 7) Compare and match the observed radiation brightness temperature with the radiation brightness temperature inverted under different dielectric loss conditions to determine the dielectric loss range of the shallow layer at different frequencies.

[0088] Step 7-1) By adjusting the adjustable parameter β, effective simulation of the radiation brightness temperature data under different dielectric loss conditions is achieved;

[0089] Step 7-2) Based on the simulated brightness temperature data, the maximum and minimum daytime brightness temperature curves observed in the Chang'e-2 brightness temperature data are effectively matched and fitted to invert the dielectric loss range of the shallow material in the Von Karman crater at different frequencies.

[0090] Figure 5 The study demonstrates how simulated brightness temperatures match real-world data at varying dielectric loss levels. Adjusting the dielectric loss allows for effective analysis of brightness temperature data based on maximum loss (low detection depth, strong diurnal temperature variation) and minimum loss (high detection depth, weak diurnal temperature variation), thereby estimating and constraining the dielectric loss range at different frequencies. The estimated dielectric loss ranges for the shallow lunar regolith in Von Kármán crater at 3, 7.8, 19.35, and 37 GHz are 0.0066-0.0262, 0.0027-0.0173, 0.0019-0.0097, and 0.0023-0.0116, respectively.

[0091] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A method for estimating dielectric loss in the lunar shallow surface layer by combining radiation brightness temperature and stratum information, characterized in that: The following steps are involved: Step 1) Obtain Chang'e-2 radiation brightness temperature data and determine the local time of observation; Step 2) Acquire and pre-process Chang'e-4 lunar radar data; Step 3) performing stratigraphic division based on the pre-processed lunar radar data and extracting lunar soil layer data; Step 4) obtaining the Lunar Surveyor thermal band 7 data as the lunar surface physical temperature; Step 5) Based on the lunar regolith thickness data from the lunar radar and the detectable depth of the radiation brightness temperature data, the influence of the rock radiation below the lunar regolith on the echo is eliminated, and the lunar surface physical temperature data is used as a constraint condition to construct a lunar shallow surface physical temperature model based on the one-dimensional thermodynamic equation: Where ρ is the density of the medium, c is the specific heat capacity, κ is the thermal conductivity, is the radiance, σ is the Stefan-Boltzmann constant, Q s is the physical temperature of the lunar surface, Q s is solar radiation, Q g It is geothermal radiation; Step 6) Combining the lunar surface physical temperature model and radiation transfer equation to effectively simulate the brightness temperature of radiation at different frequencies; The step 6) comprises the following steps: Step 6-1) estimating the power loss coefficient based on the detection frequency, dielectric constant, and loss tangent; Step 6-2) Based on the physical temperature at different depths provided by the lunar surface physical temperature model, combined with the power loss coefficient and the weight of each layer, the radiation brightness temperature T is calculated. B An effective simulation of: Among them, T i is the physical temperature at different depths, W i is the weight of each stratum, d i is the thickness of layer i, r i(i+1) is the reflection coefficient of layers i and i+1, ∈ i is the dielectric constant of layer i, k i is the power loss coefficient of formation i; Step 7) Compare and match the observed radiation brightness temperature with the radiation brightness temperature inverted under different dielectric loss conditions to determine the dielectric loss range of the shallow layer at different frequencies.

2. The method for estimating dielectric loss of the lunar shallow surface layer by combining radiation brightness temperature and stratum information according to claim 1 is characterized in that: The local time at the observation time is calculated based on the solar azimuth, incidence angle and latitude of the observation point.

3. The method for estimating dielectric loss of the lunar shallow surface layer by combining radiation brightness temperature and stratum information according to claim 2, characterized in that: Assuming the solar incidence angle is i, the solar azimuth is α, and the latitude of the observation point is λ, then the local time corresponding to the observation time is:

4. The method for estimating dielectric loss of the lunar shallow surface layer by combining radiation brightness temperature and stratum information according to claim 1, characterized in that: The step 2) comprises the following steps: Step 2-1) Acquire Chang'e-4 lunar radar data; Step 2-2) Deduplication: remove duplicate data from lunar radar data; Step 2-3) Zero time correction: Align each column of data with the echo time of the strong vacuum-lunar soil echo in the radar echo; Step 2-4) DC offset correction; Step 2-5) background noise suppression; Step 2-6) Bandpass filtering to retain information near the center frequency; Step 2-7) Echo Gain: Perform amplitude compensation on deep echo based on radar echo time.

5. The method for estimating dielectric loss of the lunar shallow surface layer by combining radiation brightness temperature and stratum information according to claim 1, characterized in that: The step 5) comprises the following steps: Step 5-1) Dividing the stratigraphic profile obtained by the lunar radar into a lunar soil layer and a non-lunar soil layer based on the amplitude information of the radar echo; Step 5-2) Estimate the thickness of the lunar regolith based on the empirical dielectric constant of the lunar regolith. The lowest thickness detected at the landing area is 7 meters. Step 5-3) Compare the lowest lunar soil thickness and the highest brightness temperature data detection depth to determine that the brightness temperature data cannot penetrate the lunar soil layer, that is, all data are composed of shallow lunar soil radiation; Step 5-4) Use the lunar surface physical temperature data as constraints and rely on one-dimensional thermodynamic equations to construct a lunar shallow surface physical temperature model.

6. The method for estimating dielectric loss of the lunar shallow surface layer by combining radiation brightness temperature and stratum information according to claim 1, characterized in that: The power loss coefficient is estimated as follows: Among them, k i is the power loss coefficient of formation i, ∈ i is the dielectric constant of formation i, f is the detection frequency, tanδ is the loss tangent, and β is an adjustable parameter.

7. The method for estimating dielectric loss of the lunar shallow surface layer by combining radiation brightness temperature and stratum information according to claim 6, characterized in that: The step 7) comprises the following steps: Step 7-1) By adjusting the adjustable parameter β, effective simulation of the radiation brightness temperature data under different dielectric loss conditions is achieved; Step 7-2) Based on the simulated brightness temperature data, the maximum and minimum daytime brightness temperature curves observed in the Chang'e-2 brightness temperature data are effectively matched and fitted to invert the dielectric loss range of the shallow material in the Von Karman crater at different frequencies.

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