Medium-wave infrared spectrum calibration method and device, electronic equipment and program product

Abstract

The embodiment of the invention discloses a medium-wave infrared spectrum calibration method and device, electronic equipment and a program product. The method comprises the following steps: acquiring a reference water vapor absorption spectrum in a medium-wave infrared target wave band; in the medium-wave infrared target wave band, an atmospheric radiation spectrum is determined by a water vapor absorption spectrum, and the waveform stability degree of the reference water vapor absorption spectrum is higher than a set threshold value; obtaining a medium-wave infrared radiation interference signal observed by the infrared spectrum detector; determining a spectrum calibration coefficient by optimizing the deviation between an observation spectrum corresponding to the medium-wave infrared radiation interference signal and the reference water vapor absorption spectrum; and realizing the spectrum calibration of the infrared spectrum detector by using the spectrum calibration coefficient. According to the technical scheme, the medium-wave infrared band observation data is directly used, and spectrum calibration is carried out on the medium-wave infrared observation spectrum.

Description

Technical Field

[0001] The present disclosure relates to the field of satellite technology, and in particular, to a mid-wave infrared spectral calibration method, apparatus, electronic device, and program product. Background Art

[0002] Currently, the on-orbit spectral calibration methods for spectral sensors mainly include: on-board standard lamp spectral calibration method and spectral matching calibration method based on atmospheric absorption characteristics. Since most domestic satellites are not equipped with standard lamps, the on-board standard lamp spectral calibration method is not applicable to the spectral sensors on most domestic satellites.

[0003] The spectral matching calibration methods mainly include spectral angle method, spectral Euclidean distance method, and correlation coefficient method. Usually, the long-wave infrared band data is used for calibration because the absorption and scattering of long-wave infrared by components in the atmosphere are relatively weak, making the long-wave infrared signal more accurately reflect the radiation characteristics of the target to a certain extent. In the mid-wave and short-wave infrared bands, due to the strong absorption ability of water vapor, when using the mid-wave and short-wave infrared bands for calibration, the interference of water vapor will make the calibration results inaccurate. In actual operation, the infrared spectral imager generally directly uses the calibration parameters of the long-wave infrared band. Usually, the infrared spectral detector uses a beam splitter to project infrared radiation of different bands onto different detection arrays for observation respectively. However, the optical axis offsets of different detection arrays are not consistent. Therefore, directly using the calibration parameters of the long-wave infrared band to calibrate the entire infrared band will inevitably affect the calibration accuracy of the mid-wave and short-wave infrared bands. Summary of the Invention

[0004] Embodiments of the present disclosure provide a mid-wave infrared spectral calibration method, apparatus, electronic device, and program product.

[0005] In a first aspect, a mid-wave infrared spectral calibration method is provided in embodiments of the present disclosure, which includes:

[0006] Obtain a reference water vapor absorption spectrum in the mid-wave infrared target band; in the mid-wave infrared target band, the atmospheric radiation spectrum is determined by the water vapor absorption spectrum, and the waveform stability degree of the reference water vapor absorption spectrum is higher than a set threshold;

[0007] Obtain the mid-wave infrared radiation interference signal observed by the infrared spectral detector;

[0008] Determine the spectral calibration coefficient by optimizing the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum;

[0009] Implement spectral calibration of the infrared spectral detector using the spectral calibration coefficient.

[0010] Further, the method further includes:

[0011] Calculate the top of the atmosphere under standard atmospheric conditions and set the radiation absorption spectra of gas molecules of a set type in the mid-wave infrared band; the gas molecules of the set type include water vapor molecules and other types of molecules;

[0012] Based on the radiation absorption spectra, determine the mid-wave infrared target band by comparing the radiation absorption of the water vapor molecules and other types of molecules.

[0013] Further, the method further includes:

[0014] Obtain different water vapor vertical profiles corresponding to different atmospheric humidity conditions;

[0015] Calculate the radiation absorption spectra of water vapor molecules under the different water vapor vertical profile conditions;

[0016] Determine the part of the radiation absorption spectra that is in the mid-wave infrared target band and has a waveform stability degree higher than the set threshold as the reference water vapor absorption spectra.

[0017] Further, determine the spectral calibration coefficient by optimizing the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectra, including:

[0018] Calculate the spectral calibration coefficient when the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectra is minimized through an iterative optimization algorithm.

[0019] Further, calculate the spectral calibration coefficient when the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectra is minimized through an iterative optimization algorithm, including:

[0020] Assign an initial value to the candidate calibration coefficient;

[0021] Use the candidate calibration coefficient to convert the mid-wave infrared radiation interference signal into an observed spectrum to be optimized;

[0022] Calculate the candidate deviation when the correlation between the observed spectrum to be optimized and the reference water vapor absorption spectra is the largest;

[0023] Update the candidate calibration coefficient and jump to the step of using the candidate calibration coefficient to convert the mid-wave infrared radiation interference signal into an observed spectrum to be optimized, calculate the candidate deviation corresponding to the updated candidate calibration coefficient until the updated candidate calibration coefficient meets the set conditions;

[0024] Determine the candidate calibration coefficient corresponding to the smallest candidate deviation as the spectral calibration coefficient.

[0025] Second aspect, an apparatus for mid-wave infrared spectral calibration is provided in an embodiment of the present disclosure. The apparatus includes:

[0026] A first acquisition module configured to acquire a reference water vapor absorption spectrum in a mid-wave infrared target band; in the mid-wave infrared target band, the atmospheric radiation spectrum is determined by the water vapor absorption spectrum, and the waveform stability degree of the reference water vapor absorption spectrum is higher than a set threshold;

[0027] A second acquisition module configured to acquire a mid-wave infrared radiation interference signal observed by an infrared spectral detector;

[0028] A determination module configured to determine a spectral calibration coefficient by optimizing the deviation between an observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum;

[0029] A calibration module configured to implement spectral calibration of the infrared spectral detector by using the spectral calibration coefficient.

[0030] Further, the determination module includes:

[0031] An iteration sub-module configured to calculate a spectral calibration coefficient when the deviation between an observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum is minimized through an iterative optimization algorithm.

[0032] The function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions.

[0033] In a possible design, the structure of the above apparatus includes a memory and a processor. The memory is used to store one or more computer instructions for supporting the above apparatus to execute the corresponding method, and the processor is configured to execute the computer instructions stored in the memory. The above apparatus may further include a communication interface for the above apparatus to communicate with other devices or communication networks.

[0034] Third aspect, an electronic device is provided in an embodiment of the present disclosure, including a memory, a processor, and a computer program stored on the memory. The processor executes the computer program to implement the method described in any of the above aspects.

[0035] Fourth aspect, a computer-readable storage medium is provided in an embodiment of the present disclosure, which is used to store computer instructions used by any of the above apparatuses. When the computer instructions are executed by a processor, they are used to implement the method described in any of the above aspects.

[0036] Fifthly, embodiments of the present disclosure provide a computer program product, which includes computer instructions that, when executed by a processor, are used to implement the methods described in any of the above aspects.

[0037] The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects:

[0038] Through the above method, this embodiment realizes directly using the observation data in the mid-wave infrared band to perform spectral calibration on the observation spectrum in the mid-wave infrared band. Compared with the method of using long-wave infrared band data to replace mid-wave infrared band data for mid-wave infrared band spectral calibration in the existing technology, it can improve the spectral calibration accuracy of the mid-wave infrared band.

[0039] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In combination with the accompanying drawings, through the following detailed description of non-limiting embodiments, other features, objectives, and advantages of the present disclosure will become more apparent. In the drawings:

[0041] Figure 1 A flowchart showing a mid-wave infrared spectral calibration method according to an embodiment of the present disclosure.

[0042] Figure 2 Showing the radiation absorption spectra of various gas molecules according to an embodiment of the present disclosure.

[0043] Figure 3 Showing various water vapor vertical profiles corresponding to selected time parameters and position parameters according to an embodiment of the present disclosure.

[0044] Figure 4 Showing Figure 3 The water vapor absorption spectra in the 1960 - 1980 band corresponding to various water vapor vertical profiles.

[0045] Figure 5 A structural block diagram showing a mid-wave infrared spectral calibration device according to an embodiment of the present disclosure.

[0046] Figure 6 A structural block diagram showing an electronic device provided by an embodiment of the present disclosure.

[0047] Figure 7 A schematic structural diagram of an electronic device suitable for implementing the mid-wave infrared spectral calibration method according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] In the following, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for clarity, parts unrelated to the description of the exemplary embodiments are omitted in the drawings.

[0049] In the present disclosure, it should be understood that terms such as "including" or "having" are intended to indicate the presence of features, numbers, steps, actions, components, parts, or combinations thereof disclosed in this specification, and do not exclude the possibility of the presence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0050] It should also be noted that, without conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with embodiments.

[0051] Details of the embodiments of the present disclosure will be introduced in detail below through specific embodiments.

[0052] Figure 1 A flowchart showing a mid-wave infrared spectral calibration method according to an embodiment of the present disclosure is shown. As Figure 1 shown, the mid-wave infrared spectral calibration method includes the following steps:

[0053] In step S101, a reference water vapor absorption spectrum in the mid-wave infrared target band is obtained; in the mid-wave infrared target band, the atmospheric radiation spectrum is determined by the water vapor absorption spectrum, and the waveform stability degree of the reference water vapor absorption spectrum is higher than a set threshold;

[0054] In step S102, a mid-wave infrared radiation interference signal observed by an infrared spectral detector is obtained;

[0055] In step S103, by optimizing the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum, a spectral calibration coefficient is determined;

[0056] In step S104, spectral calibration of the infrared spectral detector is achieved by using the spectral calibration coefficient.

[0057] In this embodiment, the mid-wave infrared target band is a part of the mid-wave infrared band. The independence of the water vapor absorption spectrum in this target band is relatively good. That is to say, the radiation absorption of water vapor molecules in this target band is relatively large, while the radiation absorption of other molecules is very small or negligible. Therefore, the absorption of other molecules in this target band can be ignored compared with that of water vapor molecules. At the same time, the water vapor absorption spectrum in this target band has the characteristic of stable waveform and will not change significantly or basically will not change with the change of atmospheric humidity conditions. It can be understood that the atmospheric radiation spectrum is determined by the water vapor absorption spectrum, which means that in this mid-wave infrared target band, the atmospheric radiation spectrum depends on the radiation absorption of water vapor molecules, and the influence of the radiation absorption of other gas molecules on the atmospheric radiation spectrum can be ignored.

[0058] In some embodiments, a set threshold can be set. When the stability degree of the water vapor absorption spectrum waveform is higher than this set threshold, it can be considered that the waveform of the water vapor absorption spectrum is stable. Therefore, the reference water vapor absorption spectrum with stable waveform in the mid-wave infrared target band can be selected from different atmospheric humidity conditions. This reference water vapor absorption spectrum is used as the reference spectrum for the calibration of the infrared spectrometer, and its wave number range is the range where the mid-wave infrared target band is located.

[0059] During the spectral calibration process, the deviation between the observation spectrum corresponding to the mid-wave infrared radiation interference signal observed by the infrared spectrometer and the above reference water vapor absorption spectrum can be optimized, and the spectral calibration coefficient can be calculated, so as to realize the spectral calibration of the infrared spectrometer based on the optimized spectral calibration coefficient. It can be understood that the observation spectrum is the spectrum within the wave number range corresponding to the mid-wave infrared target band.

[0060] Through the above method, this embodiment realizes directly using the observation data in the mid-wave infrared band to perform spectral calibration on the observation spectrum in the mid-wave infrared band. Compared with the method of using long-wave infrared band data to replace mid-wave infrared band data for mid-wave infrared band spectral calibration in the prior art, it can improve the spectral calibration accuracy of the mid-wave infrared band.

[0061] In an alternative implementation manner of this embodiment, the method further includes the following steps:

[0062] Calculate the radiation absorption spectrum of the set types of gas molecules at the top of the atmosphere under standard atmospheric conditions in the mid-wave infrared band; the set types of gas molecules include water vapor molecules and other types of molecules;

[0063] Based on the radiation absorption spectrum, by comparing the radiation absorption situations between the water vapor molecules and other types of molecules, determine the mid-wave infrared target band.

[0064] In this optional implementation, the specified types of gas molecules may include water vapor molecules and other types of gas molecules, such as CH4, CO, CO2, N2O, O3, SO2, etc. In some embodiments, the LBLRTM atmospheric radiation transfer model can be used to calculate the radiation absorption spectra of the specified types of gas molecules in the middle infrared band at the top of the atmosphere under standard atmospheric conditions. Then, by comparing the radiation absorption spectra corresponding to different gas molecules, the target band of the middle infrared wave in which the radiation absorption of water vapor molecules is much greater than that of other gas molecules can be found. That is to say, in the target band of the middle infrared wave, the radiation absorption of water vapor molecules is much greater than that of other gas molecules, so the radiation absorption of other gas molecules can be ignored. The radiation absorption spectra of the specified types of gas molecules in the middle infrared band at the top of the atmosphere under standard atmospheric conditions are as Figure 2 shown. It can be seen from this that the radiation absorption of water vapor molecule H2O is the most obvious in the 1960 - 1980 band, and the radiation absorption spectra of other gas molecules can be almost ignored. Therefore, 1960 - 1980 can be determined as the target band of the middle infrared wave. It can be understood that the above is only an example. In practical applications, other target bands of the middle infrared wave can also be selected by other means, and the present disclosure does not make specific restrictions on this.

[0065] In an optional implementation of this embodiment, the method further includes the following steps:

[0066] Obtain different water vapor vertical profiles corresponding to different atmospheric humidity conditions;

[0067] Calculate the radiation absorption spectra of water vapor molecules under the conditions of the different water vapor vertical profiles;

[0068] Determine the part of the radiation absorption spectrum that is in the target band of the middle infrared wave and whose waveform stability degree is higher than the set threshold as the reference water vapor absorption spectrum.

[0069] In this optional implementation, different water vapor vertical profiles can be obtained in the following way: First, select the position parameters and time parameters representing different atmospheric humidity conditions, such as a certain longitude and latitude position on the ocean, different dates in different seasons, and different time points. Then, use the global meteorological field reanalysis data (such as ERA5) to screen out the different water vapor vertical profiles corresponding to the selected above position parameters and time parameters. After that, use the LBLRTM atmospheric radiation transfer model to calculate the radiation absorption spectra of water vapor molecules under these different water vapor vertical profiles, and select the part of these radiation absorption spectra that is in the target band of the middle infrared wave and whose waveform stability degree is higher than the set threshold as the reference water vapor absorption spectrum. In some embodiments, the radiation absorption spectrum with the highest waveform stability degree in the target band of the middle infrared wave can be used as the reference water vapor absorption spectrum. SeeFigure 3 As shown, after selecting a certain latitude and longitude position on the ocean, the time is selected as the 1st, 10th, 20th, and 30th of January, April, July, and October 2024, and the vertical water vapor profiles at 0:00, 6:00, 12:00, and 18:00. The water vapor absorption spectra in the 1960 - 1980 band corresponding to these vertical water vapor profiles are as Figure 4 shown. Based on the above principles, from Figure 4 the water vapor absorption spectra shown, the water vapor absorption spectra in the 1960 - 1962 band and / or the 1975 - 1977 band can be selected as the reference water vapor absorption spectra.

[0070] In an alternative implementation of this embodiment, step S103, that is, the step of determining the spectral calibration coefficient by optimizing the deviation between the observed spectrum corresponding to the mid - wave infrared radiation interference signal and the reference water vapor absorption spectrum, further includes the following steps:

[0071] Using an iterative optimization algorithm, calculate the spectral calibration coefficient when the deviation between the observed spectrum corresponding to the mid - wave infrared radiation interference signal and the reference water vapor absorption spectrum is minimized.

[0072] In this alternative implementation, the mid - wave infrared radiation interference signal can be converted into the corresponding observed spectrum B′(σ) by using Fourier transform, and the conversion formula is as follows:

[0073]

[0074] where σ is the wavenumber within the mid - wave infrared target band range, N is the number of mid - wave infrared radiation interference signals, GST is the mid - wave infrared radiation interference signal value, λ is the equal optical path difference sampling interval of the mid - wave infrared radiation interference signal: λ = 0.8523um, and SpeCal is the calibration coefficient.

[0075] The deviation between the observed spectrum and the reference water vapor absorption spectrum can be calculated using the cross - correlation function, as shown in the following formula:

[0076]

[0077] where BB′ R n (Δσ) is the cross - correlation function value, B(σ) is the reference water vapor absorption spectrum, the wavenumber range of the mid - wave infrared target band is from σ1 to σ

[0078] By solving the above formulas (1) and (2) through an iterative optimization algorithm, the calibration coefficient SpeCal when Δσ is minimized is obtained, and thus the mid - wave infrared radiation interference signal is calibrated using this calibration coefficient.

[0079] In an alternative implementation of this embodiment, the step of calculating the spectral calibration coefficient when the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum is minimized through an iterative optimization algorithm further includes the following steps:

[0080] Assign an initial value to the candidate calibration coefficient;

[0081] Using the candidate calibration coefficient, convert the mid-wave infrared radiation interference signal into an observed spectrum to be optimized;

[0082] Calculate the candidate deviation when the correlation between the observed spectrum to be optimized and the reference water vapor absorption spectrum is maximized;

[0083] Update the candidate calibration coefficient and jump to the step of using the candidate calibration coefficient to convert the mid-wave infrared radiation interference signal into an observed spectrum to be optimized, calculate the candidate deviation corresponding to the updated candidate calibration coefficient until the updated candidate calibration coefficient meets the set conditions;

[0084] Determine the candidate calibration coefficient corresponding to the smallest candidate deviation as the spectral calibration coefficient.

[0085] In this alternative implementation, the calibration coefficient can be calculated through the following iterative optimization method:

[0086] First, determine the candidate values of the calibration coefficient during the iteration process and assign an initial value to it. For the convenience of describing the following text, the candidate values of the calibration coefficient are referred to as candidate calibration coefficients. In some embodiments, the range of candidate values of the calibration coefficient can be set to (0, 1], and this range of candidate values is sampled at a set step size, such as 0.001, to obtain the candidate values of the calibration coefficient in each iterative optimization process. The initial value of the candidate calibration coefficient can be 1, and it is updated in a decreasing manner with the candidate values obtained by the above sampling in each iteration.

[0087] Secondly, substitute the candidate calibration coefficient into the above formula (1) to obtain the observed spectrum to be optimized of the mid-wave infrared radiation interference signal, calculate the cross-correlation function value between the observed spectrum to be optimized and the reference water vapor absorption spectrum using formula (2), and determine the Δσ when the cross-correlation function value is the largest as the candidate deviation obtained in the current iteration process.

[0088] After that, update the candidate calibration coefficient using the candidate values obtained by the above sampling, that is, select the unused ones from the candidate values obtained by the above sampling as the current candidate calibration coefficient, and then repeat the above steps to calculate the candidate deviation corresponding to the updated candidate calibration coefficient until the candidate deviations corresponding to all the candidate values obtained by the sampling are calculated. Therefore, the set condition that the updated candidate calibration coefficient needs to meet is that the candidate deviations corresponding to all the candidate values have been calculated.

[0089] Finally, the candidate calibration coefficient corresponding to the minimum candidate deviation is used as the finally optimized calibration coefficient, and the observed spectrum corresponding to the finally optimized calibration coefficient is used as the spectral calibration result of the infrared spectral detector, thereby completing the spectral calibration process.

[0090] The following is an embodiment of the disclosed device, which can be used to execute the embodiment of the disclosed method.

[0091] Figure 5 The structural block diagram of a mid-wave infrared spectral calibration device according to an embodiment of the present disclosure is shown. This device can be implemented as part or all of an electronic device through software, hardware, or a combination of both. As Figure 5 shown, the mid-wave infrared spectral calibration device includes:

[0092] A first acquisition module 501, configured to acquire a reference water vapor absorption spectrum in a mid-wave infrared target band; in the mid-wave infrared target band, the atmospheric radiation spectrum is determined by the water vapor absorption spectrum, and the waveform stability degree of the reference water vapor absorption spectrum is higher than a set threshold;

[0093] A second acquisition module 502, configured to acquire a mid-wave infrared radiation interference signal observed by the infrared spectral detector;

[0094] A determination module 503, configured to determine a spectral calibration coefficient by optimizing the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum;

[0095] A calibration module 504, configured to use the spectral calibration coefficient to implement spectral calibration of the infrared spectral detector.

[0096] In this embodiment, the mid-wave infrared target band is a part of the mid-wave infrared band. The independence of the water vapor absorption spectrum in this target band is good. That is to say, the radiation absorption of water vapor molecules in this target band is large, while the radiation absorption of other molecules is very small or none. Therefore, the absorption of other molecules in this target band can be ignored compared with that of water vapor molecules; at the same time, the water vapor absorption spectrum in this target band has the characteristic of stable waveform and will not change significantly with the change of atmospheric humidity conditions, or basically will not change. That the atmospheric radiation spectrum is determined by the water vapor absorption spectrum can be understood as that in this mid-wave infrared target band, the atmospheric radiation spectrum depends on the radiation absorption of water vapor molecules, and the influence of the radiation absorption of other gas molecules on the atmospheric radiation spectrum can be ignored.

[0097] In some embodiments, a set threshold can be set. When the stability degree of the water vapor absorption spectrum waveform is higher than this set threshold, it can be considered that the waveform of the water vapor absorption spectrum is stable. Therefore, the reference water vapor absorption spectra with stable waveforms in the medium-wave infrared target band can be selected under different atmospheric humidity conditions. This reference water vapor absorption spectrum is used as the reference spectrum for the calibration of the infrared spectrometer, and its wavenumber range is the range where the medium-wave infrared target band is located.

[0098] During the spectral calibration process, the deviation between the observed spectrum corresponding to the medium-wave infrared radiation interference signal observed by the infrared spectrometer and the above reference water vapor absorption spectrum can be optimized, and the spectral calibration coefficient can be calculated, so as to realize the spectral calibration of the infrared spectrometer based on the optimized spectral calibration coefficient. It can be understood that the observed spectrum is the spectrum within the wavenumber range corresponding to the medium-wave infrared target band.

[0099] Through the above device in this embodiment, it is realized to directly use the observation data in the medium-wave infrared band to perform spectral calibration on the observed spectrum in the medium-wave infrared band. Compared with the method of using long-wave infrared band data to replace medium-wave infrared band data for spectral calibration in the medium-wave infrared band in the prior art, it can improve the spectral calibration accuracy in the medium-wave infrared band.

[0100] In an optional implementation manner of this embodiment, the device further further includes:

[0101] A first calculation module, configured to calculate the radiation absorption spectrum of the set type of gas molecules at the top of the atmosphere under standard atmospheric conditions in the medium-wave infrared band; the set type of gas molecules includes water vapor molecules and other types of molecules;

[0102] A comparison module, configured to determine the medium-wave infrared target band based on the radiation absorption spectrum by comparing the radiation absorption situations between the water vapor molecules and other types of molecules.

[0103] In this optional implementation manner, the set type of gas molecules can include water vapor molecules and other types of gas molecules, such as CH4, CO, CO2, N2O, O3, SO2, etc. In some embodiments, the LBLRTM atmospheric radiation transfer model can be used to calculate the radiation absorption spectra of the set type of gas molecules at the top of the atmosphere under standard atmospheric conditions in their respective medium-wave infrared bands, and then by comparing the radiation absorption spectra corresponding to different gas molecules, find out the medium-wave infrared wave target band where the radiation absorption of water vapor molecules is much greater than that of other gas molecules. That is to say, in the medium-wave infrared target band, the radiation absorption of water vapor molecules is much greater than that of other gas molecules, so the radiation absorption of other gas molecules can be ignored. The radiation absorption spectra of the set type of gas molecules at the top of the atmosphere under standard atmospheric conditions in their respective medium-wave infrared bands are asFigure 2 As shown, it can be seen that the radiative absorption of water vapor molecules H2O in the 1960 - 1980 band is the most obvious, and the radiative absorption spectra of other gas molecules can be almost ignored. Therefore, the 1960 - 1980 band can be determined as the mid - wave infrared target band. It can be understood that the above is only an example, and in practical applications, other mid - wave infrared target bands can also be selected by other means, and the present disclosure does not make specific limitations on this.

[0104] In an alternative implementation of this embodiment, the apparatus further includes:

[0105] A third acquisition module, configured to acquire different water vapor vertical profiles corresponding to different atmospheric humidity conditions;

[0106] A second calculation module, configured to calculate the radiative absorption spectra of water vapor molecules under the conditions of the different water vapor vertical profiles;

[0107] A reference determination module, configured to determine, as the reference water vapor absorption spectrum, the part of the radiative absorption spectrum that is in the mid - wave infrared target band and has a waveform stability degree higher than the set threshold.

[0108] In this alternative implementation, different water vapor vertical profiles can be obtained in the following way: First, select position parameters and time parameters representing different atmospheric humidity conditions, such as selecting a certain longitude and latitude position on the ocean, different dates in different seasons, and different time points. Then, use global meteorological field re - analysis data (such as ERA5) to screen out different water vapor vertical profiles corresponding to the selected above - mentioned position parameters and time parameters. After that, use the LBLRTM atmospheric radiative transfer model to calculate the radiative absorption spectra of water vapor molecules under the conditions of these different water vapor vertical profiles, and screen out, from the parts of these radiative absorption spectra that are in the mid - wave infrared target band, the parts with a waveform stability degree higher than the set threshold as the reference water vapor absorption spectrum. In some embodiments, the radiative absorption spectrum with the highest waveform stability degree in the mid - wave infrared target band can be used as the reference water vapor absorption spectrum. See Figure 3 As shown, after selecting a certain longitude and latitude position on the ocean, the time selects the 1st, 10th, 20th, and 30th of January, April, July, and October 2024, and the water vapor vertical profiles at 0 o'clock, 6 o'clock, 12 o'clock, and 18 o'clock. The water vapor absorption spectra in the 1960 - 1980 band corresponding to these water vapor vertical profiles are as Figure 4 shown. Based on the above principle, from the Figure 4 shown water vapor absorption spectra, the water vapor absorption spectra in the 1960 - 1962 band and / or the 1975 - 1977 band can be screened out as the reference water vapor absorption spectrum.

[0109] In an alternative implementation of this embodiment, the determination module includes:

[0110] An iteration sub-module, configured to calculate the spectral calibration coefficient when the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum is minimized through an iterative optimization algorithm.

[0111] In this optional implementation, the mid-wave infrared radiation interference signal can be converted into the corresponding observed spectrum B′(σ) by using Fourier transform, and the conversion formula is as follows:

[0112]

[0113] Where, σ is the wavenumber within the mid-wave infrared target band range, N is the number of mid-wave infrared radiation interference signals, GST is the value of the mid-wave infrared radiation interference signal, λ is the equal optical path difference sampling interval of the mid-wave infrared radiation interference signal: λ = 0.8523um, and SpeCal is the calibration coefficient.

[0114] The deviation between the observed spectrum and the reference water vapor absorption spectrum can be calculated by using the cross-correlation function, as shown in the following formula:

[0115]

[0116] Where, R BB′ (Δσ) is the cross-correlation function value, B(σ) is the reference water vapor absorption spectrum, and the wavenumber range of the mid-wave infrared target band is from σ1 to σ n , and Δσ is the deviation between the observed spectrum and the reference water vapor absorption spectrum.

[0117] The above formulas (1) and (2) are solved through an iterative optimization algorithm to obtain the calibration coefficient SpeCal when Δσ is the smallest, so as to calibrate the mid-wave infrared radiation interference signal by using this calibration coefficient.

[0118] In an optional implementation of this embodiment, the iteration sub-module includes:

[0119] An assignment sub-module, configured to assign an initial value to the candidate calibration coefficient;

[0120] A conversion sub-module, configured to convert the mid-wave infrared radiation interference signal into an observed spectrum to be optimized by using the candidate calibration coefficient;

[0121] A calculation sub-module, configured to calculate the candidate deviation when the correlation between the observed spectrum to be optimized and the reference water vapor absorption spectrum is the largest;

[0122] Update the candidate calibration coefficient, and jump to the step of converting the mid-wave infrared radiation interference signal into the observed spectrum to be optimized by using the candidate calibration coefficient, and calculate the candidate deviation corresponding to the updated candidate calibration coefficient until the updated candidate calibration coefficient meets the set conditions;

[0123] Determine the candidate calibration coefficient corresponding to the smallest candidate deviation as the spectral calibration coefficient.

[0124] In this alternative implementation, the calibration coefficient can be calculated by the following iterative optimization device:

[0125] First, determine the candidate values of the calibration coefficient during the iteration process and assign an initial value to it. For the convenience of subsequent description, the candidate values of the calibration coefficient are referred to as candidate calibration coefficients. In some embodiments, the range of candidate values of the calibration coefficient can be set to (0, 1], and the range of candidate values is sampled at a set step size, such as 0.001, to obtain the candidate values of the calibration coefficient in each iteration optimization process. The initial value of the candidate calibration coefficient can be 1, and each time it is updated in a decreasing manner with the candidate values obtained by the above sampling.

[0126] Secondly, substitute the candidate calibration coefficient into the above formula (1) to obtain the observed spectrum to be optimized of the mid-wave infrared radiation interference signal, calculate the cross-correlation function value between the observed spectrum to be optimized and the reference water vapor absorption spectrum by using formula (2), and determine the Δσ when the cross-correlation function value is the largest as the candidate deviation obtained in the current iteration process.

[0127] After that, update the candidate calibration coefficient by using the candidate values obtained by the above sampling, that is, select the unused candidate values obtained by the above sampling as the current candidate calibration coefficient, and then repeat the above steps to calculate the candidate deviation corresponding to the updated candidate calibration coefficient until the candidate deviations corresponding to all the candidate values obtained by sampling are calculated. Therefore, the set condition that the updated candidate calibration coefficient needs to meet is that the candidate deviations corresponding to all the candidate values have been calculated.

[0128] Finally, take the candidate calibration coefficient corresponding to the smallest candidate deviation as the finally optimized calibration coefficient, and take the observed spectrum corresponding to the finally optimized calibration coefficient as the spectral calibration result of the infrared spectrometer, thereby completing the spectral calibration process.

[0129] The present disclosure also discloses an electronic device, Figure 6 The structural block diagram of the electronic device provided by an embodiment of the present disclosure is shown, as Figure 6 shown, the electronic device 600 includes a memory 601 and a processor 602; wherein,

[0130] The memory 601 is used to store one or more computer instructions, and the one or more computer instructions are executed by the processor 602 to implement the above method steps.

[0131] Figure 7 It is a schematic structural diagram of an electronic device suitable for implementing the mid-wave infrared spectral calibration method according to an embodiment of the present disclosure.

[0132] As Figure 7 shown, the electronic device 700 includes a processing unit 701, which can be implemented as a processing unit such as a CPU, GPU, FPGA, NPU, etc. The processing unit 701 can execute various processes in the embodiments of any of the above methods of the present disclosure according to a program stored in the read-only memory (ROM) 702 or a program loaded from the storage section 708 into the random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the electronic device 700 are also stored. The processing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. The input / output (I / O) interface 705 is also connected to the bus 704.

[0133] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, a modem, etc. The communication section 709 performs communication processing via a network such as the Internet. The drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed, so that a computer program read from it can be installed into the storage section 708 as needed.

[0134] Specifically, according to an embodiment of the present disclosure, any of the above methods with reference to the embodiments of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program tangibly contained on a machine-readable medium, and the computer program includes program codes for executing any of the methods in the embodiments of the present disclosure. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709 and / or installed from the removable medium 711.

[0135] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0136] The units or modules involved in the embodiments described in the present disclosure can be implemented in software or in hardware. The described units or modules can also be provided in a processor, and the names of these units or modules do not, in some cases, constitute a limitation on the units or modules themselves.

[0137] As another aspect, the present disclosure also provides a computer-readable storage medium, which can be the computer-readable storage medium included in the device described in the above embodiments; or it can exist separately and be a computer-readable storage medium not assembled into the device. The computer-readable storage medium stores one or more programs, and the one or more programs are used by one or more processors to execute the methods described in the present disclosure.

[0138] The above description is only the preferred embodiments of the present disclosure and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, technical solutions formed by mutually replacing the above features with technical features having similar functions (but not limited to) disclosed in the present disclosure.

Claims

1. A mid-wave infrared spectral calibration method, wherein, Including: Obtain a reference water vapor absorption spectrum in the mid-wave infrared target band; In the mid-wave infrared target band, the atmospheric radiation spectrum is determined by the water vapor absorption spectrum, and the waveform stability degree of the reference water vapor absorption spectrum is higher than a set threshold; Obtain the mid-wave infrared radiation interference signal observed by the infrared spectrometer; Determine the spectral calibration coefficient by optimizing the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum; Use the spectral calibration coefficient to perform spectral calibration of the infrared spectrometer.

2. The method according to claim 1, wherein The method further includes: Calculate the radiation absorption spectrum of gas molecules of a set type in the top of the atmosphere under standard atmospheric conditions in the mid-wave infrared band; the set type of gas molecules includes water vapor molecules and other types of molecules; Based on the radiation absorption spectrum, determine the mid-wave infrared target band by comparing the radiation absorption conditions between the water vapor molecules and other types of molecules.

3. The method according to claim 1 or 2, wherein The method further includes: Obtain different water vapor vertical profiles corresponding to different atmospheric humidity conditions; Calculate the radiation absorption spectrum of water vapor molecules under the different water vapor vertical profile conditions; Determine the part of the radiation absorption spectrum that is in the mid-wave infrared target band and has a waveform stability degree higher than the set threshold as the reference water vapor absorption spectrum.

4. The method according to claim 1 or 2, wherein, Determining the spectral calibration coefficient by optimizing the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum includes: Calculate the spectral calibration coefficient when the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum is minimized through an iterative optimization algorithm.

5. The method according to claim 1 or 2, wherein Calculating the spectral calibration coefficient when the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum is minimized through an iterative optimization algorithm includes: Assign an initial value to the candidate calibration coefficient; Use the candidate calibration coefficient to convert the mid-wave infrared radiation interference signal into an observed spectrum to be optimized; Calculate the candidate deviation when the correlation between the observed spectrum to be optimized and the reference water vapor absorption spectrum is the largest; Update the candidate calibration coefficient, and jump to the step of using the candidate calibration coefficient to convert the mid-wave infrared radiation interference signal into an observed spectrum to be optimized, calculate the candidate deviation corresponding to the updated candidate calibration coefficient until the updated candidate calibration coefficient meets the set conditions; Determine the candidate calibration coefficient corresponding to the smallest candidate deviation as the spectral calibration coefficient.

6. A mid-wave infrared spectral calibration device, wherein, Including: A first acquisition module configured to obtain a reference water vapor absorption spectrum in the mid-wave infrared target band; In the mid-wave infrared target band, the atmospheric radiation spectrum is determined by the water vapor absorption spectrum, and the waveform stability degree of the reference water vapor absorption spectrum is higher than a set threshold; A second acquisition module configured to obtain the mid-wave infrared radiation interference signal observed by the infrared spectrometer; A determination module configured to determine the spectral calibration coefficient by optimizing the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum; A calibration module configured to perform spectral calibration of the infrared spectrometer using the spectral calibration coefficient.

7. The apparatus according to claim 6, wherein, The determination module includes: An iteration sub-module configured to calculate spectral calibration coefficients when the deviation between the observed spectrum corresponding to the mid-wave infrared radiation interference signal and the reference water vapor absorption spectrum is minimized through an iterative optimization algorithm.

8. An electronic device, wherein, It includes a memory, a processor, and a computer program stored on the memory. Among them, the processor executes the computer program to implement the method according to any one of claims 1-5.

9. A computer-readable storage medium having computer instructions stored thereon, wherein, When the computer instruction is executed by the processor, it implements the method according to any one of claims 1-5.

10. A computer program product, comprising computer instructions, wherein, When the computer instruction is executed by the processor, it implements the method according to any one of claims 1-5.

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