Method and device for testing on-orbit spectrum precision of ultraviolet hyperspectral remote sensor

Abstract

The invention discloses an on-orbit spectrum precision test method and equipment for an ultraviolet hyperspectral remote sensor, and the method comprises the steps: selecting a high-resolution reference solar spectrum higher than the spectral resolution of the ultraviolet hyperspectral remote sensor, and calculating a reference standard solar spectrum according to the high-resolution reference solar spectrum; establishing a reference wavelength library according to the reference standard solar spectrum of the ultraviolet band, and selecting a standard absorption line meeting conditions as a reference wavelength; screening an absorption peak center position of the observation spectrum, finding an absorption peak center closest to the reference wavelength in combination with the reference wavelength library, and constructing a peak searching database of the absorption peak center of the discrete spectrum; and calculating a difference value between the central wavelength calculated according to the peak searching database and the corresponding reference wavelength to obtain the spectrum calibration precision of the ultraviolet hyperspectral remote sensor. According to the method, the precision difference of the spatial dimension can be identified, the distribution of the overall system deviation is quantified, and reliable support is provided for on-orbit precision verification and performance optimization of the ultraviolet hyperspectral remote sensor.

Description

Technical Field

[0001] This invention belongs to the field of satellite space, and more specifically, relates to a method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor. Background Technology

[0002] Ultraviolet (UV) hyperspectral remote sensing technology can accurately detect the characteristic absorption spectra of trace gases in the atmosphere, making it an important means of obtaining atmospheric component concentrations. By precisely detecting depth changes in characteristic gas absorption lines, UV hyperspectral remote sensing enables the quantitative inversion of weak atmospheric component signals. Therefore, the primary requirement for atmospheric component inversion is accurate wavelength; thus, the application of hyperspectral data must first address the issues of spectral verification, validation, and correction.

[0003] Spectral accuracy verification is the process of confirming the accuracy of on-board spectral calibration results and a means of comprehensively understanding and analyzing the spectral characteristics of data. Spectral accuracy verification typically uses a standard wavelength of an independent solar Fraunhofer absorption line to verify the wavelength accuracy of the instrument's observed spectrum. However, verifying hyperspectral observation data in the ultraviolet band presents two challenges. Firstly, because the solar spectrum in the ultraviolet band has very dense absorption lines, the center wavelength position of the reference line is difficult to obtain directly, making the determination of the reference spectral line a challenge. Secondly, the spectra observed by hyperspectral instruments are discrete spectral data after instrument sampling. Due to limitations in the spectral sampling rate, the actual observed spectra exhibit significant non-smoothness characteristics. Therefore, the accuracy of obtaining the center wavelength position of the absorption line based on discrete spectral data is also crucial to the spectral accuracy verification results.

[0004] Therefore, overcoming the technical defects of the existing technology is an urgent problem to be solved in this technical field. Summary of the Invention

[0005] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides a method and device for on-orbit spectral accuracy verification of ultraviolet hyperspectral remote sensors. The purpose is to accurately locate the center of absorption peaks by constructing an adaptive reference spectrum and wavelength library and using a differentiable energy function constructed with a polynomial regression model, thereby solving the problem of inaccurate spectral calibration accuracy verification caused by dense absorption lines, discrete sampling errors, and frequency shift interference in the ultraviolet band.

[0006] To achieve the above objectives, according to one aspect of the present invention, a method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor is provided, the method comprising:

[0007] Select a high-resolution reference solar spectrum that is higher than the spectral resolution of the ultraviolet hyperspectral remote sensor, and calculate the reference standard solar spectrum based on the high-resolution reference solar spectrum;

[0008] A reference wavelength library is established based on the reference standard solar spectrum in the ultraviolet band, and reference absorption lines that meet the conditions are selected as reference wavelengths.

[0009] The absorption peak center positions of the observed spectra are screened, and the absorption peak center closest to the reference wavelength is found in combination with the reference wavelength library to construct a peak-finding database for discrete spectral absorption peak centers.

[0010] The spectral calibration accuracy of the ultraviolet hyperspectral remote sensor is obtained by calculating the difference between the center wavelength calculated based on the peak-finding database and the corresponding reference wavelength.

[0011] As a further improvement and supplement to the above solution, the present invention also includes the following additional technical features.

[0012] Preferably, the resolution of the reference standard solar spectrum is at least twice that of the spectral resolution of the ultraviolet hyperspectral remote sensor, the difference in the number of absorption lines between the reference standard solar spectrum and the observed spectrum is within 10%, and the absorption lines of the reference standard solar spectrum are deeper than those of the observed spectrum.

[0013] Preferably, the method for calculating the reference standard solar spectrum based on the high-resolution reference solar spectrum includes:

[0014] The calculation is performed by combining the spectral response function and the high-resolution reference solar spectrum.

[0015] Preferably, the method for establishing a reference wavelength library based on the reference standard solar spectrum and selecting a reference absorption line that meets the conditions includes:

[0016] Select absorption lines that do not overlap with adjacent absorption lines and have a peak-valley energy difference greater than 30% as reference absorption lines, and select a preset number of reference absorption lines as a reference wavelength library.

[0017] Preferably, the method further includes:

[0018] Before constructing the peak-finding database, the observed spectra of the ultraviolet hyperspectral remote sensor are corrected for Doppler frequency shift.

[0019] Based on the satellite's velocity relative to the sun and the speed of light, the frequency variation of the observed spectrum is calculated, and the wavelength is corrected.

[0020] The center positions of the absorption peaks in the observed spectra were then selected from the corrected observation spectra.

[0021] Preferably, the method for constructing a peak-finding database of discrete spectral absorption peak centers includes:

[0022] Using the absorption peak center closest to the reference wavelength as the center, a preset number of ultraviolet hyperspectral remote sensor sampling points are selected on both sides of the center. The selected sampling points are used to cover a complete absorption peak to establish a peak-finding database.

[0023] Preferably, the method for calculating the center wavelength of the absorption peak includes:

[0024] A polynomial regression model is established, and an objective function is constructed to minimize the deviation between the observed radiation energy and the polynomial fitted value. The polynomial coefficients are solved through optimization iteration.

[0025] Based on the polynomial regression model, a differentiable energy function is constructed. By differentiating the differentiable energy function, the center wavelength of the absorption peak in the observed spectrum is obtained.

[0026] Preferably, the degree of the polynomial regression model is a predetermined number.

[0027] Preferably, the step of screening the center position of the observed absorption peak includes:

[0028] The local minimum method is used to preliminarily identify the center position of the absorption peak and its radiant energy from the observed spectrum.

[0029] According to another aspect of the present invention, a method and apparatus for verifying the on-orbit spectral accuracy of an ultraviolet remote sensor as described in the first aspect are provided, the apparatus comprising:

[0030] One or more processors;

[0031] A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the on-orbit spectral accuracy verification method for ultraviolet hyperspectral remote sensors as described in the first aspect.

[0032] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0033] The present invention provides a method and equipment for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor, which can characterize the on-orbit spectral calibration performance of the OMSN instrument, identify the accuracy differences in spatial dimensions, and quantify the distribution of the overall system deviation, providing reliable support for the on-orbit accuracy verification and performance optimization of ultraviolet hyperspectral remote sensors. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0035] Figure 1 This is a schematic diagram of the on-orbit spectral accuracy verification method for an ultraviolet hyperspectral remote sensor provided in Embodiment 1.

[0036] Figure 2 These are the reference standard solar spectra with spectral resolutions of 0.2 nm and 0.5 nm used in this embodiment.

[0037] Figure 3 This is the reference wavelength position selected in this first embodiment;

[0038] Figure 4 It is the center position of the absorption peak in the observation spectrum near 434.1 nm of the OMSN instrument in this embodiment;

[0039] Figure 5 This describes the spatial dimension distribution characteristics of the spectral calibration accuracy of the OMSN instrument on January 10, 2024, in this embodiment.

[0040] Figure 6 This describes the statistical distribution characteristics of the spectral calibration accuracy of the OMSN instrument on January 10, 2024, in this embodiment.

[0041] Figure 7 This is a schematic diagram of an on-orbit spectral accuracy verification device for an ultraviolet hyperspectral remote sensor provided in Embodiment 2. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0043] Example 1:

[0044] This embodiment addresses the challenge of verifying the spectral accuracy of high-resolution ultraviolet remote sensing instruments in orbit by innovatively proposing a spectral accuracy verification method based on independent characteristic absorption lines. This method fully utilizes characteristic spectral lines with a certain absorption depth obtained through hyperspectral instrument observations. By constructing a differentiable energy function and using extremum search, it accurately identifies the center position of the absorption peak and precisely calculates the wavelength difference between the observed spectrum and the reference spectrum, achieving high-precision verification of the in-orbit observed spectrum. This method can effectively solve the uncertainty in wavelength accuracy verification results caused by peak-finding errors in discrete spectral sampling of grating-based hyperspectral remote sensing instruments.

[0045] This embodiment provides a method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor, such as... Figure 1 As shown, the method includes:

[0046] S101: Select a high-resolution reference solar spectrum with a resolution higher than that of the ultraviolet hyperspectral remote sensor, and calculate the reference standard solar spectrum based on the high-resolution reference solar spectrum.

[0047] For the ultraviolet solar spectrum, absorption lines are dense, and with excessively high spectral resolution, the number of absorption lines will significantly exceed that of the observed spectrum. Therefore, the center wavelength position of the reference standard needs to be calculated by combining the instrument's spectral resolution and spectral response characteristics to obtain a reference standard solar spectrum that is more than twice the instrument's spectral resolution, ensuring that the reference absorption lines have a certain absorption depth and are isolated and non-overlapping. This first embodiment uses the latest international TSIS (Total and Spectral Solar Irradiance Sensor) solar spectrum recommended by the international cross-calibration organization. Its spectral resolution can reach up to 0.001 nm, which is more than an order of magnitude higher than the 0.5 nm spectral resolution of the Ozone Detector-Nadir (OMSN) instrument on the Fengyun-3F satellite.

[0048] To ensure that the number of absorption lines in the reference standard solar spectrum is consistent with that in the observed spectrum, and that the absorption line depth is significantly greater than that in the observed spectrum, facilitating accurate determination of the absorption peak center position, this embodiment uses a solar spectrum with a spectral resolution of 0.2 nm as the reference standard solar spectrum for spectral accuracy verification. This spectral resolution is more than twice that of the OMSN instrument on the Fengyun-3F satellite, meeting the requirement that the number of absorption lines in the reference standard solar spectrum and the observed spectrum are basically consistent, and that the absorption lines are deeper than those in the observed spectrum.

[0049] like Figure 2As shown, this embodiment selects a spectral resolution of 0.2 nm to calculate the reference standard solar spectrum because, under this resolution, the number of absorption lines in the reference standard solar spectrum and the observed spectrum is relatively consistent. If the spectral resolution is too high, more absorption lines will be identified; therefore, the spectral resolution should not be too high. Figure 3 As shown, the absorption line depth at 0.2 nm is significantly higher than that of the observed spectrum, allowing for accurate determination of the absorption peak center position. In this embodiment, 0.2 nm was chosen to match the 0.5 nm spectral resolution of the OMSN instrument. If the instrument's spectral resolution differs significantly from 0.5 nm, such as by more than 40%, then 0.2 nm may not be suitable.

[0050] like Figure 2 As shown, locations with significant absorption (easily identifiable as minimum values) are considered absorption lines (small fluctuations should be excluded). The red and black lines represent the solar spectrum at spectral resolutions of 0.2 nm and 0.5 nm, respectively. It can be seen that a higher spectral resolution (red line 0.2 nm) results in a greater number of identified absorption lines, manifesting as denser fluctuations and deeper absorption. Therefore, excessively high spectral resolution can lead to inconsistencies in the number of absorption lines between the reference standard solar spectrum and the observed spectrum. Figure 2 In the diagram, the horizontal axis represents wavelength and the vertical axis represents radiation intensity. Lines of different colors represent different spectral resolutions. By comparing solar spectra at resolutions of 0.2 and 0.5 nm, the number of absorption lines in the solar spectra at the two resolutions is basically the same (within 10% difference), and the absorption lines overlap. At the same time, the spectral absorption depth of the 0.2 nm resolution is deeper, which is beneficial for the accurate identification of the absorption center position. Therefore, the spectrum calculated using the 0.2 nm spectral resolution can be used as a reference standard solar spectrum.

[0051] Figure 3 The horizontal axis represents wavelength, and the vertical axis represents normalized radiation intensity. Since the absolute value of radiation energy is not emphasized, and the focus is on the position of the absorption peak, normalized energy is used. Figure 3 The spectrum in the image is the reference standard solar spectrum calculated using a spectral resolution of 0.2 nm. The red dots represent the selected absorption peak wavelengths used for spectral accuracy verification. Figure 3 The red dots in the diagram correspond to the center wavelength positions of the reference absorption lines required for spectral accuracy verification; by selecting these wavelength positions, a reference wavelength library for spectral accuracy verification can be established.

[0052] The standard reference spectrum can be calculated as follows:

[0053]

[0054] In the formula, For high-resolution reference solar spectrum, As the instrument's spectral response function, in Example 1, by adjusting the spectral resolution, a spectral resolution condition was selected that satisfies the principles that the number of absorption lines in the reference standard solar spectrum and the observed spectrum are basically the same, and that the absorption lines are deeper than those in the observed spectrum. Finally, the full width at half maximum (FWHM) of the ISRF was set to 0.2 nm. This is the calculated reference standard solar spectrum used for verifying the accuracy of the on-board spectrum. λ is the wavelength.

[0055] S102: Establish a reference wavelength library based on the reference standard solar spectrum in the ultraviolet band, and select the reference absorption line that meets the conditions as the reference wavelength.

[0056] Based on the calculated reference standard solar spectrum, a reference wavelength library for spectral accuracy verification was established by selecting independent, non-overlapping absorption lines with a certain absorption depth. A total of 30 reference absorption lines that meet the requirements were selected.

[0057] W ref =[w1, w2, w3, ..., w p ].

[0058] In this first embodiment, p is 30, and there are a total of 30 reference absorption lines that meet the requirements. A reference wavelength library is established by selecting the center position of the absorption lines.

[0059] It should be noted that the spectral resolution of similar ultraviolet hyperspectral instruments used for atmospheric composition detection, both domestically and internationally, is generally set to around 0.5 nm. Therefore, when establishing a reference wavelength library for such instruments, the reference standard solar spectrum at a resolution of 0.2 nm can be used directly as the benchmark, or the reference wavelength library established in Example 1 can be used directly.

[0060] S103: Screen the absorption peak center positions of the observed spectra, and combine them with the reference wavelength library to find the absorption peak center closest to the reference wavelength, thus constructing a peak-finding database for discrete spectral absorption peak centers.

[0061] Prepare satellite observation data, utilizing solar observations obtained from on-orbit observations by remote sensors. Based on discrete spectral sampling data, locate all possible absorption peak positions C and their corresponding radiant energies in the observed spectrum. Due to the discrete spectral sampling, the center wavelength obtained in this step may not be the true absorption peak center.

[0062] In order to obtain a more accurate location of the absorption peak center, the local minimum method is used for preliminary identification in this first embodiment.

[0063] Based on on-orbit solar observations, the center positions of absorption peaks and their corresponding radiative values ​​are selected from the observed spectra. Due to detector size limitations, most hyperspectral remote sensors using grating-based spectrometers suffer from limitations in the size of the detector array for instrument spectral sampling points. Therefore, the absorption peak center wavelength obtained in this step may not have sufficient absorption depth, and even if it does have a certain absorption depth, it may still deviate from the accurate center wavelength.

[0064] ;

[0065] in, This represents the radiant energy of the absorption peak in the observed spectrum obtained by the local minimum method. This is the matrix of spectral positions corresponding to the absorption peaks. q is the number of spectral samples taken by the instrument, which is 1024 for the OMSN instrument. i is the radiant energy of each spectral sampling point obtained by the instrument.

[0066] In this first embodiment, a constructed differentiable energy function is used to optimize the initially identified absorption peak. This function is constructed based on characteristic spectral lines with a certain absorption depth obtained from hyperspectral instrument observations. It can comprehensively consider the spectral information around the absorption peak, and obtain the optimized absorption peak center position near the initially identified absorption peak through calculation and analysis of the differentiable energy function.

[0067] The optimization effectively reduces peak-finding errors in discrete spectral sampling and improves the accuracy of absorption peak center location identification. The optimized absorption peak center location is then compared with the reference absorption line in the reference wavelength library to accurately calculate the wavelength difference between the observed spectrum and the reference spectrum.

[0068] For polar-orbiting satellites, the flight speed can reach 7 km / s, which can cause a Doppler frequency shift of 0.01 nm for hyperspectral instruments in the ultraviolet band. This is comparable to the 0.01 nm spectral calibration accuracy required by OMSN instruments, therefore its effect must be subtracted. The Doppler frequency shift can be calculated using the following formula:

[0069] ;

[0070] ;

[0071] in, It is the wavelength of the spectrum observed by the instrument. It is the wavelength after Doppler frequency shift correction. It is the frequency of the observed spectrum. It is the frequency of the standard solar spectrum. It is the speed of the satellite relative to the sun along the direction of the instrument's flight, where c represents the speed of light.

[0072] In this first embodiment, the spectral sampling rate of the OMSN is approximately 2-3. Based on the data sampling characteristics, a complete characterization of an absorption line requires approximately 6-7 sampling points. Therefore, with... Centered on the spectral peak, three sampling points are selected on each side. The number of sampling points depends on the instrument's spectral sampling rate. OMSN instruments typically have a sampling rate of 2-3 points per spectral resolution. Under these conditions, a complete characterization of an absorption line generally requires 6-7 sampling points; therefore, three sampling points are selected on each side. This ensures that the number of sampling points covers a complete absorption peak, and a peak-finding database is established based on this. A fourth-order polynomial regression model is then constructed, the objective function E is defined, and the polynomial coefficients are determined. .

[0073] ;

[0074] ;

[0075] Where k=4 indicates that a 4th-order polynomial was used to construct the polynomial regression model, j represents the index number of the polynomial regression model, j=0~4. a is the polynomial coefficient, W is the wavelength. n represents the number of samples in the peak-finding database, and m represents the index number of the samples in the peak-finding database, m=1~n.

[0076] Based on the differentiable energy function established by the polynomial regression model, the wavelength corresponding to the energy minimum can be located by performing first and second derivative analysis on this function, thus determining the accurate absorption peak center wavelength W of the observed spectrum. obs,cen By comparing the accurate absorption peak center of the identified observed spectrum with the wavelength of the corresponding reference absorption line in the reference wavelength library, the spectral accuracy of the absorption position can be obtained.

[0077] like Figure 4 As shown, the blue discrete points represent the observed spectrum. The red curve is obtained after polynomial fitting of the observed spectrum. The minimum value of the red curve, marked by a red asterisk, is the center of the absorption peak, approximately 434.1 nm. The method of determining the absorption peak center wavelength by searching for the minimum value using a polynomial regression model solves the problem of absorption peak center positioning error caused by discrete sampling.

[0078] The high degree of fit between the discrete points of the observed spectrum and the fitted curve in the figure indicates that the fitted model can effectively characterize the spectral morphology of the absorption peaks, providing reliable basic data for subsequent comparison with the reference wavelength library and calculation of spectral calibration accuracy.

[0079] S104: Calculate the difference between the wavelength in the peak-finding database and the corresponding reference wavelength to obtain the spectral calibration accuracy of the ultraviolet hyperspectral remote sensor.

[0080] In this first embodiment, the reference wavelength library W is used.ref The wavelengths of the center wavelengths of the absorption peaks corresponding to all samples are compared with the corresponding reference absorption line wavelengths in the reference spectrum. The wavelength deviation of the instrument's on-orbit observation spectrum is calculated to evaluate the spectral calibration accuracy. The calculation method is as follows: - .

[0081] The wavelength difference for each absorption peak is obtained by subtracting the center wavelength of the optimized absorption peak in the peak-finding database from the wavelength of the corresponding reference line in the reference wavelength library. Statistical analysis is then performed on these wavelength differences, such as calculating the mean and standard deviation, to evaluate the spectral accuracy of the observed spectra.

[0082] If the average wavelength difference is close to zero and the standard deviation is small, it indicates that the wavelength accuracy of the observed spectrum is high and the spectral precision meets the requirements. Conversely, if the average value deviates significantly from zero or the standard deviation is large, it indicates that there is a certain wavelength deviation in the observed spectrum, requiring further calibration and adjustment of the remote sensor. This method enables high-precision verification of on-orbit observed spectra, providing more accurate data support for applications such as atmospheric composition inversion.

[0083] Existing high-resolution reference solar spectra have poor compatibility with the observed spectra of ultraviolet hyperspectral remote sensors, exhibiting problems such as excessively high spectral resolution and significant differences in the number of absorption lines, thus failing to provide a direct and accurate reference for verifying spectral accuracy. In this first embodiment, the resolution of the reference standard solar spectrum is at least twice that of the ultraviolet hyperspectral remote sensor, the difference in the number of absorption lines between the reference standard solar spectrum and the observed spectrum is within 10%, and the absorption lines of the reference standard solar spectrum are deeper than those of the observed spectrum.

[0084] In order to match the calculated reference standard solar spectrum with the actual observation scenario of the instrument, considering the spectral response characteristics and on-orbit observation wavelength range of the ultraviolet hyperspectral remote sensor, this embodiment one includes the following method for calculating the reference standard solar spectrum based on the high-resolution reference solar spectrum:

[0085] The calculation is performed by combining the spectral response function and the high-resolution reference solar spectrum.

[0086] To clarify the unified criteria for selecting reference absorption lines in the reference wavelength library and avoid issues such as overlap with adjacent absorption lines or insufficient absorption depth affecting spectral accuracy verification results, this embodiment of the method for establishing a reference wavelength library based on the aforementioned reference standard solar spectrum and selecting suitable reference absorption lines includes:

[0087] Select absorption lines that do not overlap with adjacent absorption lines and have a peak-valley energy difference greater than 30% as reference absorption lines, and select a preset number of reference absorption lines as a reference wavelength library.

[0088] The relative motion between the satellite and the sun produces a Doppler frequency shift equivalent to the spectral calibration accuracy. Failure to subtract this shift will result in deviations in the observed spectral wavelengths, affecting the accuracy of spectral precision verification. In this first embodiment, the method further includes:

[0089] Before constructing the peak-finding database, the observed spectra of the ultraviolet hyperspectral remote sensor are corrected for Doppler frequency shift.

[0090] Based on the satellite's velocity relative to the sun and the speed of light, the frequency variation of the observed spectrum is calculated, and the wavelength is corrected.

[0091] The center positions of the absorption peaks in the observed spectra were then selected from the corrected observation spectra.

[0092] To fully characterize the spectral features of absorption peaks, a reasonable number and distribution of sampling points are selected for the peak-finding database to avoid deviations in the location of absorption peak centers, which could affect the spectral accuracy verification results. In this first embodiment, the method for constructing a peak-finding database for discrete spectral absorption peak centers includes:

[0093] Using the absorption peak center closest to the reference wavelength as the center, a preset number of ultraviolet hyperspectral remote sensor sampling points are selected on both sides of the center. The selected sampling points are used to cover a complete absorption peak to establish a peak-finding database.

[0094] To address the errors caused by directly extracting the absorption peak center from discrete spectral sampling data, this embodiment of the method for calculating the absorption peak center wavelength includes:

[0095] A polynomial regression model is established, and an objective function is constructed to minimize the deviation between the observed radiation energy and the polynomial fitted value. The polynomial coefficients are solved through optimization iteration.

[0096] Based on the polynomial regression model, a differentiable energy function is constructed. By differentiating and analyzing the differentiable energy function, the accurate absorption peak center wavelength of the observed spectrum is obtained.

[0097] By optimizing the location of the absorption peak center through scientific model fitting and derivative calculation, the wavelength of the absorption peak center can be calculated accurately.

[0098] Currently, there is no clear basis for selecting the degree of the polynomial regression model. Too low a degree leads to inaccurate fitting of the absorption peak, while too high a degree causes overfitting; neither can accurately calculate the center wavelength of the absorption peak, affecting the reliability of spectral accuracy verification. In this first embodiment, the degree of the polynomial regression model is a predetermined number.

[0099] To address the lack of a unified and reliable method for selecting the center positions of observed absorption peaks, which leads to low accuracy of candidate absorption peak centers and the presence of false peaks, missed peaks, or positioning deviations, thus creating potential errors for subsequent peak-finding database construction and absorption peak center calculation, this embodiment one includes the following steps for selecting the center positions of observed absorption peaks:

[0100] The local minimum method is used to preliminarily identify the center position of the absorption peak and its radiant energy from the observed spectrum.

[0101] The OMSN instrument observes 238 spatial pixels in a single measurement, and each spatial pixel produces a complete spectrum for spectral accuracy verification. For example... Figure 5 As shown, the 238 spatial pixels on the horizontal axis correspond to different spectral precisions (each pixel corresponds to the average of 30 reference standards), and the vertical axis represents wavelength deviation. Spectral precision exhibits a spatial pixel dependency; the wavelength deviation of the first 62 spatial pixels fluctuates slightly more, while the precision of pixels 63-238 is more stable. This demonstrates that the testing method in Example 1 can identify differences in spectral calibration consistency across different spatial regions of the instrument.

[0102] like Figure 6 As shown, using 238 spatial pixels, each with 30 reference wavelengths as independent samples, the spectral calibration accuracy of each absorption line center can be accurately verified. Statistical results show that all samples have positive deviations, ranging from 0.0043 nm to 0.0137 nm, with the most frequent deviation being approximately 0.0075 nm. This indicates that the instrument exhibits a systematic wavelength drift in the long-wavelength direction, but the magnitude of the deviation is very small, and the overall spectral calibration accuracy is at a high level. This verifies the effectiveness of the verification method in Example 1 in quantifying systematic deviations and assessing the magnitude of accuracy.

[0103] In summary, the verification method in this embodiment can characterize the on-orbit spectral calibration performance of the OMSN instrument, identify the accuracy differences in spatial dimensions, and quantify the distribution of the overall system deviation, providing reliable support for the on-orbit accuracy verification and performance optimization of ultraviolet hyperspectral remote sensors.

[0104] Example 2:

[0105] This second embodiment provides an on-orbit spectral accuracy verification device for an ultraviolet hyperspectral remote sensor, such as... Figure 7 As shown, the device includes:

[0106] One or more processors;

[0107] A storage device for storing one or more programs, which, when executed by one or more processors, enable the one or more processors to implement the on-orbit spectral accuracy verification method for ultraviolet hyperspectral remote sensors as described in Embodiment 1.

[0108] Figure 7 This is a schematic diagram of the on-orbit spectral accuracy testing equipment for an ultraviolet hyperspectral remote sensor provided in Embodiment 2 of the present invention. Figure 7 The ultraviolet hyperspectral remote sensor on-orbit spectral accuracy verification equipment shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0109] like Figure 7 As shown, the on-orbit spectral accuracy verification equipment for ultraviolet hyperspectral remote sensors is presented in the form of a general-purpose device. The components of the on-orbit spectral accuracy verification equipment for ultraviolet hyperspectral remote sensors may include, but are not limited to: one or more processors or processing units, memory, and buses connecting different system components (including memory and processing units).

[0110] A bus refers to one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0111] On-orbit spectral accuracy verification equipment for ultraviolet hyperspectral remote sensors typically includes a variety of computer-readable media. These media can be any available media that can be accessed by the on-orbit spectral accuracy verification equipment for ultraviolet hyperspectral remote sensors, including volatile and non-volatile media, and portable and non-portable media.

[0112] The memory may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory. The on-orbit spectral accuracy verification equipment for the ultraviolet hyperspectral remote sensor may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system may be used to read and write non-removable, non-volatile magnetic media (…). Figure 7 Not shown; usually referred to as a "hard drive"). Although Figure 7 As not shown, disk drives for reading and writing to removable non-volatile disks (e.g., "floppy disks") and optical disc drives for reading and writing to removable non-volatile optical discs (e.g., CD-ROMs, DVD-ROMs, or other optical media) may be provided. In these cases, each drive may be connected to a bus via one or more data media interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0113] A program / utility having a set (at least one) of program modules can be stored, for example, in memory. Such program modules include, but are not limited to, an operating system, one or more applications, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules typically perform the functions and / or methods described in the embodiments of this invention.

[0114] The on-orbit spectral accuracy verification device for ultraviolet hyperspectral remote sensors can also communicate with one or more external devices (e.g., keyboards, pointing devices, displays, etc.), one or more devices that allow users to interact with the device, and / or any device that enables the device to communicate with one or more other devices (e.g., network cards, modems, etc.). This communication can be performed via input / output (I / O) interfaces. Furthermore, the device can also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter. Figure 7 As shown, the network adapter communicates with other modules of the on-orbit spectral accuracy verification equipment for the ultraviolet hyperspectral remote sensor via a bus. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the on-orbit spectral accuracy verification equipment for the ultraviolet hyperspectral remote sensor, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0115] The processing unit executes various functional applications and data processing by running programs stored in the memory, such as implementing the on-orbit spectral accuracy verification method for ultraviolet hyperspectral remote sensors provided in any embodiment of the present invention. Specifically: a high-resolution reference solar spectrum higher than the spectral resolution of the ultraviolet hyperspectral remote sensor is selected; a reference standard solar spectrum is calculated based on the high-resolution reference solar spectrum; a reference wavelength library is established based on the reference standard solar spectrum in the ultraviolet band; a reference absorption line that meets the conditions is selected as the reference wavelength; the absorption peak center positions of the observed spectra are screened, and the absorption peak center closest to the reference wavelength is found in combination with the reference wavelength library, constructing a peak-finding database for discrete spectral absorption peak centers; the difference between the center wavelength calculated based on the peak-finding database and the corresponding reference wavelength is calculated to obtain the spectral calibration accuracy of the ultraviolet hyperspectral remote sensor.

[0116] It is worth noting that the information interaction and execution process between the modules and units in the above-mentioned device and system are based on the same concept as the processing method embodiment of the present invention. For details, please refer to the description in the method embodiment of the present invention, and will not be repeated here.

[0117] Those skilled in the art will understand that all or part of the steps in the various methods of the embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor, characterized in that, The method includes: Select a high-resolution reference solar spectrum that is higher than the spectral resolution of the ultraviolet hyperspectral remote sensor, and calculate the reference standard solar spectrum based on the high-resolution reference solar spectrum; A reference wavelength library is established based on the reference standard solar spectrum in the ultraviolet band, and reference absorption lines that meet the conditions are selected as reference wavelengths. The absorption peak center positions of the observed spectra are screened, and the absorption peak center closest to the reference wavelength is found in combination with the reference wavelength library to construct a peak-finding database for discrete spectral absorption peak centers. The spectral calibration accuracy of the ultraviolet hyperspectral remote sensor is obtained by calculating the difference between the center wavelength calculated based on the peak-finding database and the corresponding reference wavelength.

2. The method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor as described in claim 1, characterized in that, The spectral resolution of the reference standard solar spectrum is at least twice that of the spectral resolution of the ultraviolet hyperspectral remote sensor, the difference in the number of absorption lines between the reference standard solar spectrum and the observed spectrum is within 10%, and the absorption lines of the reference standard solar spectrum are deeper than those of the observed spectrum.

3. The method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor as described in claim 1, characterized in that, The method for calculating the reference standard solar spectrum based on the high-resolution reference solar spectrum includes: The calculation is performed by combining the spectral response function and the high-resolution reference solar spectrum.

4. The method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor as described in claim 1, characterized in that, The method for establishing a reference wavelength library based on the reference standard solar spectrum and selecting reference absorption lines that meet the conditions includes: Select absorption lines that do not overlap with adjacent absorption lines and have a peak-valley energy difference greater than 30% as reference absorption lines, and select a preset number of reference absorption lines as a reference wavelength library.

5. The method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor as described in claim 1, characterized in that, The method further includes: Before constructing the peak-finding database, the observed spectra of the ultraviolet hyperspectral remote sensor are corrected for Doppler frequency shift. Based on the satellite's velocity relative to the sun and the speed of light, the frequency variation of the observed spectrum is calculated, and the wavelength is corrected. The center positions of the absorption peaks in the observed spectra were then selected from the corrected observation spectra.

6. The method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor as described in claim 1, characterized in that, The method for constructing a peak-finding database for discrete spectral absorption peak centers includes: Using the absorption peak center closest to the reference wavelength as the center, a preset number of ultraviolet hyperspectral remote sensor sampling points are selected on both sides of the center. The selected sampling points are used to cover a complete absorption peak to establish a peak-finding database.

7. The method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor as described in claim 6, characterized in that, The method for calculating the center wavelength of the absorption peak includes: A polynomial regression model is established, and an objective function is constructed to minimize the deviation between the observed radiation energy and the polynomial fitted value. The polynomial coefficients are solved through optimization iteration. Based on the polynomial regression model, a differentiable energy function is constructed. By differentiating the differentiable energy function, the center wavelength of the absorption peak in the observed spectrum is obtained.

8. The method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor as described in claim 7, characterized in that, The degree of the polynomial regression model is a predetermined number.

9. The method for verifying the on-orbit spectral accuracy of an ultraviolet hyperspectral remote sensor as described in claim 1, characterized in that, The step of screening and observing the center position of the absorption peak includes: The local minimum method is used to preliminarily identify the center position of the absorption peak and its radiant energy from the observed spectrum.

10. An on-orbit spectral accuracy verification device for an ultraviolet hyperspectral remote sensor, characterized in that, The equipment includes: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the on-orbit spectral accuracy verification method for ultraviolet hyperspectral remote sensors as described in any one of claims 1-9.

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