CN116539168A - Circular gradient filter spectrum radiometer data processing and calibrating method - Google Patents
Circular gradient filter spectrum radiometer data processing and calibrating method Download PDFInfo
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Abstract
The invention relates to a data processing and scaling method of a spectrum radiometer with a circular gradient filter, which comprises the following steps: receiving detector data sent by the instrument end in a sub-package mode, and splicing to obtain complete detector data; correcting the acquired original data to obtain drift corrected detector data; performing wavelength registration and then performing registration verification to obtain fine registration spectrum data; and comparing the precisely registered spectrum data with spectra of different temperature points recorded in the interval, and obtaining a responsivity function of the target to be detected through linear interpolation. The invention provides a drift correction method based on covariance cross-correlation and cyclic offset correction, and the wavelength after drift correction is re-registered by adopting a gas absorption method on the basis of CVF spectrum calibration, so that the problem of spectrum distortion caused by drift in the CVF rotation process is solved; the invention can solve the nonlinear response problem caused by large measuring temperature range and wide working wave band, and ensures the accuracy of the measuring result of the instrument.
Description
Technical Field
The invention relates to the technical field of spectral radiometer measurement, in particular to a method for processing and calibrating data of a circular gradient filter spectral radiometer.
Background
The spectral radiometer is used to determine the spectral radiation characteristics of a radiation source, by virtue of its spectroscopic capabilities to characterize and distinguish optical signals. The method is widely applied to the fields of industry, scientific research, national defense and the like, such as the fields of material emissivity evaluation, missile flame radiation characteristics, atmosphere remote sensing and the like. Due to the wide application in different fields, a spectral radiometer has become an indispensable measuring instrument.
Currently, spectrum radiometers are largely classified into interference type, dispersion type, filter type, and the like according to the type of light splitting. Each type of radiometer has its own unique characteristics and is therefore suitable for different application scenarios. The interference type and the dispersion type spectrum radiometers are two types which are developed most rapidly at home and abroad, and meanwhile, the data processing research of the two types of radiometers is relatively mature.
The transmission wavelength of the circular graded filter (Circular Variable Filter, CVF) is in linear relation with the angle, and the spectrum radiometer formed by the circular graded filter has the advantages of wide spectrum, large target temperature range and the like, so that the spectrum radiometer of the type is wider in application field. Because different types of radiometers have different characteristics, the processing steps and methods are not identical. Thus, the data processing and calibration of a spectroradiometer generally needs to be developed based on the characteristics of the instrument itself, and the adoption of an effective data processing and calibration method based on a CVF spectroradiometer is a precondition for ensuring the accuracy of measurement results.
The radiation calibration method of the current spectrum radiometer mainly comprises a single-point method, a two-point method, a multi-point method and the like. The single point method is suitable for the conditions of lower instrument resolution and fewer data points. The two-point method is suitable for the conditions of good linearity of the spectrum radiometer and more measured data points. Because the CVF type spectrum radiometer has the characteristics of wide measuring working band and wide target temperature range, the problem of nonlinearity to a certain extent is brought, and the traditional calibration method cannot realize accurate radiocalibration.
Disclosure of Invention
The invention aims to solve the problem that the traditional method cannot calibrate in a wide spectrum and large target temperature range, and provides a circular gradient filter spectrum radiometer data processing and calibrating method which can realize accurate radiometric calibration and ensure the accuracy of an instrument measurement result.
In order to achieve the above purpose, the present invention adopts the following technical scheme: a method for processing and scaling data of a circular graded filter spectrum radiometer, comprising the following sequential steps:
(1) And (3) data splicing: receiving detector data sent by the instrument end in a sub-package mode, and splicing the detector data through analysis and verification of data instructions to obtain complete detector data;
(2) Drift correction: calculating the drift degree of complete detector data by a covariance cross-correlation method, and correcting the acquired original data by cyclic offset correction and the calculated offset value to obtain the detector data after drift correction;
(3) Wavelength re-registration: the method comprises the steps of dividing wavelength registration and registration verification into two parts, carrying out wavelength registration on drift corrected detector data, and carrying out registration verification to obtain fine registration spectrum data;
(4) Radiation calibration: when infrared spectrum measurement is carried out, the spectrum data of the fine registration is compared with spectra of different temperature points recorded in the interval, and the upper limit and the lower limit of a temperature subinterval to which a target to be measured belongs are determined; and obtaining the responsivity function of the target to be measured through linear interpolation according to the responsivity function calculated in the subinterval, substituting the responsivity function into a calibration formula, and completing radiometric calibration.
The step (1) specifically comprises the following steps:
(1a) Analyzing the data packet according to the instruction format, and carrying out validity check on the head and tail check bits of the data packet instruction by using a regular expression registration method;
(1b) Analyzing the frame number and the packet number in the data packet, ensuring the continuity of the data through the frame number and the packet number, comparing the frame number and the packet number in the effective data packet with the frame number and the packet number stored in the history, and triggering different processing mechanisms through different comparison results;
(1c) Analyzing the data in the effective data packet, and updating the data size temporarily stored;
(1d) Judging whether the detector data meet the data integrity requirement or not by comparing the data size of the temporary storage with the data size corresponding to the scanning rate;
(1e) If the data integrity requirement is met, data splicing is carried out, the complete detector data is output, and otherwise, the detector data packet is continuously received.
The step (2) specifically comprises the following steps:
(2a) After the rotating speed of the circular gradient filter is stable, carrying out multiple measurements, and taking the average value of the multiple measurement data as a reference spectral line;
(2b) The covariance between signals is calculated through a covariance cross-correlation method to determine a cross-correlation function, a covariance cross-correlation function is obtained, drift degree is determined through the covariance cross-correlation function, the covariance cross-correlation function value is normalized to obtain a correlation degree matrix, and an offset position with the highest correlation degree in the correlation degree matrix is searched, namely the offset corresponding to detector data is found, and the covariance cross-correlation function is obtainedThe calculation formula of (2) is as follows:
wherein x is n 、y n Respectively measuring signals and reference signals, wherein N and m respectively represent relative displacement of x and y signals, and N is the total offset of the two signals;
normalizing the covariance cross-correlation function:
in the method, in the process of the invention,for normalized covariance cross-correlation function +.>For the unnormalized covariance cross-correlation function, +.>The covariance autocorrelation functions of the x and y signals are respectively.
(2c) And finally correcting the drift data by using a cyclic offset method through the calculated offset to obtain the detector data after the drift correction.
The step (3) specifically comprises the following steps:
(3a) Using the initial position of the stepping motor stored in the history to map the data sampling point and the stepping number of the stepping motor for the detector data after drift correction;
(3b) Using a relation between the stepping number of the stepping motor and the transmission wavelength of the circular gradient filter, and performing wavelength matching on the data to obtain coarse registration data:
wavelength＝k×motorindex+b
wherein, wavelength is a wavelength value, motorindex is the stepping number of the stepping motor, and k and b are calibration coefficients;
(3c) Transmission model by means of MODTRA radiationCalculation of theoretical CO 2 Transmittance curve, CO in coarse registration data 2 Absorption peak and theoretical CO 2 Comparing the absorption peak positions in the transmittance so as to judge the offset degree;
(3d) According to the offset degree, calculating to obtain coarse registration spectrum data; if the comparison result has offset, calculating an actual starting value of the stepping motor through the offset, carrying out iterative updating on the actual value, carrying out wavelength registration again through the new value, and eliminating invalid values of the interval region in the re-registered data, thereby obtaining the fine-registered spectrum data.
The step (4) specifically comprises the following steps:
(4a) Dividing the temperature interval of the measured object into n subintervals, and accurately registering the spectrum data S corresponding to n+1 different blackbody temperatures in the temperature interval range C i (lambda) measurements and recordings are made;
(4b) At the time of measurement, a target spectrum S to be measured m (lambda) finely registered spectral data S corresponding to different blackbody temperatures in a temperature interval C i (lambda) comparing to obtain the upper boundary of the target temperature subinterval to be measuredAnd lower bound->
(4c) Spectral signals of upper and lower boundaries of temperature subinterval to be measuredIntegrating in a measurement wavelength interval, and solving a linear interpolation coefficient alpha of a responsivity function by using a linear ratio, wherein the calculation formula of the linear interpolation coefficient alpha is as follows:
wherein I is m Is a measured spectral signalIntegration of the value over its detector wavelength response interval;the method is to measure the integral of the upper and lower temperature spectrum signal values in the wavelength response interval of the detector;
(4d) Through the corresponding temperature subinterval K found by the target to be detected hot (λ)、K cold (lambda) performing linear interpolation calculation, and solving to obtain a responsivity function K of the target to be measured m (lambda) the linear interpolation formula is as follows:
K m (λ)＝(1-α)K cold (λ)+αK hot (λ)
in the formula, the responsivity function K of the subinterval hot (λ)、K cold And (lambda) is calculated by measuring spectral measurement data of a standard blackbody at the same temperature as a target to be measured, and the responsivity function is calculated according to the following formula:
wherein ε BB Emissivity of a target blackbody; l (lambda, T) BB ) Is lambda wavelength and T temperature of target black body BB Is a radiation brightness of (2); l (lambda, T) Amb ) Is lambda wavelength and T temperature of the internal environment of the instrument Amb Is a radiation brightness of (2); l (lambda, T) IBB ) Is lambda wavelength and T temperature of internal black body IBB Is a radiation brightness of (2); k (lambda) is a responsivity function, S BB (lambda) is the original signal of the measurement target blackbody; the radiance of a blackbody is calculated using the planck formula:
in the formula, a first radiation constant c 1 ＝2πhc 2 A second radiation constant c 2 =hc/K, λ is wavelength, T is temperature;
(4e) The measured spectrum and the calculated responsivity function K m Substituting (lambda) into a scaling formula to complete radiometric scaling, wherein the scaling formula is as follows:
wherein S (lambda) is a measured original signal, and W (lambda) is the observed target radiance related to the wavelength lambda; τ (λ, l) represents the atmospheric transmittance at a distance l between the target and the radiometer; l (lambda, T) air ) At an ambient temperature of T air When the radiation brightness is L (lambda, T) 0 ) For internal reference blackbody temperature T 0 The radiation brightness at that time.
In step (1 b), the different processing mechanisms include:
(1b1) When the frame numbers in the data packets are the same and the packet numbers are continuous, judging that the data packets are continuous data packets, temporarily storing the data of the data packets, and adding 1 to the historically stored packet numbers;
(1b2) When the frame numbers in the data packets are different and the packet number is 0, judging that the transmitted data is a brand new frame of data, temporarily storing the data, and updating the frame number and the packet number;
(1b3) When the frame number and the packet number in the data packet are determined to be other conditions except the step (1 b 1) and the step (1 b 2), the data packet is determined to be a discontinuous invalid data packet, the data packet is discarded, the temporarily stored data is also emptied, the historically stored frame number and the packet number are updated, and the data packet of a new frame is waited.
According to the technical scheme, the beneficial effects of the invention are as follows: firstly, the invention provides a drift correction method based on covariance cross-correlation and cyclic offset correction, and the wavelength after drift correction is re-registered by adopting a gas absorption method on the basis of CVF spectrum calibration, so that the problem of spectrum distortion caused by drift in the CVF rotation process is solved; secondly, the invention provides a responsivity radiometric calibration method based on partition linearity, which can solve the problem of nonlinear response caused by large measuring temperature range and wide working wave band which cannot be solved by the traditional method, and ensures the accuracy of the measuring result of the instrument.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a schematic diagram before drift correction after data splicing in the first embodiment of the present invention;
fig. 3 is a schematic diagram of the drift correction after data splicing in the first embodiment of the present invention;
FIG. 4 shows the spectrum after wavelength re-registration and the CO calculated by MODTRA in accordance with an embodiment of the present invention 2 Comparing absorption peaks in the transmittance;
fig. 5 is a graph showing the comparison between the theoretical value and the actual value of a 600 ℃ blackbody according to the first embodiment of the present invention after radiation calibration.
Detailed Description
As shown in fig. 1, a method for processing and calibrating data of a circular graded filter spectrum radiometer comprises the following steps in sequence:
(1) And (3) data splicing: receiving detector data sent by the instrument end in a sub-package mode, and splicing the detector data through analysis and verification of data instructions to obtain complete detector data;
(2) Drift correction: calculating the drift degree of complete detector data by a covariance cross-correlation method, and correcting the acquired original data by cyclic offset correction and the calculated offset value to obtain the detector data after drift correction;
(3) Wavelength re-registration: the method comprises the steps of dividing wavelength registration and registration verification into two parts, carrying out wavelength registration on drift corrected detector data, and carrying out registration verification to obtain fine registration spectrum data;
(4) Radiation calibration: when infrared spectrum measurement is carried out, the spectrum data of the fine registration is compared with spectra of different temperature points recorded in the interval, and the upper limit and the lower limit of a temperature subinterval to which a target to be measured belongs are determined; and obtaining the responsivity function of the target to be measured through linear interpolation according to the responsivity function calculated in the subinterval, substituting the responsivity function into a calibration formula, and completing radiometric calibration.
The step (1) specifically comprises the following steps:
(1a) Analyzing the data packet according to the instruction format, and carrying out validity check on the head and tail check bits of the data packet instruction by using a regular expression registration method;
(1b) Analyzing the frame number and the packet number in the data packet, ensuring the continuity of the data through the frame number and the packet number, comparing the frame number and the packet number in the effective data packet with the frame number and the packet number stored in the history, and triggering different processing mechanisms through different comparison results;
(1c) Analyzing the data in the effective data packet, and updating the data size temporarily stored;
(1d) Judging whether the detector data meet the data integrity requirement or not by comparing the data size of the temporary storage with the data size corresponding to the scanning rate;
(1e) If the data integrity requirement is met, data splicing is carried out, the complete detector data is output, and otherwise, the detector data packet is continuously received.
In step (1 b), the different processing mechanisms include:
(1b1) When the frame numbers in the data packets are the same and the packet numbers are continuous, judging that the data packets are continuous data packets, temporarily storing the data of the data packets, and adding 1 to the historically stored packet numbers;
(1b2) When the frame numbers in the data packets are different and the packet number is 0, judging that the transmitted data is a brand new frame of data, temporarily storing the data, and updating the frame number and the packet number;
(1b3) When the frame number and the packet number in the data packet are determined to be other conditions except the step (1 b 1) and the step (1 b 2), the data packet is determined to be a discontinuous invalid data packet, the data packet is discarded, the temporarily stored data is also emptied, the historically stored frame number and the packet number are updated, and the data packet of a new frame is waited.
The step (2) specifically comprises the following steps:
(2a) After the rotating speed of the circular gradient filter is stable, carrying out multiple measurements, and taking the average value of the multiple measurement data as a reference spectral line;
(2b) Determining cross-correlations by calculating covariance between signals by covariance cross-correlationCorrelation function, obtain covariance cross-correlation function, confirm the drift degree through covariance cross-correlation function, normalize covariance cross-correlation function value, get the correlation degree matrix, find the highest offset position of correlation degree in the correlation degree matrix, namely is the corresponding offset of the detector data, covariance cross-correlation functionThe calculation formula of (2) is as follows:
wherein x is n 、y n Respectively measuring signals and reference signals, wherein N and m respectively represent relative displacement of x and y signals, and N is the total offset of the two signals;
normalizing the covariance cross-correlation function:
in the method, in the process of the invention,for normalized covariance cross-correlation function +.>For the unnormalized covariance cross-correlation function, +.>The covariance autocorrelation functions of the x and y signals are respectively.
(2c) And finally correcting the drift data by using a cyclic offset method through the calculated offset to obtain the detector data after the drift correction.
The step (3) specifically comprises the following steps:
(3a) Using the initial position of the stepping motor stored in the history to map the data sampling point and the stepping number of the stepping motor for the detector data after drift correction;
(3b) Using a relation between the stepping number of the stepping motor and the transmission wavelength of the circular gradient filter, and performing wavelength matching on the data to obtain coarse registration data:
wavelength＝k×motorindex+b
wherein, wavelength is a wavelength value, motorindex is the stepping number of the stepping motor, and k and b are calibration coefficients;
(3c) Calculation of theoretical CO by means of MODTRA radiation transmission model 2 Transmittance curve, CO in coarse registration data 2 Absorption peak and theoretical CO 2 Comparing the absorption peak positions in the transmittance so as to judge the offset degree;
(3d) According to the offset degree, calculating to obtain coarse registration spectrum data; if the comparison result has offset, calculating an actual starting value of the stepping motor through the offset, carrying out iterative updating on the actual value, carrying out wavelength registration again through the new value, and eliminating invalid values of the interval region in the re-registered data, thereby obtaining the fine-registered spectrum data.
The step (4) specifically comprises the following steps:
(4a) Dividing the temperature interval of the measured object into n subintervals, and accurately registering the spectrum data S corresponding to n+1 different blackbody temperatures in the temperature interval range C i (lambda) measurements and recordings are made;
(4b) At the time of measurement, a target spectrum S to be measured m (lambda) finely registered spectral data S corresponding to different blackbody temperatures in a temperature interval C i (lambda) comparing to obtain the upper boundary of the target temperature subinterval to be measuredAnd lower bound->
(4c) Spectral signals of upper and lower boundaries of temperature subinterval to be measuredIntegrating in a measurement wavelength interval, and solving a linear interpolation coefficient alpha of a responsivity function by using a linear ratio, wherein the calculation formula of the linear interpolation coefficient alpha is as follows:
wherein I is m Is the integration of the measured spectral signal value over its detector wavelength response interval;the method is to measure the integral of the upper and lower temperature spectrum signal values in the wavelength response interval of the detector;
(4d) Through the corresponding temperature subinterval K found by the target to be detected hot (λ)、K cold (lambda) performing linear interpolation calculation, and solving to obtain a responsivity function K of the target to be measured m (lambda) the linear interpolation formula is as follows:
K m (λ)＝(1-α)K cold (λ)+αK hot (λ)
in the formula, the responsivity function K of the subinterval hot (λ)、K cold And (lambda) is calculated by measuring spectral measurement data of a standard blackbody at the same temperature as a target to be measured, and the responsivity function is calculated according to the following formula:
wherein ε BB Emissivity of a target blackbody; l (lambda, T) BB ) Is lambda wavelength and T temperature of target black body BB Is a radiation brightness of (2); l (lambda, T) Amb ) Is lambda wavelength and T temperature of the internal environment of the instrument Amb Is a radiation brightness of (2); l (lambda, T) IBB ) Is lambda wavelength and T temperature of internal black body IBB Is a radiation brightness of (2); k (lambda) is a responsivity function, S BB (lambda) is the original signal of the measurement target blackbody; the radiance of a blackbody is calculated using the planck formula:
in the formula, a first radiation constant c 1 ＝2πhc 2 A second radiation constant c 2 =hc/K, λ is wavelength, T is temperature;
(4e) The measured spectrum and the calculated responsivity function K m Substituting (lambda) into a scaling formula to complete radiometric scaling, wherein the scaling formula is as follows:
wherein S (lambda) is a measured original signal, and W (lambda) is the observed target radiance related to the wavelength lambda; τ (λ, l) represents the atmospheric transmittance at a distance l between the target and the radiometer; l (lambda, T) air ) At an ambient temperature of T air When the radiation brightness is L (lambda, T) 0 ) For internal reference blackbody temperature T 0 The radiation brightness at that time.
Example 1
The spectrum wavelength range of the CVF spectrum radiometer is 1.3-14.3 mu m, the spectrum resolution is less than 2% of the wavelength, and the signal acquisition in the wavelength range is realized by adopting InSb and MCT detectors. The CVF speed was set to 1Hz and 600 ℃ black body measurements were made with a narrow field of view (NFOV) at 7.5mrad horizontal distance 3 m. And comparing the measurement signal obtained by data splicing with a reference signal, wherein the results before and after drift correction are respectively shown in fig. 2 and 3, and the correction error is 1 sampling point by calculating and comparing the actual offset with covariance cross correlation.
Continuing to perform wavelength re-registration on the corrected measurement signal by using the steps, and calculating the obtained spectrum curve and the CO calculated by MODTRA 2 Absorption peaks in transmittance were compared as shown in fig. 4. The average error of the results was reduced from 0.019 μm to 0.004 μm by wavelength re-registration.
Radiometric calibration is performed on the re-registered spectrum, and the calibration result is compared with a theoretical planck function, and the result is shown in fig. 5. And the equivalent temperature of the blackbody in the whole wave band range at different temperatures is reversely pushed by adopting the Planckian theory formula and the least square method, the equivalent temperature is 197.4 ℃, and the calibration precision is better than 98%.
In summary, the invention provides a drift correction method based on covariance cross-correlation and cyclic offset correction, and the wavelength after drift correction is re-registered by adopting a gas absorption method on the basis of CVF spectrum calibration, so that the problem of spectrum distortion caused by drift in the CVF rotation process is solved; the invention provides a responsivity radiometric calibration method based on partition linearity, which can solve the problem of nonlinear response caused by large measurement temperature range and wide working wave band which cannot be solved by the traditional method, and ensures the accuracy of the measurement result of the instrument.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made therein without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. A method for processing and calibrating data of a spectrum radiometer with a circular gradient filter is characterized by comprising the following steps: the method comprises the following steps in sequence:
(1) And (3) data splicing: receiving detector data sent by the instrument end in a sub-package mode, and splicing the detector data through analysis and verification of data instructions to obtain complete detector data;
(2) Drift correction: calculating the drift degree of complete detector data by a covariance cross-correlation method, and correcting the acquired original data by cyclic offset correction and the calculated offset value to obtain the detector data after drift correction;
(3) Wavelength re-registration: the method comprises the steps of dividing wavelength registration and registration verification into two parts, carrying out wavelength registration on drift corrected detector data, and carrying out registration verification to obtain fine registration spectrum data;
(4) Radiation calibration: when infrared spectrum measurement is carried out, the spectrum data of the fine registration is compared with spectra of different temperature points recorded in the interval, and the upper limit and the lower limit of a temperature subinterval to which a target to be measured belongs are determined; and obtaining the responsivity function of the target to be measured through linear interpolation according to the responsivity function calculated in the subinterval, substituting the responsivity function into a calibration formula, and completing radiometric calibration.
2. The method for processing and scaling the data of the circular graded filter spectrum radiometer according to claim 1, wherein the method comprises the following steps: the step (1) specifically comprises the following steps:
(1a) Analyzing the data packet according to the instruction format, and carrying out validity check on the head and tail check bits of the data packet instruction by using a regular expression registration method;
(1b) Analyzing the frame number and the packet number in the data packet, ensuring the continuity of the data through the frame number and the packet number, comparing the frame number and the packet number in the effective data packet with the frame number and the packet number stored in the history, and triggering different processing mechanisms through different comparison results;
(1c) Analyzing the data in the effective data packet, and updating the data size temporarily stored;
(1d) Judging whether the detector data meet the data integrity requirement or not by comparing the data size of the temporary storage with the data size corresponding to the scanning rate;
(1e) If the data integrity requirement is met, data splicing is carried out, the complete detector data is output, and otherwise, the detector data packet is continuously received.
3. The method for processing and scaling the data of the circular graded filter spectrum radiometer according to claim 1, wherein the method comprises the following steps: the step (2) specifically comprises the following steps:
(2a) After the rotating speed of the circular gradient filter is stable, carrying out multiple measurements, and taking the average value of the multiple measurement data as a reference spectral line;
(2b) The covariance between signals is calculated through a covariance cross-correlation method to determine a cross-correlation function, a covariance cross-correlation function is obtained, drift degree is determined through the covariance cross-correlation function, the covariance cross-correlation function value is normalized to obtain a correlation degree matrix, and an offset position with the highest correlation degree in the correlation degree matrix is searched, namely the offset corresponding to detector data is found, and the covariance cross-correlation function is obtainedThe calculation formula of (2) is as follows:
wherein x is n 、y n Respectively measuring signals and reference signals, wherein N and m respectively represent relative displacement of x and y signals, and N is the total offset of the two signals;
normalizing the covariance cross-correlation function:
in the method, in the process of the invention,for normalized covariance cross-correlation function +.>For the unnormalized covariance cross-correlation function, +.>The covariance autocorrelation functions of the x and y signals are respectively.
(2c) And finally correcting the drift data by using a cyclic offset method through the calculated offset to obtain the detector data after the drift correction.
4. The method for processing and scaling the data of the circular graded filter spectrum radiometer according to claim 1, wherein the method comprises the following steps: the step (3) specifically comprises the following steps:
(3a) Using the initial position of the stepping motor stored in the history to map the data sampling point and the stepping number of the stepping motor for the detector data after drift correction;
(3b) Using a relation between the stepping number of the stepping motor and the transmission wavelength of the circular gradient filter, and performing wavelength matching on the data to obtain coarse registration data:
wavelength＝k×motorindex+b
wherein, wavelength is a wavelength value, motorindex is the stepping number of the stepping motor, and k and b are calibration coefficients;
(3c) Calculation of theoretical CO by means of MODTRA radiation transmission model 2 Transmittance curve, CO in coarse registration data 2 Absorption peak and theoretical CO 2 Comparing the absorption peak positions in the transmittance so as to judge the offset degree;
(3d) According to the offset degree, calculating to obtain coarse registration spectrum data; if the comparison result has offset, calculating an actual starting value of the stepping motor through the offset, carrying out iterative updating on the actual value, carrying out wavelength registration again through the new value, and eliminating invalid values of the interval region in the re-registered data, thereby obtaining the fine-registered spectrum data.
5. The method for processing and scaling the data of the circular graded filter spectrum radiometer according to claim 1, wherein the method comprises the following steps: the step (4) specifically comprises the following steps:
(4a) Dividing the temperature interval of the measured object into n subintervals, and accurately registering the spectrum data S corresponding to n+1 different blackbody temperatures in the temperature interval range C i (lambda) measurements and recordings are made;
(4b) At the time of measurement, a target spectrum S to be measured m (lambda) finely registered spectral data S corresponding to different blackbody temperatures in a temperature interval C i (lambda) comparing to obtain the upper boundary of the target temperature subinterval to be measuredAnd lower bound->
(4c) Spectral signals of upper and lower boundaries of temperature subinterval to be measuredIntegrating in a measurement wavelength interval, and solving a linear interpolation coefficient alpha of a responsivity function by using a linear ratio, wherein the calculation formula of the linear interpolation coefficient alpha is as follows:
wherein I is m Is the integration of the measured spectral signal value over its detector wavelength response interval;the method is to measure the integral of the upper and lower temperature spectrum signal values in the wavelength response interval of the detector;
(4d) Through the corresponding temperature subinterval K found by the target to be detected hot (λ)、K cold (lambda) performing linear interpolation calculation, and solving to obtain a responsivity function K of the target to be measured m (lambda) the linear interpolation formula is as follows:
K m (λ)＝(1-α)K cold (λ)+αK hot (λ)
in the formula, the responsivity function K of the subinterval hot (λ)、K cold (lambda) is a spectrum measurement data meter by measuring standard black body at the same temperature as the object to be measuredThe calculation formula of the responsivity function is as follows:
wherein ε BB Emissivity of a target blackbody; l (lambda, T) BB ) Is lambda wavelength and T temperature of target black body BB Is a radiation brightness of (2); l (lambda, T) Amb ) Is lambda wavelength and T temperature of the internal environment of the instrument Amb Is a radiation brightness of (2); l (lambda, T) IBB ) Is lambda wavelength and T temperature of internal black body IBB Is a radiation brightness of (2); k (lambda) is a responsivity function, S BB (lambda) is the original signal of the measurement target blackbody; the radiance of a blackbody is calculated using the planck formula:
in the formula, a first radiation constant c 1 ＝2πhc 2 A second radiation constant c 2 =hc/K, λ is wavelength, T is temperature;
(4e) The measured spectrum and the calculated responsivity function K m Substituting (lambda) into a scaling formula to complete radiometric scaling, wherein the scaling formula is as follows:
wherein S (lambda) is a measured original signal, and W (lambda) is the observed target radiance related to the wavelength lambda; τ (λ, l) represents the atmospheric transmittance at a distance l between the target and the radiometer; l (lambda, T) air ) At an ambient temperature of T air When the radiation brightness is L (lambda, T) 0 ) For internal reference blackbody temperature T 0 The radiation brightness at that time.
6. The method for processing and scaling the data of the circular graded filter spectrum radiometer according to claim 2, wherein the method comprises the following steps: in step (1 b), the different processing mechanisms include:
(1b1) When the frame numbers in the data packets are the same and the packet numbers are continuous, judging that the data packets are continuous data packets, temporarily storing the data of the data packets, and adding 1 to the historically stored packet numbers;
(1b2) When the frame numbers in the data packets are different and the packet number is 0, judging that the transmitted data is a brand new frame of data, temporarily storing the data, and updating the frame number and the packet number;
(1b3) When the frame number and the packet number in the data packet are determined to be other conditions except the step (1 b 1) and the step (1 b 2), the data packet is determined to be a discontinuous invalid data packet, the data packet is discarded, the temporarily stored data is also emptied, the historically stored frame number and the packet number are updated, and the data packet of a new frame is waited.
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