CN117705748A - Fractional rotation angle calibration method for noise equivalent radiance of infrared spectrometer - Google Patents
Fractional rotation angle calibration method for noise equivalent radiance of infrared spectrometer Download PDFInfo
- Publication number
- CN117705748A CN117705748A CN202311872363.XA CN202311872363A CN117705748A CN 117705748 A CN117705748 A CN 117705748A CN 202311872363 A CN202311872363 A CN 202311872363A CN 117705748 A CN117705748 A CN 117705748A
- Authority
- CN
- China
- Prior art keywords
- blackbody temperature
- rotation angle
- temperature point
- blackbody
- noise
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 53
- 238000001228 spectrum Methods 0.000 claims abstract description 104
- 230000004044 response Effects 0.000 claims abstract description 50
- 238000012545 processing Methods 0.000 claims abstract description 8
- 230000007613 environmental effect Effects 0.000 claims abstract description 7
- 230000005855 radiation Effects 0.000 claims description 44
- 230000003595 spectral effect Effects 0.000 claims description 35
- 230000009466 transformation Effects 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000004590 computer program Methods 0.000 claims description 7
- 238000001914 filtration Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 abstract description 17
- 238000010586 diagram Methods 0.000 description 36
- 230000036760 body temperature Effects 0.000 description 17
- 238000000354 decomposition reaction Methods 0.000 description 16
- 239000007789 gas Substances 0.000 description 7
- 230000003287 optical effect Effects 0.000 description 7
- 238000004458 analytical method Methods 0.000 description 6
- 238000012360 testing method Methods 0.000 description 6
- 238000011088 calibration curve Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- 238000002474 experimental method Methods 0.000 description 3
- 238000002329 infrared spectrum Methods 0.000 description 3
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000005316 response function Methods 0.000 description 2
- 230000005457 Black-body radiation Effects 0.000 description 1
- 238000004566 IR spectroscopy Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 229910002092 carbon dioxide Inorganic materials 0.000 description 1
- 239000001569 carbon dioxide Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000005086 pumping Methods 0.000 description 1
- 238000007670 refining Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Radiation Pyrometers (AREA)
Abstract
The invention provides a fractional rotation angle calibration method of noise equivalent radiance of an infrared spectrometer, belonging to the field of photoelectric information acquisition and processing, comprising the following steps: acquiring spectrum data corresponding to a plurality of blackbody temperature points respectively at a target environmental temperature; acquiring a calibration data set corresponding to each rotation angle based on the spectrum data corresponding to each of the plurality of blackbody temperature points; acquiring a noise spectrum DN value of the rotary interference infrared spectrometer based on the spectrum data corresponding to each blackbody temperature point; calculating the system response gain of one or more first blackbody temperature points under each rotation angle based on the calibration data set corresponding to each rotation angle; and aiming at each rotation angle, calibrating the noise equivalent radiance corresponding to each first blackbody temperature point under each rotation angle based on the noise spectrum DN value and the system response gain corresponding to each first blackbody temperature point. By scaling the noise equivalent radiance by a partial rotation angle, the measurement data can be corrected more accurately.
Description
Technical Field
The invention belongs to the field of photoelectric information acquisition and processing, and particularly relates to a fractional rotation angle calibration method of noise equivalent radiance of an infrared spectrometer.
Background
An infrared Fourier spectrometer is a spectrum information acquisition and analysis device based on interferometric measurement. Compared with the traditional dispersion type infrared spectrum instrument, the infrared spectrum instrument has the advantages of high spectrum identification precision, high detection signal-to-noise ratio and the like, and is widely applied to the fields of environmental gas monitoring, fire protection security, explosive detection and the like. When the Fourier spectrometer is used for telemetering the target, the infrared radiation of the target can be absorbed, scattered and the like after passing through the atmosphere, and the environmental background signal and the radiation signal of the instrument can be loaded in a weak target signal, so that the accuracy of extracting and identifying the characteristics of the target signal is obviously affected. Aiming at the detection of more distant and weaker targets, reducing the equivalent noise of the instrument itself or accurately characterizing the equivalent noise of the instrument and correcting the equivalent noise, thereby improving the detection signal-to-noise ratio is the most main technical approach at present. Noise equivalent radiance (Noise Equivalent Spectral Radiance, NESR) is an important parameter of this type of instrument, which measures the limit level of capability of a fourier spectrometer to detect a target signal. Accurate calibration NESR is helpful for improving the research and development level of equipment and the quantitative application level of telemetry data, and the available value of the measurement result is determined.
Fig. 1 is a schematic diagram of a rotating interference optical structure provided in the prior art, and a spectrum detector may use a high-speed fourier infrared spectrometer (a rotating interference infrared spectrometer), where the spectrometer uses a rotating interferometer (whose optical structure is shown in fig. 1) and includes a rotating refractive mirror R inside.
Incident light enters from a field diaphragm FS, is projected to a beam splitter (spectroscope) BS (semi-reflection and semi-transmission) after passing through a correction lens LC, and half of the light is reflected to a reflecting mirror M at the top, passes through a rotary refractive mirror R, is finally reflected by a reflecting mirror ME at the lower part, and is reflected to the spectroscope BS along the original path;
the other half of the light rays incident to the spectroscope BS are reflected by the reflecting mirror M at the bottom, transmitted by the rotary refracting mirror R, reflected by the reflecting mirror ME above and reflected to the spectroscope BS along the original path;
the two reflected light rays are recombined (interfered) at the beam splitter BS and then focused by the focusing lens LF to the spectral detector D.
The interference light is converted into a voltage signal by the detector, and different optical path differences (Optical Path Difference, OPD) are formed along with the rotation of the rotating refractor R. One rotation produces a total of 4 points with an optical path difference of 0, so a total of 4 frames of interference spectra are acquired per rotation.
Conventional fourier infrared spectrometers typically employ one or more linear calibration methods in performing device noise calibration, which methods provide for a significant degree of instrument accuracy. However, in practical application, the rotation property of the fourier infrared spectrometer makes the spectrum data obtained at different angles have certain difference, and the problem still exists in the system error possibly caused at a specific angle, so that the accuracy of the measurement result is reduced, and the error of the existing calibration method is larger.
Disclosure of Invention
The invention provides a method for calibrating a sub-rotation angle of noise equivalent radiance of an infrared spectrometer, which is used for solving the defect that in the prior art, the accuracy of a measurement result is reduced due to a system error under a specific angle, realizing the calibration of the sub-rotation angle, and selecting a corresponding calibration curve according to the current measurement angle so as to more accurately correct measurement data.
In order to achieve the above object, in a first aspect, the present invention provides a method for calibrating a fractional rotation angle of noise equivalent radiance of an infrared spectrometer, comprising:
acquiring spectra of blackbody at different temperatures by using a rotary interference infrared spectrometer at a target environmental temperature, and acquiring spectral data corresponding to a plurality of blackbody temperature points respectively;
Classifying the spectrum data according to a plurality of rotation angles of the rotation interference infrared spectrometer based on the spectrum data respectively corresponding to a plurality of blackbody temperature points, and obtaining calibration data sets corresponding to the rotation angles, wherein the calibration data sets comprise the spectrum data respectively corresponding to the blackbody temperature points under the corresponding rotation angles;
acquiring a noise spectrum digital signal value DN value of the rotary interference infrared spectrometer through wavelet transformation based on spectrum data corresponding to each blackbody temperature point;
calculating system response gains corresponding to one or more first blackbody temperature points under each rotation angle based on the calibration data set corresponding to each rotation angle;
and aiming at each rotation angle, calibrating the noise equivalent radiance corresponding to each first blackbody temperature point under each rotation angle based on a noise spectrum DN value and the system response gain corresponding to each first blackbody temperature point.
Optionally, the calculating, based on the calibration data set corresponding to each rotation angle, a system response gain corresponding to one or more first blackbody temperature points under each rotation angle includes:
Based on a calibration data set corresponding to a target rotation angle, extracting spectrum data corresponding to a second blackbody temperature point and spectrum data corresponding to a third blackbody temperature point under the target rotation angle, wherein the target rotation angle is any one angle of the plurality of rotation angles, the second blackbody temperature point is lower than the first blackbody temperature point, and the third blackbody temperature point is higher than the first blackbody temperature point;
and determining the system response gain corresponding to the first blackbody temperature point under the target rotation angle through two-point linear calibration based on the spectrum data corresponding to the second blackbody temperature point and the spectrum data corresponding to the third blackbody temperature point under the target rotation angle.
Optionally, the determining the system response gain corresponding to the first blackbody temperature point at the target rotation angle based on the spectral data corresponding to the second blackbody temperature point and the spectral data corresponding to the third blackbody temperature point at the target rotation angle through two-point linear scaling specifically includes calculating the system response gain according to the following formula:
wherein Gain (λ) represents the system response Gain, DN L (lambda) represents the spectral data corresponding to the second blackbody temperature point, S L (lambda) represents the preset blackbody theoretical radiance, DN, corresponding to the second blackbody temperature point H (lambda) represents spectral data corresponding to a third blackbody temperature point, S H And (lambda) represents the preset blackbody theoretical radiance corresponding to the third blackbody temperature point, and lambda represents the wavelength.
Optionally, after extracting the spectral data corresponding to the second blackbody temperature point and the spectral data corresponding to the third blackbody temperature point at the target rotation angle based on the calibration data set corresponding to the target rotation angle, the method further includes:
determining a radiation bias corresponding to a first blackbody temperature point under the target rotation angle through two-point linear calibration based on the spectrum data corresponding to a second blackbody temperature point and the spectrum data corresponding to a third blackbody temperature point under the target rotation angle;
and carrying out Gaussian filtering processing based on the radiation bias corresponding to the first blackbody temperature point under the target rotation angle, and obtaining the filtered radiation bias corresponding to the first blackbody temperature point under the target rotation angle.
Optionally, the determining, based on the spectral data corresponding to the second blackbody temperature point and the spectral data corresponding to the third blackbody temperature point at the target rotation angle, the radiation bias corresponding to the first blackbody temperature point at the target rotation angle by two-point linear scaling specifically includes calculating the radiation bias by the following formula:
Wherein offset (λ) represents the radiation bias, DN L (lambda) represents the spectral data corresponding to the second blackbody temperature point, S L (lambda) represents the preset blackbody theoretical radiance, DN, corresponding to the second blackbody temperature point H (lambda) represents the thirdSpectral data corresponding to blackbody temperature points, S H And (lambda) represents the preset blackbody theoretical radiance corresponding to the third blackbody temperature point, and lambda represents the wavelength.
Optionally, for each rotation angle, based on a noise spectrum DN value and a system response gain corresponding to each first blackbody temperature point, scaling a noise equivalent radiance corresponding to each first blackbody temperature point at each rotation angle specifically includes scaling the noise equivalent radiance by the following formula:
wherein S is input_noise (lambda) represents noise equivalent radiance, DN noise (lambda) represents the DN value at the noise wavelength lambda and k (lambda) represents the system response gain at the wavelength lambda.
Optionally, the bands covered by the spectrum data corresponding to the blackbody temperature points respectively include: near infrared band, short wave band, medium wave band and long wave band, correspondingly, the equivalent radiance of noise that first blackbody temperature point corresponds includes: the noise equivalent radiance of the near infrared band, the noise equivalent radiance of the short wave band, the noise equivalent radiance of the medium wave band and the noise equivalent radiance of the long wave band.
In a second aspect, the present invention further provides a device for calibrating a sub-rotation angle of noise equivalent radiance of an infrared spectrometer, including:
the acquisition module is used for acquiring spectra of blackbody at different temperatures through the rotary interference infrared spectrometer under the target environment temperature to acquire spectral data corresponding to a plurality of blackbody temperature points respectively;
the calibration data set acquisition module is used for classifying the spectrum data according to a plurality of rotation angles of the rotation interference infrared spectrometer based on the spectrum data respectively corresponding to a plurality of blackbody temperature points to acquire calibration data sets corresponding to the rotation angles, wherein the calibration data sets comprise the spectrum data respectively corresponding to a plurality of blackbody temperature points under the corresponding rotation angles;
the wavelet transformation module is used for acquiring a noise spectrum digital signal value DN value of the rotary interference infrared spectrometer through wavelet transformation based on the spectrum data respectively corresponding to each blackbody temperature point;
the system response gain calculation module is used for calculating system response gains corresponding to one or more first blackbody temperature points under each rotation angle based on the calibration data set corresponding to each rotation angle;
the calibration module is used for calibrating the noise equivalent radiance corresponding to each first blackbody temperature point under each rotation angle based on the noise spectrum DN value and the system response gain corresponding to each first blackbody temperature point.
In a third aspect, the present invention provides an electronic device comprising: at least one memory for storing a program; at least one processor for executing a memory-stored program, which when executed is adapted to carry out the method described in the first aspect or any one of the possible implementations of the first aspect.
In a fourth aspect, the present invention provides a computer readable storage medium storing a computer program which, when run on a processor, causes the processor to perform the method described in the first aspect or any one of the possible implementations of the first aspect.
It will be appreciated that the advantages of the second to fourth aspects may be found in the relevant description of the first aspect and are not repeated here.
In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:
the spectrum data are classified through the sub-rotation angles, the calibration data set corresponding to each rotation angle can be obtained, the system response gain can be calculated according to the rotation angles, the system response gain corresponding to one or more blackbody temperature points under each rotation angle can be determined, the noise spectrum DN value obtained through wavelet transformation is combined, the noise equivalent radiance corresponding to the blackbody temperature points can be calibrated according to the rotation angles, the integral linear relation of the spectrometer is considered, the similarity under different angles is fully utilized, and in actual measurement, the corresponding calibration curve can be selected according to the current measurement angle, and therefore the measurement data can be corrected more accurately.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a prior art rotating interference optical structure;
FIG. 2 is a flow chart of a method for calibrating the fractional rotation angle of the noise equivalent radiance of an infrared spectrometer according to the present invention;
FIG. 3 is a schematic diagram of a device noise signal after wavelet decomposition provided by the present invention;
FIG. 4 is a schematic diagram of near infrared band noise curve after wavelet decomposition provided by the present invention;
FIG. 5 is a schematic diagram of a short wave band noise curve after wavelet decomposition provided by the invention;
FIG. 6 is a graph showing the noise curves of the intermediate wave bands after wavelet decomposition provided by the invention;
FIG. 7 is a schematic diagram of a wavelet decomposed long-wave band noise curve provided by the present invention;
FIG. 8 is a schematic diagram of a system gain curve calculated from the blackbody temperature of 0℃and 50℃at a first angle provided by the present invention;
FIG. 9 is a graph showing a first angular gain sub-band curve provided by the present invention;
FIG. 10 is a second exemplary plot of a first angular gain sub-band provided by the present invention;
FIG. 11 is a third exemplary plot of a first angular gain sub-band provided by the present invention;
FIG. 12 is a fourth schematic diagram of a first angular gain sub-band plot provided by the present invention;
FIG. 13 is a schematic diagram of the calculated system radiation bias for black body temperatures of 0℃and 50℃at a first angle provided by the present invention;
FIG. 14 is a schematic diagram of a system gain curve calculated from black body temperatures of 0℃and 50℃at a second angle according to the present invention;
FIG. 15 is a schematic diagram of the calculated system radiation bias for black body temperatures of 0℃and 50℃at a second angle provided by the present invention;
FIG. 16 is a schematic diagram of a system gain curve calculated from black body temperatures of 0℃and 50℃at a third angle according to the present invention;
FIG. 17 is a schematic diagram of the calculated system radiation bias for black body temperatures of 0℃and 50℃at a third angle provided by the present invention;
FIG. 18 is a graph showing the calculated system gain curve for black body temperatures of 0℃and 50℃at a fourth angle provided by the present invention;
FIG. 19 is a schematic diagram of the calculated system radiation bias for black body temperatures of 0℃and 50℃at a fourth angle provided by the present invention;
FIG. 20 is a schematic view of a noise equivalent amplitude luminance curve at a first angle according to the present invention;
FIG. 21 is a graph showing the equivalent amplitude of the near infrared noise at a first angle according to the present invention;
FIG. 22 is a graph showing the equivalent amplitude brightness of short wave noise at a first angle according to the present invention;
FIG. 23 is a graph showing the equivalent amplitude brightness of medium wave noise at a first angle according to the present invention;
FIG. 24 is a schematic view of a long-wave noise equivalent amplitude luminance curve at a first angle according to the present invention;
FIG. 25 is a graph showing the noise equivalent amplitude luminance at a second angle according to the present invention;
FIG. 26 is a schematic view of a noise equivalent amplitude luminance curve at a third angle according to the present invention;
FIG. 27 is a graph showing the noise equivalent amplitude luminance at a fourth angle according to the present invention;
FIG. 28 is a graph comparing DN values of a black body at 30 ℃ with a device noise spectrum;
FIG. 29 is a graph of the radiant brightness of a black body at 30℃ versus the noise spectrum of the device;
FIG. 30 is a schematic diagram of the device for calibrating the fractional rotation angle of the noise equivalent radiance of the infrared spectrometer.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The terms "first" and "second" and the like in the description and in the claims are used for distinguishing between different objects and not for describing a particular sequential order of objects. For example, a first blackbody temperature point and a second blackbody temperature point, etc. are used to distinguish between different blackbody temperature points, and are not used to describe a particular order of blackbody temperature points.
In embodiments of the invention, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "e.g." in an embodiment should not be taken as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
In the description of the embodiments of the present invention, unless otherwise specified, the meaning of "plurality" means two or more, for example, a plurality of blackbody temperature points means two or more blackbody temperature points, etc.; the plurality of rotation angles means two or more rotation angles and the like.
Next, the technical scheme provided in the embodiment of the present invention is described.
Fig. 2 is a schematic flow chart of a method for calibrating a fractional rotation angle of noise equivalent radiance of an infrared spectrometer, and as shown in fig. 2, an execution subject of the method may be an electronic device, such as a server. The method includes step S101, step S102, step S103, step S104, and step S105.
Step S101, acquiring spectra of blackbody at different temperatures by using a rotary interference infrared spectrometer at a target environmental temperature, and acquiring spectral data corresponding to a plurality of blackbody temperature points.
Specifically, in order to achieve the noise equivalent radiance of the calibration rotary interference infrared spectrometer, infrared spectrum data of blackbody at different temperatures can be obtained under the same target environment temperature, and multiple pieces of spectrum data are collected at each blackbody temperature point.
Illustratively, black bodies of different temperatures were measured at a target ambient temperature of-1℃: the spectrum data of total 4 blackbody temperature points at 0 ℃, 30 ℃, 50 ℃ and 80 ℃ are collected, 1024 spectrums are collected under each blackbody temperature point, the Number N=1782 of Digital Number (DN) of each spectrum sample at the wavelength of 1.67-13.95 um, and the calibration test provides important support for subsequent analysis.
Step S102, classifying the spectrum data according to a plurality of rotation angles of the rotary interference infrared spectrometer based on the spectrum data respectively corresponding to the plurality of blackbody temperature points, and obtaining calibration data sets corresponding to the rotation angles, wherein the calibration data sets comprise the spectrum data respectively corresponding to the plurality of blackbody temperature points under the corresponding rotation angles.
Specifically, a fourier infrared spectrometer is rotated one revolution to produce multiple frames of spectra, each frame of spectra corresponding to an angle.
For example, a fourier infrared spectrometer rotates one revolution to produce 4 frames of spectra, four angles forming one revolution, a first frame of spectra being produced at a first angle, a second frame of spectra being produced at a second angle, a third frame of spectra being produced at a third angle, and a fourth frame of spectra being produced at a fourth angle.
And classifying the spectrums generated by the four angles according to the file numbers. Analyzing the number of each file to extract the included angle information, classifying according to the first angle, the second angle, the third angle and the fourth angle, integrating the spectrum data in the same angle range into a data set (namely the calibration data set), wherein one data set comprises the spectrum data respectively corresponding to a plurality of blackbody temperature points under the corresponding rotation angles, and facilitating the subsequent processing.
Step S103, obtaining a noise spectrum digital signal value DN value of the rotary interference infrared spectrometer through wavelet transformation based on the spectrum data respectively corresponding to each blackbody temperature point.
Specifically, wavelet change is performed on the collected spectrum data to obtain a high-frequency part of the data, namely a device noise spectrum DN value. In order to acquire the device noise spectrum, wavelet transformation is performed on the acquired blackbody data. Wavelet transform (Wavelet Transform, WT) is a transform analysis method that is primarily characterized by the ability to achieve localized analysis of temporal (or spatial) frequencies by transforming specific features of the salient problem. The method processes signals (or functions) by gradually refining in multiple scales and utilizing telescopic translation operation, and finally, high-frequency and low-frequency signals are obtained through decomposition. Wherein the high frequency signal reflects a detailed part of the signal, i.e. the noise signal of the device, and the low frequency signal reflects the general contour of the signal.
Alternatively, wavelet decomposition may be performed using a plurality of Bei Xixiao waves (DB wavelet functions). The multiple Bei Xixiao wave is mainly applied to discrete wavelet transformation, the classification of which is based on the value a of the vanishing momentum, and as a increases, the smoothness of the adjustment function (low-pass filtering) and the wavelet function (high-pass filtering) also increases. Illustratively, in the wavelet decomposition process using a plurality of Bei Xixiao waves, the present invention selects a=4 and performs wavelet decomposition on blackbody calibration data.
The wavelet decomposition result of the calibration curve of the target environment temperature of minus 1 ℃ and the blackbody temperature of 30 ℃ is shown in fig. 3, and fig. 3 is a schematic diagram of the noise signal of the device after wavelet decomposition provided by the invention.
It will be appreciated that the near-infrared to long-wave electromagnetic bands exhibit different characteristics in the ground scene and therefore require sub-band scaling. This is because the sources and characteristics of the signals in the different bands are different and it is important to accurately measure and interpret the signals.
In the medium-wavelength and long-wavelength ranges, the signal intensity of the ground scene is high and is mainly influenced by the self radiation of the ground. This means that the signals received by the device in these bands come mainly from the radiation emitted by the ground object itself, and thus corresponding mid-wave and long-wave sub-band scaling is required to accurately reflect the radiation characteristics of the ground scene.
In contrast, in the near infrared and short wave range, the signal of the ground scene is mainly affected by the reflection of solar radiation. Thus, in these bands, the scaling process requires more attention to the reflective properties of the signal to correctly interpret the response of the terrestrial object to solar radiation.
By means of sub-band calibration, the method and the device can be used for accurately knowing the radiation characteristics of ground scenes in different bands, are beneficial to avoiding errors caused by the difference between the bands, and improve the accuracy and reliability of remote sensing equipment in ground observation.
The result of wavelet decomposition of the calibration curve with the target environment temperature of-1 ℃ and the blackbody temperature of 30 ℃ is shown in fig. 4-7, fig. 4 is a near infrared band noise curve schematic diagram after wavelet decomposition provided by the invention, fig. 5 is a short wave band noise curve schematic diagram after wavelet decomposition provided by the invention, fig. 6 is a middle wave band noise curve schematic diagram after wavelet decomposition provided by the invention, and fig. 7 is a long wave band noise curve schematic diagram after wavelet decomposition provided by the invention.
Step S104, calculating system response gains corresponding to one or more first blackbody temperature points under each rotation angle based on the calibration data sets corresponding to each rotation angle.
The first blackbody temperature point is one of a plurality of blackbody temperature points, for example, the first blackbody temperature point is a 30 ℃ blackbody temperature point.
Specifically, based on a calibration data set corresponding to a target rotation angle, extracting spectral data corresponding to a second blackbody temperature point and spectral data corresponding to a third blackbody temperature point under the target rotation angle, wherein the target rotation angle is any one of a plurality of rotation angles, the second blackbody temperature point is lower than the first blackbody temperature point, and the third blackbody temperature point is higher than the first blackbody temperature point;
And determining the system response gain corresponding to the first blackbody temperature point under the target rotation angle through two-point linear calibration based on the spectrum data corresponding to the second blackbody temperature point and the spectrum data corresponding to the third blackbody temperature point under the target rotation angle.
The second black body temperature point and the third black body temperature point are two of the plurality of black body temperature points, for example, in the case that the first black body temperature point is 30 degrees celsius, the second black body temperature point is 0 degrees celsius, and the third black body temperature point is 50 degrees celsius.
Optionally, after extracting the spectral data corresponding to the second blackbody temperature point and the spectral data corresponding to the third blackbody temperature point at the target rotation angle based on the calibration data set corresponding to the target rotation angle, the method further includes:
determining a radiation bias corresponding to the first blackbody temperature point under the target rotation angle through two-point linear calibration based on the spectrum data corresponding to the second blackbody temperature point and the spectrum data corresponding to the third blackbody temperature point under the target rotation angle;
and carrying out Gaussian filtering processing based on the radiation bias corresponding to the first blackbody temperature point under the target rotation angle, and obtaining the filtered radiation bias corresponding to the first blackbody temperature point under the target rotation angle.
The radiation bias can be used to scale the DN value actually measured by the blackbody to obtain the corresponding blackbody radiation brightness.
Illustratively, using blackbody spectrum data, the system response gain and radiation bias for different blackbody temperatures at the same ambient temperature are calculated in terms of rotation angle.
The two-point linear calibration method is established on the premise that the system radiates the linear response in the dynamic range, and the output response is calibrated according to the uniformly calibrated output response, so that the calibration coefficient is obtained. The two-point scaling method is shown in the following formula (1):
DN(λ)＝Gain(λ)·S input (λ)+offset(λ) (1)；
where DN (lambda) is the system calibration data set, S input (lambda) is a system calibration test input corresponding to the calibration data set, gain (lambda) is a system Gain response function, offset (lambda) is a system radiation offset, lambda is a wavelength, and the unit is um.
From the above equation (1), it can be known that the Gain response function Gain (λ) and the radiation offset (λ) of the remote sensing system need to be calculated under at least two input conditions, and a high-temperature blackbody measurement (corresponding to the measurement of the third blackbody temperature point) and a low-temperature blackbody measurement (corresponding to the measurement of the second blackbody temperature point) are adopted.
DN H (λ)＝Gain(λ)·S H (λ)+offset(λ) (2)；
DN L (λ)＝Gain(λ)·S L (λ)+offset(λ) (3)；
Wherein Gain (λ) represents the system response Gain, offset (λ) represents the radiation bias, DN L (lambda) represents the spectral data corresponding to the second blackbody temperature point, S L (lambda) represents the preset blackbody theoretical radiance, DN, corresponding to the second blackbody temperature point H (lambda) represents spectral data corresponding to a third blackbody temperature point, S H And (lambda) represents the preset blackbody theoretical radiance corresponding to the third blackbody temperature point, and lambda represents the wavelength.
The combined type (2) and (3) can obtain Gain (lambda) and offset (lambda):
the gain and bias calculation of the equipment is carried out by using a blackbody at the temperature of-1 ℃ and a blackbody at the temperature of 50 ℃ of the target environment temperature and utilizing a split rotation angle two-point calibration method, the gain and bias calculation of the equipment is carried out by taking the formula (4) and the formula (5), the calculated split rotation angle gain curve is fitted, and the calculated gain curve is subjected to the sub-band treatment.
In the test environment, the radiation behaviors of various gas molecules and incomplete evacuation of the map-related equipment can have an influence on the experiment. Infrared radiation can occur during the testing of gas molecules (atmospheric, carbon dioxide molecules), generating background signals to spectroscopic data, especially in infrared spectroscopy experiments, which can lead to aliasing and interference of the signals. The radiation characteristics of different gas molecules also affect the shape and intensity of the spectrogram.
On the other hand, incomplete evacuation of the pattern-associated device may lead to the presence of gas residues in the test environment, whose molecules are also involved in infrared radiation. The presence of these residual gases may interfere with accurate measurements of the object to be measured. In addition, incomplete evacuation may introduce different temperature and pressure conditions, negatively affecting the repeatability and accuracy of the experimental results.
In order to reduce the influences, a Gaussian filtering treatment method is adopted for the bias curve obtained through calculation, so that the influence of incomplete vacuum pumping of various gas molecules in a test environment and spectrum related equipment can be effectively removed, and the accuracy and reliability of an experiment result are improved.
Optionally, the bands covered by the spectrum data corresponding to the blackbody temperature points respectively include: near infrared band, short wave band, mid wave band and long wave band, and correspondingly, the system response gain that the first blackbody temperature point corresponds includes: the system response gain in the near infrared band, the system response gain in the short wave band, the system response gain in the medium wave band, and the system response gain in the long wave band.
Fig. 8-13 show, in fig. 8, a schematic diagram of a system gain curve calculated from a black body temperature of 0 ℃ and 50 ℃ at a first angle provided by the present invention, fig. 9 is one of a first angular gain sub-band curve schematic diagram provided by the present invention, fig. 10 is a second of the first angular gain sub-band curve schematic diagram provided by the present invention, fig. 11 is a third of the first angular gain sub-band curve schematic diagram provided by the present invention, fig. 12 is a fourth of the first angular gain sub-band curve schematic diagram provided by the present invention, and fig. 13 is a schematic diagram of a system radiation bias calculated from a black body temperature of 0 ℃ and 50 ℃ at the first angle provided by the present invention.
Fig. 14 is a schematic diagram of a system gain curve calculated by the blackbody temperature at 0 ℃ and 50 ℃ at the second angle provided by the present invention, and fig. 15 is a schematic diagram of a system radiation bias calculated by the blackbody temperature at 0 ℃ and 50 ℃ at the second angle provided by the present invention, as shown in fig. 14 and 15.
Fig. 16 and 17 show graphs of system gain curves calculated from the black body temperatures of 0 ℃ and 50 ℃ at the third angle provided by the present invention, and fig. 17 shows graphs of system radiation bias calculated from the black body temperatures of 0 ℃ and 50 ℃ at the third angle provided by the present invention.
As shown in fig. 18 and 19, fig. 18 is a schematic diagram of a system gain curve calculated by the blackbody temperature at the fourth angle of 0 ℃ and 50 ℃, and fig. 19 is a schematic diagram of a system radiation bias calculated by the blackbody temperature at the fourth angle of 0 ℃ and 50 ℃.
Step S105, aiming at each rotation angle, calibrating the noise equivalent radiance corresponding to each first blackbody temperature point under each rotation angle based on the noise spectrum DN value and the system response gain corresponding to each first blackbody temperature point.
Specifically, inverting the noise spectrum of the corresponding type by using the gain and bias calculated by the blackbody of the corresponding angle and the corresponding temperature range to obtain the equivalent radiance of the noise of the equipment.
Illustratively, four different angles of 30 ℃ blackbody noise spectra are inverted using gains and offsets obtained from four angle solutions of 0 ℃ blackbody and 50 ℃ blackbody, respectively.
The traditional noise equivalent radiance calculation formula is as follows:
wherein DN is noise (lambda) is the digital signal value at noise wavelength lambda, k (lambda), b (lambda) are the system response gain and the system radiation bias at wavelength lambda, respectively; s is S input_noise And (lambda) is the equivalent image side radiation brightness of noise with wavelength lambda.
Since the invention adopts wavelet decomposition to acquire the noise spectrum of the equipment, the bias is successfully removed from the high-frequency part, and thus the noise radiance required by the invention is not influenced by the bias. This means that in noise analysis, the present invention can more accurately acquire the real noise characteristics generated by the device without being disturbed by the bias. The method is an important technical innovation for accurately measuring and analyzing the noise of equipment, and provides a more reliable data base for research and application in the related field.
In addition, the noise analysis of the present invention has higher sensitivity and resolution by successfully removing the bias through the high frequency part. Compared with the traditional method, the method is more accurate in measuring the equivalent radiance of noise, and provides more reliable data support for the engineering and science fields.
This technical innovation is of great significance for noise control and equipment optimization. Through accurately acquiring the frequency distribution and the intensity information of the noise, engineers and researchers can be assisted to take measures in a targeted manner, the performance of equipment is improved, the noise level is reduced, and therefore the reliability and the service life of the equipment are improved.
Therefore, the calculation formula of the noise equivalent radiation brightness of the invention is as follows:
wherein DN is noise (λ) is the digital signal value (DN value) at noise wavelength λ, k (λ) is the system response gain at wavelength λ; s is S input_noise And (lambda) is the equivalent image side radiation brightness of noise with wavelength lambda.
Optionally, the bands covered by the spectrum data corresponding to the blackbody temperature points respectively include: near infrared band, short wave band, medium wave band and long wave band, correspondingly, the equivalent radiance of noise that first blackbody temperature point corresponds includes: the noise equivalent radiance of the near infrared band, the noise equivalent radiance of the short wave band, the noise equivalent radiance of the medium wave band and the noise equivalent radiance of the long wave band.
As shown in fig. 20 to 24, fig. 20 is a schematic diagram of a first-angle noise equivalent amplitude luminance curve provided by the present invention, fig. 21 is a schematic diagram of a first-angle near-infrared noise equivalent amplitude luminance curve provided by the present invention, fig. 22 is a schematic diagram of a first-angle short-wave noise equivalent amplitude luminance curve provided by the present invention, fig. 23 is a schematic diagram of a first-angle medium-wave noise equivalent amplitude luminance curve provided by the present invention, and fig. 24 is a schematic diagram of a first-angle long-wave noise equivalent amplitude luminance curve provided by the present invention.
Fig. 25-27 show a second angular noise equivalent amplitude luminance graph according to the present invention, fig. 26 shows a third angular noise equivalent amplitude luminance graph according to the present invention, and fig. 27 shows a fourth angular noise equivalent amplitude luminance graph according to the present invention.
Fig. 28 is a 30 ℃ blackbody versus device noise spectrum DN value, and fig. 29 is a 30 ℃ blackbody versus device noise spectrum radiance comparison.
By respectively acquiring standard spectrum data under each rotating angle of the Fourier infrared spectrometer, classifying the spectrum data according to the rotating angles, acquiring a calibration data set corresponding to each rotating angle, and further calculating system response gains according to the rotating angles (in a two-point linear calibration mode) to determine system response gains respectively corresponding to one or more blackbody temperature points under each rotating angle, and further combining noise spectrum DN values obtained by wavelet transformation, the noise equivalent radiance corresponding to the blackbody temperature points can be calibrated according to the rotating angles, the integral linear relation of the spectrometer is considered, and the similarity under different angles is fully utilized, so that in actual measurement, a corresponding calibration curve can be selected according to the current measuring angle, and the measured data can be corrected more accurately.
The equipment noise calibration method provided by the invention not only improves the accuracy of measurement, but also reduces the influence of system errors by considering spectrum similarity. The method provides a more reliable calibration scheme for the application of the Fourier infrared spectrometer under various rotation angles, thereby playing a greater role in the fields of target identification and the like.
The sub-rotation angle calibration device provided by the invention is described below, and the sub-rotation angle calibration device described below and the sub-rotation angle calibration method described above can be referred to correspondingly.
FIG. 30 is a schematic structural diagram of a device for calibrating the fractional rotation angle of the noise equivalent radiance of an infrared spectrometer, provided by the invention, as shown in FIG. 30, the device comprises: the system comprises an acquisition module 10, a calibration data set acquisition module 20, a wavelet transformation module 30, a system response gain calculation module 40 and a calibration module 50. Wherein:
the acquisition module 10 is used for acquiring spectra of blackbody at different temperatures through the rotary interference infrared spectrometer under the target environmental temperature to acquire spectral data corresponding to a plurality of blackbody temperature points respectively;
the calibration data set obtaining module 20 is configured to classify the spectrum data according to a plurality of rotation angles of the rotation interference infrared spectrometer based on the spectrum data respectively corresponding to the plurality of blackbody temperature points, and obtain a calibration data set corresponding to each rotation angle, where the calibration data set includes spectrum data respectively corresponding to the plurality of blackbody temperature points under the corresponding rotation angles;
The wavelet transformation module 30 is configured to obtain a digital signal value DN value of a noise spectrum of the rotary interference infrared spectrometer through wavelet transformation based on spectral data corresponding to each blackbody temperature point;
a system response gain calculation module 40, configured to calculate, based on the calibration data sets corresponding to the rotation angles, system response gains corresponding to one or more first blackbody temperature points under the rotation angles, respectively;
the scaling module 50 is configured to scale, for each rotation angle, noise equivalent radiance corresponding to each first blackbody temperature point at each rotation angle based on the noise spectrum DN value and the system response gain corresponding to each first blackbody temperature point.
It should be understood that, the foregoing apparatus is used to perform the method in the foregoing embodiment, and corresponding program modules in the apparatus implement principles and technical effects similar to those described in the foregoing method, and reference may be made to corresponding processes in the foregoing method for the working process of the apparatus, which are not repeated herein.
Based on the method in the above embodiment, the embodiment of the invention provides an electronic device. The apparatus may include: at least one memory for storing programs and at least one processor for executing the programs stored by the memory. Wherein the processor is adapted to perform the method described in the above embodiments when the program stored in the memory is executed.
Based on the method in the above embodiment, the embodiment of the present invention provides a computer-readable storage medium storing a computer program, which when executed on a processor, causes the processor to perform the method in the above embodiment.
Based on the method in the above embodiments, an embodiment of the present invention provides a computer program product, which when run on a processor causes the processor to perform the method in the above embodiments.
It is to be appreciated that the processor in embodiments of the invention may be a central processing unit (central processing unit, CPU), other general purpose processor, digital signal processor (digital signal processor, DSP), application specific integrated circuit (application specific integrated circuit, ASIC), field programmable gate array (field programmable gate array, FPGA) or other programmable logic device, transistor logic device, hardware components, or any combination thereof. The general purpose processor may be a microprocessor, but in the alternative, it may be any conventional processor.
The steps of the method in the embodiment of the present invention may be implemented by hardware, or may be implemented by executing software instructions by a processor. The software instructions may be comprised of corresponding software modules that may be stored in random access memory (random access memory, RAM), flash memory, read-only memory (ROM), programmable ROM (PROM), erasable programmable PROM (EPROM), electrically erasable programmable EPROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present invention, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted across a computer-readable storage medium. The computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.
It will be appreciated that the various numerical numbers referred to in the embodiments of the present invention are merely for ease of description and are not intended to limit the scope of the embodiments of the present invention.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The method for calibrating the fractional rotation angle of the noise equivalent radiance of the infrared spectrometer is characterized by comprising the following steps of:
acquiring spectra of blackbody at different temperatures by using a rotary interference infrared spectrometer at a target environmental temperature, and acquiring spectral data corresponding to a plurality of blackbody temperature points respectively;
classifying the spectrum data according to a plurality of rotation angles of the rotation interference infrared spectrometer based on the spectrum data respectively corresponding to a plurality of blackbody temperature points, and obtaining calibration data sets corresponding to the rotation angles, wherein the calibration data sets comprise the spectrum data respectively corresponding to the blackbody temperature points under the corresponding rotation angles;
acquiring a noise spectrum digital signal value DN value of the rotary interference infrared spectrometer through wavelet transformation based on spectrum data corresponding to each blackbody temperature point;
Calculating system response gains corresponding to one or more first blackbody temperature points under each rotation angle based on the calibration data set corresponding to each rotation angle;
and aiming at each rotation angle, calibrating the noise equivalent radiance corresponding to each first blackbody temperature point under each rotation angle based on a noise spectrum DN value and the system response gain corresponding to each first blackbody temperature point.
2. The method for calibrating a sub-rotation angle of noise equivalent radiance of an infrared spectrometer according to claim 1, wherein the calculating a system response gain corresponding to one or more first blackbody temperature points under each rotation angle based on the calibration data set corresponding to each rotation angle comprises:
based on a calibration data set corresponding to a target rotation angle, extracting spectrum data corresponding to a second blackbody temperature point and spectrum data corresponding to a third blackbody temperature point under the target rotation angle, wherein the target rotation angle is any one angle of the plurality of rotation angles, the second blackbody temperature point is lower than the first blackbody temperature point, and the third blackbody temperature point is higher than the first blackbody temperature point;
And determining the system response gain corresponding to the first blackbody temperature point under the target rotation angle through two-point linear calibration based on the spectrum data corresponding to the second blackbody temperature point and the spectrum data corresponding to the third blackbody temperature point under the target rotation angle.
3. The method for calibrating the sub-rotation angle of the noise equivalent radiance of the infrared spectrometer according to claim 2, wherein the determining the system response gain corresponding to the first blackbody temperature point at the target rotation angle by two-point linear calibration based on the spectral data corresponding to the second blackbody temperature point and the spectral data corresponding to the third blackbody temperature point at the target rotation angle specifically comprises calculating the system response gain by the following formula:
wherein Gain (λ) represents the system response Gain, DN L (lambda) represents the spectral data corresponding to the second blackbody temperature point, S L (lambda) represents the preset blackbody theoretical radiance, DN, corresponding to the second blackbody temperature point H (lambda) represents spectral data corresponding to a third blackbody temperature point, S H And (lambda) represents the preset blackbody theoretical radiance corresponding to the third blackbody temperature point, and lambda represents the wavelength.
4. The method for calibrating the sub-rotation angle of the noise equivalent radiance of the infrared spectrometer according to claim 2, wherein after extracting the spectral data corresponding to the second blackbody temperature point and the spectral data corresponding to the third blackbody temperature point at the target rotation angle based on the calibration data set corresponding to the target rotation angle, further comprises:
Determining a radiation bias corresponding to a first blackbody temperature point under the target rotation angle through two-point linear calibration based on the spectrum data corresponding to a second blackbody temperature point and the spectrum data corresponding to a third blackbody temperature point under the target rotation angle;
and carrying out Gaussian filtering processing based on the radiation bias corresponding to the first blackbody temperature point under the target rotation angle, and obtaining the filtered radiation bias corresponding to the first blackbody temperature point under the target rotation angle.
5. The method for calibrating the sub-rotation angle of the noise equivalent radiance of the infrared spectrometer according to claim 4, wherein the determining the radiation bias corresponding to the first blackbody temperature point at the target rotation angle by two-point linear calibration based on the spectral data corresponding to the second blackbody temperature point and the spectral data corresponding to the third blackbody temperature point at the target rotation angle specifically comprises calculating the radiation bias by the following formula:
wherein offset (λ) represents the radiation bias, DN L (lambda) represents the spectral data corresponding to the second blackbody temperature point, S L (lambda) represents the preset blackbody theoretical radiance, DN, corresponding to the second blackbody temperature point H (lambda) represents spectral data corresponding to a third blackbody temperature point, S H And (lambda) represents the preset blackbody theoretical radiance corresponding to the third blackbody temperature point, and lambda represents the wavelength.
6. The method for calibrating the noise equivalent radiance of an infrared spectrometer according to claim 1, wherein the calibrating the noise equivalent radiance corresponding to each first blackbody temperature point at each rotation angle based on a noise spectrum DN value and a system response gain corresponding to each first blackbody temperature point specifically comprises calibrating the noise equivalent radiance by the following formula:
wherein S is input_noise (lambda) represents noise equivalent radiance, DN noise (lambda) represents the DN value at the noise wavelength lambda and k (lambda) represents the system response gain at the wavelength lambda.
7. The method for calibrating the fractional rotation angle of the noise equivalent radiance of an infrared spectrometer according to any one of claims 1 to 6, wherein the bands covered by the spectral data corresponding to the temperature points of each black body respectively comprise: near infrared band, short wave band, medium wave band and long wave band, correspondingly, the equivalent radiance of noise that first blackbody temperature point corresponds includes: the noise equivalent radiance of the near infrared band, the noise equivalent radiance of the short wave band, the noise equivalent radiance of the medium wave band and the noise equivalent radiance of the long wave band.
8. The utility model provides an infrared spectrometer noise equivalent radiance's branch rotation angle calibration device which characterized in that includes:
the acquisition module is used for acquiring spectra of blackbody at different temperatures through the rotary interference infrared spectrometer under the target environment temperature to acquire spectral data corresponding to a plurality of blackbody temperature points respectively;
the calibration data set acquisition module is used for classifying the spectrum data according to a plurality of rotation angles of the rotation interference infrared spectrometer based on the spectrum data respectively corresponding to a plurality of blackbody temperature points to acquire calibration data sets corresponding to the rotation angles, wherein the calibration data sets comprise the spectrum data respectively corresponding to a plurality of blackbody temperature points under the corresponding rotation angles;
the wavelet transformation module is used for acquiring a noise spectrum digital signal value DN value of the rotary interference infrared spectrometer through wavelet transformation based on the spectrum data respectively corresponding to each blackbody temperature point;
the system response gain calculation module is used for calculating system response gains corresponding to one or more first blackbody temperature points under each rotation angle based on the calibration data set corresponding to each rotation angle;
the calibration module is used for calibrating the noise equivalent radiance corresponding to each first blackbody temperature point under each rotation angle based on the noise spectrum DN value and the system response gain corresponding to each first blackbody temperature point.
9. An electronic device, comprising:
at least one memory for storing a program;
at least one processor for executing the memory-stored program, which processor is adapted to perform the method according to any of claims 1-7, when the memory-stored program is executed.
10. A non-transitory computer readable storage medium storing a computer program, characterized in that the computer program, when run on a processor, causes the processor to perform the method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311872363.XA CN117705748A (en) | 2023-12-31 | 2023-12-31 | Fractional rotation angle calibration method for noise equivalent radiance of infrared spectrometer |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311872363.XA CN117705748A (en) | 2023-12-31 | 2023-12-31 | Fractional rotation angle calibration method for noise equivalent radiance of infrared spectrometer |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117705748A true CN117705748A (en) | 2024-03-15 |
Family
ID=90149896
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311872363.XA Pending CN117705748A (en) | 2023-12-31 | 2023-12-31 | Fractional rotation angle calibration method for noise equivalent radiance of infrared spectrometer |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117705748A (en) |
-
2023
- 2023-12-31 CN CN202311872363.XA patent/CN117705748A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109100325B (en) | Gas concentration measuring method based on spectral absorption rate second harmonic feature extraction | |
| Withayachumnankul et al. | Fundamentals of measurement in terahertz time-domain spectroscopy | |
| CN101105446B (en) | Differential optical absorption spectroscopy air quality detection system | |
| RU2400715C2 (en) | Spectrometre calibration method | |
| CN103969211B (en) | A kind of method using near infrared spectrum detection FUFANG DANSHEN PIAN moisture | |
| CN105486655A (en) | Rapid detection method for organic matters in soil based on infrared spectroscopic intelligent identification model | |
| CN109991181B (en) | Adaptive surface absorption spectrum analysis method, system, storage medium and device | |
| Li et al. | Wavelength selection method for near-infrared spectroscopy based on standard-sample calibration transfer of mango and apple | |
| CN110632021A (en) | Spectrum detection method and system based on portable near-infrared spectrometer | |
| CN115391726A (en) | Fitting optimization method for ellipsometry system and related device | |
| CN105911015B (en) | Broadband dielectric parameter acquisition methods based on multiple-beam interference effect | |
| CN111141505A (en) | Non-invasive vacuum partial pressure rapid measuring instrument | |
| CN110927122A (en) | Phase type SPR detection device and method based on interference spectrum | |
| CN112729555B (en) | Method for synchronously diagnosing plasma temperature field by standard temperature method and relative spectral line method | |
| CN113390519A (en) | Device and method for improving spectral response measurement precision of infrared detector | |
| CN117705748A (en) | Fractional rotation angle calibration method for noise equivalent radiance of infrared spectrometer | |
| CN107389204B (en) | test platform and method for weak spectrum signals of infrared focal plane detector | |
| CN109141636A (en) | A kind of Fourier's formula infrared spectrometer equivalent noise spoke brightness measurement method | |
| CN116105875A (en) | Polarization calibration method for short wave infrared band of polarized remote sensor based on background radiation correction | |
| CN113640247A (en) | On-site dark current acquisition method based on near infrared spectrum technology | |
| CN113281296B (en) | Terahertz detector absolute spectral response calibration device and calibration method | |
| Wang et al. | A measurement method in near infrared spectroscopy for reference correction with the homologous optical beams | |
| CN110487404A (en) | A method of eliminating grating spectrograph Advanced Diffraction influences | |
| CN111044152A (en) | Self-adaptive correction method and system for spectrum bias external field of spectrum correlation system | |
| Workman Jr | Instrument Performance Calibration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |