Uncertainty propagation evaluation method in spatial heterodyne spectral measurement

Abstract

The invention relates to an uncertainty propagation evaluation method in spatial heterodyne spectral measurement, and belongs to the technical field of hyper-spectral remote sensing detection. The entrance pupil radiance spectral data # imgabs0 # and the output signal # imgabs1 # of the spatial heterodyne spectral measurement system are calculated; the uncertainty # imgabs2 # of the atmospheric parameters is calculated; the uncertainty # imgabs3 # of the signal electron number and the uncertainty # imgabs4 # of the noise are calculated; according to the uncertainty # imgabs5 # of the atmospheric parameters, the uncertainty # imgabs6 # of the signal electron number and the uncertainty # imgabs7 # of the noise, the uncertainty # imgabs8 # of the output signal of the spatial heterodyne spectral measurement system is calculated; the uncertain component of the uncertainty # imgabs9 # is analyzed; sorting influence contributions generated by the uncertain components; the method solves the problems that the design indexes of the spatial heterodyne spectral measurement system cannot quantitatively describe the measurement precision of the radiation energy, the entrance pupil radiance signal and the output signal, and the uncertainty contribution introduced by the spatial heterodyne spectral measurement link.

Description

Technical Field

[0001] The invention belongs to the technical field of hyperspectral remote sensing detection and relates to an uncertainty propagation evaluation method in spatial heterodyne spectrum measurement. Background Art The detection of multiple factors such as temperature, humidity, and pressure in the middle and upper atmosphere is of great significance to the study of global climate change. Spatial heterodyne spectroscopy measurement technology uses diffraction gratings to replace the plane mirrors of the Michelson interferometer. It has the characteristics of ultra-high spectral resolution, high light flux, and high stability. It can achieve vertical high-resolution observation of narrow-band spectra, thereby realizing hyperspectral observation, high signal-to-noise ratio observation, and high temporal and spatial resolution observation of the middle and upper atmosphere.

[0002] In the process of measuring atmospheric radiation signals using spatial heterodyne spectroscopy, the measurement results inevitably contain various forms of differences due to the limitations of many factors such as measurement load, measurement method, and measurement environment. How to accurately analyze the various errors that occur in the measurement process and minimize or eliminate their influence as much as possible, and then make a reasonable estimate of the errors that cannot be eliminated in the measurement results, and finally give a correct statement of the uncertainty of the measurement results, is an important prerequisite for the precise application of hyperspectral observation.

[0003] For general space measurement payloads, such as multispectral payloads and hyperspectral payloads, the performance of the payload is reflected by parameters such as signal-to-noise ratio, noise equivalent temperature difference, and calibration accuracy at a given signal level during design and development. In recent years, with the development of quantitative remote sensing technology, some space measurement payloads for quantitative applications have analyzed their measurement uncertainties based on the internationally accepted Guide to the Expression Uncertailnty in Measurement (GUM), and formed uncertainty propagation models.

[0004] However, the object of spatial heterodyne spectroscopy measurement is the non-steady atmosphere, especially the middle and upper atmosphere with greater randomness and faster changes. The general spatial measurement uncertainty assessment method cannot provide accurate and reliable evaluation results for atmospheric parameters or atmospheric element products. At the same time, the complex measurement process of spatial heterodyne spectroscopy measurement itself also brings many errors to extremely sensitive atmospheric element products such as temperature, humidity, and pressure, making it difficult to quantify the relationship between a given atmospheric state and atmospheric element products. Summary of the invention

[0005] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art and propose a method for evaluating the uncertainty propagation in spatial heterodyne spectroscopy measurement, which solves the problem that the design indicators of the spatial heterodyne spectroscopy measurement system cannot quantitatively describe the measurement accuracy of the radiation energy and entrance pupil radiance signal and the output signal, as well as the uncertainty contribution introduced by the spatial heterodyne spectroscopy measurement link.

[0006] The solution of the present invention is: A method for evaluating uncertainty propagation in spatial heterodyne spectroscopy measurement, comprising: Step 1: Calculate the pupil radiance spectrum data of the spatial heterodyne spectrum measurement system using the solar spectrum, atmospheric parameters, and load parameters and output signal ;in, is the wave number; Step 2: Calculate the uncertainty of atmospheric parameters ; Step 3: Calculate the uncertainty of the number of signal electrons and noise uncertainty ; Step 4: Based on the uncertainty of atmospheric parameters in step 2 , the uncertainty of the number of signal electrons in step 3 and noise uncertainty , calculate the uncertainty of the output signal of the spatial heterodyne spectroscopy measurement system ; Step 5: Analyze uncertainty The uncertain amount of Step 6: Sort the impact contributions of the uncertain components in step 5.

[0007] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, in step 1, the entrance pupil radiance spectrum data The calculation method is: According to the detection area and detection time of the spatial heterodyne spectral measurement system, the solar spectrum and atmospheric parameters such as gas composition content profile, atmospheric pressure profile, and atmospheric temperature profile are determined, and the entrance pupil spectral radiance spectrum data before reaching the spatial heterodyne spectral measurement system is calculated using the atmospheric radiation transmission software SCIATRAN. .

[0008] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, in step 1, the output signal The calculation method is: Counting signal electrons : Assume the F number of the front optical system is ,according to and transmittance , calculate the attenuated spectral radiance :

[0009] According to the Littrow angle of the diffraction grating and Littrow wave number , calculate the distance from the optical axis along the grating dispersion direction The interference intensity at :

[0010] According to the detector pixel area , Integration time , detector quantum efficiency , calculate the number of signal electrons :

[0011] In the formula, is Planck's constant; is the speed of light; Counting Noise Electrons :

[0012] In the formula, The photon noise of the measurement payload for spatial heterodyne spectroscopy; Dark current noise of the load is measured for spatial heterodyne spectroscopy; The readout noise of the spatial heterodyne spectroscopy measurement payload; Output signal for: .

[0013] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, in step 2, the uncertainty evaluation method of the atmospheric parameters is: S21. Use the Class B uncertainty assessment method to determine the uncertainty of atmospheric parameters such as gas composition content profile, atmospheric pressure profile, and atmospheric temperature profile; S22. According to the uncertainty of atmospheric parameters, random errors are superimposed on the gas component content profile, atmospheric pressure profile, and atmospheric temperature profile, and the entrance pupil radiance spectrum data is simulated by the Monte Carlo method; S23, calculate the standard deviation of the entrance pupil radiance spectrum data, and increase the number of simulations until the difference between two consecutive standard deviations is less than 5%; S24. Calculate the standard deviation of the simulated entrance pupil radiance spectrum data , and use it as the standard uncertainty of the entrance pupil radiance spectrum data:

[0014] In the formula, is the gas component content profile; is the atmospheric pressure profile; is the standard uncertainty of the atmospheric temperature profile; is the uncertainty caused by superimposing the SCIATRAN model.

[0015] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, in step 3, the uncertainty of the signal electron number is The calculation method is:

[0016] In the formula, Wave number The standard uncertainty of the corresponding entrance pupil radiance spectrum data; It represents the sensitivity coefficient of calculating the number of signal electrons to the entrance pupil radiance spectrum data using the first-order derivative.

[0017] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, in step 3, the uncertainty of the noise The calculation method is:

[0018] In the formula, is the standard deviation of photon noise; is the standard deviation of dark current noise; is the standard deviation of the readout noise.

[0019] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, in step 4, the uncertainty of the output signal of the spatial heterodyne spectroscopy measurement system is The calculation method is: .

[0020] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, in step 5, the method for determining the uncertainty component is: The relative uncertainty of the output signal is set to ; Establish The relationship is:

[0021] in, Relative uncertainty of the output signal introduced by atmospheric parameters; Relative uncertainty of the output signal introduced for the load parameters; Right now and Uncertain amount.

[0022] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, in step 6, the sorting method is: Calculate separately and The larger the value, the greater the impact contribution.

[0023] In the above-mentioned uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, the The calculation method is:

[0024] Said The calculation method is:

[0025] In the formula, , , They are the standard uncertainty of the gas component content profile, the standard uncertainty of the atmospheric pressure profile, and the standard uncertainty of the atmospheric temperature profile; is the uncertainty of the number of signal electrons; is the uncertainty of the noise.

[0026] The beneficial effects of the present invention compared with the prior art are: (1) The present invention adopts an uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, describes the spatial heterodyne spectroscopy measurement process from a metrological perspective, and synthesizes the uncertainty of atmospheric parameters and the uncertainty of load noise; (2) The present invention realizes the uncertainty traceability of the entrance pupil radiance spectrum data and output signal of the spatial heterodyne spectroscopy measurement system, and solves the problem that the design indicators of the spatial heterodyne spectroscopy measurement system cannot quantitatively describe the radiation energy and entrance pupil radiance signal; (3) The present invention solves the problem of output signal measurement accuracy and uncertainty contribution introduced by the spatial heterodyne spectroscopy measurement link, which is of great significance for application-oriented payload design optimization, precise application of hyperspectral observation, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of uncertainty propagation assessment of the present invention. DETAILED DESCRIPTION

[0028] The present invention will be further described below in conjunction with the embodiments.

[0029] The present invention provides a method for evaluating the uncertainty propagation in spatial heterodyne spectroscopy measurement, describes the spatial heterodyne spectroscopy measurement process from a metrological perspective, and analyzes the uncertainty of the measurement value, which is of great significance for application-oriented payload design optimization, precise application of hyperspectral observation, and the like.

[0030] Uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement, such as Figure 1 As shown, the specific steps include: Step 1: Calculate the pupil radiance spectrum data of the spatial heterodyne spectrum measurement system using the solar spectrum, atmospheric parameters, and load parameters and output signal ;in, is the wave number.

[0031] Entrance pupil radiance spectrum data The calculation method is: According to the detection area and detection time of the spatial heterodyne spectral measurement system, the solar spectrum and atmospheric parameters such as gas composition content profile, atmospheric pressure profile, and atmospheric temperature profile are determined, and the entrance pupil spectral radiance spectrum data before reaching the spatial heterodyne spectral measurement system is calculated using the atmospheric radiation transmission software SCIATRAN. .

[0032] Output signal The calculation method is: Counting signal electrons : Assume the F number of the front optical system is ,according to and transmittance , calculate the attenuated spectral radiance :

[0033] According to the Littrow angle of the diffraction grating and Littrow wave number , calculate the distance from the optical axis along the grating dispersion direction The interference intensity at :

[0034] According to the detector pixel area , Integration time , detector quantum efficiency , calculate the number of signal electrons :

[0035] In the formula, is Planck's constant; is the speed of light; Counting Noise Electrons :

[0036] In the formula, The photon noise of the measurement payload for spatial heterodyne spectroscopy; Dark current noise of the load is measured for spatial heterodyne spectroscopy; The readout noise of the spatial heterodyne spectroscopy measurement payload; Output signal for: .

[0037] Step 2: Calculate the uncertainty of atmospheric parameters .

[0038] The uncertainty assessment method of atmospheric parameters is: S21. Use the Class B uncertainty assessment method to determine the uncertainty of atmospheric parameters such as gas composition content profile, atmospheric pressure profile, and atmospheric temperature profile; use the uncertainty of atmospheric parameters as the source of uncertainty in the entrance pupil radiance spectrum data calculated by SCIATRAN.

[0039] S22. According to the uncertainty of atmospheric parameters, random errors are superimposed on the gas composition content profile, atmospheric pressure profile, and atmospheric temperature profile, and the entrance pupil radiance spectrum data is simulated by the Monte Carlo method.

[0040] S23. Calculate the standard deviation of the entrance pupil radiance spectrum data, and increase the number of simulations until the difference between two consecutive standard deviations is less than 5%.

[0041] S24. Calculate the standard deviation of the simulated entrance pupil radiance spectrum data , and use it as the standard uncertainty of the entrance pupil radiance spectrum data:

[0042] In the formula, is the gas component content profile; is the atmospheric pressure profile; is the standard uncertainty of the atmospheric temperature profile; is the uncertainty caused by superimposing the SCIATRAN model.

[0043] Step 3: Calculate the uncertainty of the number of signal electrons and noise uncertainty .

[0044] Uncertainty of signal electron count The calculation method is:

[0045] In the formula, Wave number The standard uncertainty of the corresponding entrance pupil radiance spectrum data; It represents the sensitivity coefficient of calculating the number of signal electrons to the entrance pupil radiance spectrum data using the first-order derivative.

[0046] Noise uncertainty The calculation method is:

[0047] In the formula, is the standard deviation of photon noise; is the standard deviation of dark current noise; is the standard deviation of the readout noise.

[0048] Step 4: Based on the uncertainty of atmospheric parameters in step 2 , the uncertainty of the number of signal electrons in step 3 and noise uncertainty , calculate the uncertainty of the output signal of the spatial heterodyne spectroscopy measurement system .

[0049] Uncertainty of Output Signal of Spatial Heterodyne Spectroscopy Measurement System The calculation method is: .

[0050] Step 5: Analyze uncertainty The uncertain amount.

[0051] The method for determining the uncertain component is: The relative uncertainty of the output signal is set to ; Establish The relationship is:

[0052] in, Relative uncertainty of the output signal introduced by atmospheric parameters; Relative uncertainty of the output signal introduced for the load parameters; Right now and Uncertain amount.

[0053] Step 6: Sort the impact contributions of the uncertain components in step 5.

[0054] The sorting method is: Calculate separately and The larger the value, the greater the impact contribution.

[0055] Said The calculation method is:

[0056] Said The calculation method is:

[0057] In the formula, , , They are the standard uncertainty of the gas component content profile, the standard uncertainty of the atmospheric pressure profile, and the standard uncertainty of the atmospheric temperature profile; is the uncertainty of the number of signal electrons; is the uncertainty of the noise.

[0058] The sources of uncertainty corresponding to the atmospheric parameters include the uncertainty of the gas composition content profile, the atmospheric pressure profile, and the atmospheric temperature profile; the sources of uncertainty corresponding to the load parameters include the uncertainty of photon noise, dark current noise, and readout noise.

[0059] The present invention adopts an uncertainty propagation assessment method in spatial heterodyne spectroscopy measurement, describes the spatial heterodyne spectroscopy measurement process from a metrological perspective, synthesizes the uncertainty of atmospheric parameters and the uncertainty of payload noise, and realizes the uncertainty traceability of the entrance pupil radiance spectral data and output signal of the spatial heterodyne spectroscopy measurement system. It solves the problem that the design indicators of the spatial heterodyne spectroscopy measurement system cannot quantitatively describe the measurement accuracy of the radiation energy and entrance pupil radiance signal and the output signal, as well as the uncertainty contribution introduced by the spatial heterodyne spectroscopy measurement link. It is of great significance for application-oriented payload design optimization, precise application of hyperspectral observation, and the like.

[0060] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for evaluating uncertainty propagation in spatial heterodyne spectroscopy, characterized in that: include: Step 1: Calculate the pupil radiance spectrum data of the spatial heterodyne spectrum measurement system using the solar spectrum, atmospheric parameters, and load parameters and output signal ;in, is the wave number; Step 2: Calculate the uncertainty of atmospheric parameters ; Step 3: Calculate the uncertainty of the number of signal electrons and noise uncertainty ; Step 4: Based on the uncertainty of atmospheric parameters in step 2 , the uncertainty of the number of signal electrons in step 3 and noise uncertainty , calculate the uncertainty of the output signal of the spatial heterodyne spectroscopy measurement system ; Step 5: Analyze uncertainty The uncertain amount of Step 6: Sort the impact contributions of the uncertain components in step 5.

2. The method for evaluating uncertainty propagation in spatial heterodyne spectroscopy measurement according to claim 1, characterized in that: In step 1, the entrance pupil radiance spectrum data The calculation method is: According to the detection area and detection time of the spatial heterodyne spectral measurement system, the solar spectrum and atmospheric parameters such as gas composition content profile, atmospheric pressure profile, and atmospheric temperature profile are determined, and the entrance pupil spectral radiance spectrum data before reaching the spatial heterodyne spectral measurement system is calculated using the atmospheric radiation transmission software SCIATRAN. .

3. The uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement according to claim 1, characterized in that: In the step 1, the output signal The calculation method is: Counting signal electrons : Assume the F number of the front optical system is ,according to and transmittance , calculate the attenuated spectral radiance : According to the Littrow angle of the diffraction grating and Littrow wave number , calculate the distance from the optical axis along the grating dispersion direction The interference intensity at : According to the detector pixel area , Integration time , detector quantum efficiency , calculate the number of signal electrons : In the formula, is Planck's constant; is the speed of light; Counting Noise Electrons : In the formula, The photon noise of the measurement payload for spatial heterodyne spectroscopy; Dark current noise of the load is measured for spatial heterodyne spectroscopy; The readout noise of the spatial heterodyne spectroscopy load measurement; Output signal for: 。 4. The method for evaluating uncertainty propagation in spatial heterodyne spectroscopy measurement according to claim 3, characterized in that: In step 2, the uncertainty of the atmospheric parameters is evaluated as follows: S21. Use the Class B uncertainty assessment method to determine the uncertainty of atmospheric parameters such as gas composition content profile, atmospheric pressure profile, and atmospheric temperature profile; S22. According to the uncertainty of atmospheric parameters, random errors are superimposed on the gas component content profile, atmospheric pressure profile, and atmospheric temperature profile, and the entrance pupil radiance spectrum data is simulated by the Monte Carlo method; S23, calculate the standard deviation of the entrance pupil radiance spectrum data, and increase the number of simulations until the difference between two consecutive standard deviations is less than 5%; S24. Calculate the standard deviation of the simulated entrance pupil radiance spectrum data , and use it as the standard uncertainty of the entrance pupil radiance spectrum data: In the formula, is the gas component content profile; is the atmospheric pressure profile; is the standard uncertainty of the atmospheric temperature profile; is the uncertainty caused by superimposing the SCIATRAN model.

5. The method for evaluating uncertainty propagation in spatial heterodyne spectroscopy measurement according to claim 4, characterized in that: In step 3, the uncertainty of the number of signal electrons is The calculation method is: In the formula, Wave number The standard uncertainty of the corresponding entrance pupil radiance spectrum data; It represents the sensitivity coefficient of calculating the number of signal electrons to the entrance pupil radiance spectrum data using the first-order derivative.

6. The method for evaluating uncertainty propagation in spatial heterodyne spectroscopy measurement according to claim 5, characterized in that: In step 3, the uncertainty of the noise The calculation method is: In the formula, is the standard deviation of photon noise; is the standard deviation of dark current noise; is the standard deviation of the readout noise.

7. The method for evaluating uncertainty propagation in spatial heterodyne spectroscopy measurement according to claim 6, characterized in that: In step 4, the uncertainty of the output signal of the spatial heterodyne spectroscopy measurement system is The calculation method is: 。 8. The method for evaluating uncertainty propagation in spatial heterodyne spectroscopy measurement according to claim 7, characterized in that: In step 5, the method for determining the uncertain component is: The relative uncertainty of the output signal is set to ; Establish The relationship is: in, Relative uncertainty of the output signal introduced by atmospheric parameters; Relative uncertainty of the output signal introduced for the load parameters; Right now and Uncertain amount.

9. The method for evaluating uncertainty propagation in spatial heterodyne spectroscopy measurement according to claim 8, characterized in that: In step 6, the sorting method is: Calculate separately and The larger the value, the greater the impact contribution.

10. The uncertainty propagation evaluation method in spatial heterodyne spectroscopy measurement according to claim 9, characterized in that: Said The calculation method is: Said The calculation method is: In the formula, , , They are the standard uncertainty of the gas component content profile, the standard uncertainty of the atmospheric pressure profile, and the standard uncertainty of the atmospheric temperature profile; is the uncertainty of the number of signal electrons; is the uncertainty of the noise.

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