A method for determining optimal working temperature of a spectrometer detector

Abstract

This invention relates to the field of detector operating temperature determination technology, and more particularly to a method for determining the optimal operating temperature of a spectrometer detector. The method includes the following steps: performing theoretical analysis to determine the signal-to-noise ratio (SNR) formula, analyzing the relationship between detector signal and temperature, and the relationship between detector noise and temperature, and theoretically calculating the SNR-temperature relationship; simultaneously performing laboratory measurements, including experimental setup and data acquisition and calculation; and finally, combining the theoretical calculations and the actual measured SNR results to determine the optimal operating temperature of the InGaAs detector. This invention can obtain the operating temperature at which the InGaAs detector achieves the highest SNR. When using the InGaAs detector for measurements, a temperature control module is used to stabilize the InGaAs detector at this temperature, resulting in better performance of the short-wave infrared spectrometer based on the InGaAs detector and improved instrument measurement accuracy.

Description

Technical Field

[0001] This invention relates to the field of detector operating temperature determination technology, and more particularly to a method for determining the optimal operating temperature of a spectrometer detector. Background Technology

[0002] Currently, greenhouse gas levels are rising year by year, exacerbating the greenhouse effect and posing significant threats to people's work and lives. Therefore, monitoring greenhouse gases is urgently needed. Short-wave infrared imaging spectrometry is a commonly used greenhouse gas monitoring technology, and the infrared detector, as the core component of short-wave infrared imaging spectrometry, directly affects the measurement accuracy of the spectrometer. Furthermore, infrared detectors play a crucial role in modern industry and the military, and various types of infrared detectors are widely used in numerous fields.

[0003] Compared to visible light imaging and mid-to-long-wave infrared imaging, short-wave infrared imaging technology started later, only gaining traction after the emergence and continuous development of mercury cadmium telluride (MCT) materials. However, its application in the short-wave infrared band has been slow due to limitations such as the need for deep cooling in MCT detectors. In recent years, the emergence of indium gallium arsenide (InGaAs) materials has significantly boosted the development of short-wave infrared imaging technology. InGaAs is a III-V pseudobinary semiconductor material with a zincblende cubic crystal structure. Its cutoff wavelength can be adjusted by the content of In and Ga, achieving variations from 0.87 μm to 3.5 μm. Furthermore, InGaAs can be well matched with III-V substrates to fabricate high-quality epitaxial structures, and its mature growth technology makes it easier to produce than materials like MCT. In addition, InGaAs near-infrared detectors exhibit high quantum efficiency and extremely low dark current within the effective operating wavelength range, and the requirements for cooling are gradually decreasing. Currently, it is widely used in infrared imaging, infrared remote sensing, and fiber optic sensing.

[0004] As early as the 1980s, many international research institutions began studying InGaAs materials and devices. Abroad, companies such as SUI in the US, Sofradir in France, and Xenics in Belgium are all dedicated to the research and development and production of InGaAs infrared imaging detectors, cameras, and imaging systems. With technological advancements, the imaging specifications, pixel size, and other performance characteristics of InGaAs detectors have continuously improved, and they are now widely used in military and industrial fields worldwide. For example, the spectrometer in MethaneAIR, the predecessor to the recently launched MethaneSAT satellite, uses an InGaAs detector. Carly Staebell et al. achieved high-precision CH4 measurements by studying the spectrometer's spectral calibration, including stray light correction and instrument response function acquisition. Conway et al. improved the spectrometer's signal-to-noise ratio through blind pixel masking, dark current subtraction, noise estimation, and pixel merging. In China, research on InGaAs detectors started relatively late. Major research institutions include the Shanghai Institute of Technical Physics of the Chinese Academy of Sciences, the 44th Research Institute of China Electronics Technology Group Corporation (CETC), and the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Sciences. In recent years, some domestic semiconductor companies, such as Guohui Optoelectronics and Liding Optoelectronics, have also begun research on InGaAs detectors. After successfully developing its first 128×128 pixel InGaAs detector with a pixel size of 40μm in 2006, my country has made continuous technological breakthroughs, striving to catch up with advanced international levels. The Shanghai Institute of Technical Physics of the Chinese Academy of Sciences also successfully developed a 1280×1024 pixel InGaAs focal plane array detector with a center distance of 15μm in 2019, reaching the forefront internationally. However, most of my country's applied research on InGaAs detectors focuses on improving the imaging quality of the detector through compensation measures. For example, the team of Fang Jiaxiong and Li Yongfu at Shandong University is researching short-wave infrared imaging technology based on domestically produced InGaAs detectors. They are studying blind pixel compensation and non-uniformity correction methods in InGaAs detectors to improve the imaging quality of short-wave infrared imagers. Furthermore, the team led by Ding Lei and Niu Xinhua at the Shanghai Institute of Technical Physics, Chinese Academy of Sciences, was the first to apply InGaAs detectors to the field of ultra-high-frequency spectroscopy. By studying their noise and laboratory calibration methods, they aimed to improve the signal-to-noise ratio of InGaAs detector-based spectrometers and enhance the accuracy of CO2 measurements. However, few studies have explored the optimal operating temperature of InGaAs detectors. Because the quantum efficiency of InGaAs detectors is significantly affected by material bandgap, doping level, and temperature, its effectiveness is greatly influenced by temperature. Therefore, selecting a suitable temperature for the detector is crucial for improving the signal-to-noise ratio of the spectrometer.

[0005] By observing that the quantum efficiency of the InGaAs detector gradually decreases with increasing temperature in the short-wave infrared band, while the dark current noise of the detector increases exponentially with temperature, it was inferred that there is a maximum signal-to-noise ratio (SNR) for the spectrometer at a certain temperature. To verify this hypothesis, approximate calculations were performed using the SNR formula, and laboratory measurements were conducted. Ultimately, 0℃ was selected as the optimal operating temperature for the InGaAs detector, resulting in the highest SNR for the overall spectrometer system. Using a temperature control device to consistently stabilize the detector temperature at 0℃ effectively improves the measurement accuracy of the InGaAs short-wave infrared spectrometer. This lays a solid foundation for subsequent solar radiation spectral measurements and atmospheric CH4 measurements.

[0006] Currently, most research on InGaAs detectors in my country focuses on their imaging quality characteristics, such as blind pixels, non-uniformity, pixel size, or pixel count. Few studies have explored the optimal operating temperature of InGaAs detectors. Furthermore, most people assume that for InGaAs infrared detectors, lower temperatures generally result in lower dark noise and higher signal-to-noise ratios. However, due to the unique properties of InGaAs material, including material defects and fabrication issues, the quantum efficiency of most InGaAs detectors decreases with decreasing temperature in the short-wave infrared band. Since the main noise source in InGaAs, dark current noise, decreases with decreasing temperature, it is inferred that InGaAs detectors exhibit the highest signal-to-noise ratio and best performance at a specific temperature. Therefore, this application proposes a method for determining the optimal operating temperature of spectrometer detectors. Summary of the Invention

[0007] The purpose of this invention is to address the problem in the background art that few people have explored the optimal operating temperature of InGaAs detectors, and it is impossible to know at what temperature the detector performs best. This invention proposes a method for determining the optimal operating temperature of spectrometer detectors.

[0008] The technical solution of the present invention: a method for determining the optimal operating temperature of a spectrometer detector, the method comprising the following steps:

[0009] Theoretical analysis was conducted to determine the signal-to-noise ratio formula, analyze the relationship between detector signal and temperature, analyze the relationship between detector noise and temperature, and theoretically calculate the relationship between signal-to-noise ratio and temperature.

[0010] Perform laboratory measurements, including experimental setup and data acquisition and calculation;

[0011] Based on the combined theoretical calculations and actual measurement of the signal-to-noise ratio, the optimal operating temperature for the InGaAs detector was determined.

[0012] Optionally, the signal-to-noise ratio (SNR) can be calculated using the following formula:

[0013]

[0014] Where S represents the light signal measured by the spectrometer under a fixed light source, expressed as S = L × QE, where L refers to the product of other fixed parameters after the spectrometer structure is designed, excluding the detector quantum efficiency QE; N is the total detector noise during normal measurement, expressed as... Detector noise consists of readout noise N read Shot noise N shot Dark current noise N dark and fixed-mode noise N FPN composition.

[0015] Optionally, analyzing the relationship between detector signals and temperature specifically includes:

[0016] A quantitative analysis of the relationship between the quantum efficiency of InGaAs detectors and temperature was conducted. The response DN values ​​within the CH4 inversion band of 1630nm-1660nm were averaged, and a curve was fitted with temperature as the abscissa and the average response value as the ordinate. The average response value was used to replace the detector measurement signal in the calculation of the relationship between the detector signal-to-noise ratio and temperature.

[0017] Optionally, at different temperatures, with an integration time of 200ms, 100 dark background images at the corresponding temperatures are acquired and averaged to obtain the dark background noise grayscale response value results, and the relationship between dark noise response and temperature is subjected to exponential fitting.

[0018] Optionally, the analysis of the relationship between detector noise and temperature specifically involves replacing the total noise in the signal-to-noise ratio (SNR) calculation with the detector's dark current noise, and theoretically calculating the relationship between SNR and temperature.

[0019] Using the formula:

[0020]

[0021] An approximate calculation is performed, in which the average DN value of the CH4 inversion band response is used to replace the detector quantum efficiency, and the dark background noise grayscale response value is used to replace the dark current noise.

[0022] Optionally, the experimental setup includes:

[0023] An integrating sphere is used as the light source, and a short-wave infrared spectrometer is placed in front of the integrating sphere;

[0024] Adjust the brightness of the integrating sphere so that its response is within the appropriate range of the spectrometer.

[0025] Optionally, the data acquisition and calculation include:

[0026] The spectral response was continuously measured at 200 different temperatures, and the average value of the response was used as the signal, while the standard deviation was used as the noise.

[0027] According to the formula:

[0028]

[0029] The actual signal-to-noise ratio measured by the spectrometer was obtained.

[0030] Optionally, the signal-to-noise ratio of the spectrometer reaches its maximum value when the detector temperature is between -1 and 1℃. Considering the stability and effectiveness of the detector's temperature control in actual spectrometer measurements, 0℃ is selected as the optimal operating temperature for the InGaAs detector.

[0031] Compared with the prior art, this application includes at least one of the following beneficial technical effects:

[0032] By combining theoretical approximation calculations with actual laboratory measurements, the operating temperature at which the InGaAs detector achieves the highest signal-to-noise ratio was calculated. When using the InGaAs detector for measurements, a temperature control module was used to keep the InGaAs detector stable at this temperature, thus ensuring good instrument performance and improving measurement accuracy.

[0033] This invention ensures that the short-wave infrared imaging spectrometer developed based on the InGaAs detector has a high signal-to-noise ratio, which is of great significance for accurately monitoring the content of greenhouse gases in the atmosphere. Attached Figure Description

[0034] Figure 1 The fitting curve for the average response of the integrating sphere;

[0035] Figure 2 This is a graph showing the change of DN value in the dark background noise response as a function of temperature.

[0036] Figure 3 The graph shows the ratio of the quantum efficiency of the InGaAs detector to the dark noise background response.

[0037] Figure 4 This is a graph showing the change in signal-to-noise ratio of a laboratory spectrometer as a function of temperature. Detailed Implementation

[0038] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0039] Example

[0040] This invention proposes a method for determining the optimal operating temperature of a spectrometer detector, which is described in detail below.

[0041] Signal-to-noise ratio (SNR) is a key indicator reflecting a detector's ability to acquire effective target information. Specifically, it refers to the ratio of the signal acquired by the instrument to the noise level. The magnitude of the SNR directly affects the accuracy of the detection data and analysis results; only by meeting the SNR requirements can the usability of the measurement signal be guaranteed. A detector with a low SNR will cause a large amount of complex physical noise to overwhelm the image's features, severely affecting the identification and interpretation of the measured target. Therefore, ensuring a high SNR for the detector is a prerequisite for ensuring the accurate measurement of the developed shortwave infrared spectrometer.

[0042] The formula for calculating the signal-to-noise ratio is:

[0043]

[0044] S represents the light signal measured by the spectrometer under a fixed light source. Specifically, it can be expressed by the following formula:

[0045] S=L(λ,r,φ)×τ×QE×A×ω×N sr ×Δλ×t int (2)

[0046] Where L(λ,r,φ) represents the spectral radiance of the optical system under the conditions of solar zenith angle φ and ground albedo r, τ is the transmittance of the optical system, QE is the quantum efficiency of the detector in the operating band, A is the entrance pupil area, ω is the instantaneous field of view angle of the system, and Δλ is the spectral bandwidth covering a single pixel of the detector, which is equal to the instrument's spectral resolution (FWHM) divided by the spectral sampling rate N. sr , t int Let S be the system integration time. Of the parameters mentioned above, all except the detector quantum efficiency can be determined after the spectrometer structure is designed. Here, L represents the product of all parameters, i.e., S can also be expressed as:

[0047] S=L×QE (3)

[0048] N represents the total noise of the detector during normal measurement. The detector noise is generally considered to consist of four parts, including readout noise N. read Shot noise N shot Dark current noise N dark and fixed-mode noise N FPN The expression is as follows:

[0049]

[0050] Substituting the signal S (3) and noise N (4) into the signal-to-noise ratio formula, as shown below, the parameters in the SNR expression are analyzed below.

[0051]

[0052] ① Detector signal

[0053] To quantify the relationship between the quantum efficiency of InGaAs detectors and temperature, the response DN values ​​within the CH4 inversion band of 1630nm–1660nm were averaged, and the result was used as the response value at the current temperature. Furthermore, a curve was fitted with temperature on the x-axis and the average response value on the y-axis. The fitted curve is given by formula (6), which expresses the relationship between detector signal strength and temperature. Figure 1 As shown:

[0054] y = -0.02853 * x 3 -1.958*x 2 +45.01*x+5152 (6)

[0055] Depend on Figure 1 It can be seen that as the temperature increases, the average response value begins to rise slowly, and then begins to decrease slightly after 10℃. Calculations show that it reaches its maximum value around 9℃. Using the average response value instead of the detector's measured signal in the calculation of the relationship between the detector's signal-to-noise ratio and temperature, the optimal operating temperature of the InGaAs detector can be found.

[0056] ② Detector noise

[0057] Typically, detector noise consists of four parts, including readout noise N. read Shot noise N shot Dark current noise N dark and fixed-mode noise N FPN However, after blind element compensation and non-uniformity correction are performed on the detector, the detector's readout noise, shot noise, and fixed-mode noise are less affected by temperature and can be ignored in the calculation of the signal-to-noise ratio versus temperature relationship. Therefore, the detector's dark current noise is used to replace the total noise in the signal-to-noise ratio calculation.

[0058] Dark current noise refers to noise generated under conditions of no light, primarily caused by thermally generated charge carriers in the detector material. It is a component of the output signal of optoelectronic devices in complete darkness and a major source of noise when the detector's operating temperature changes. It exhibits temperature dependence, time dependence, and inter-pixel differences; specifically, dark current increases with increasing temperature because higher temperatures result in a greater number of thermally generated charge carriers in the detector material. To quantify the relationship between dark current and temperature, 100 dark background images were acquired at different temperatures with an integration time of 200 ms. These images were then averaged to obtain the dark background noise grayscale response value, as shown below. Figure 2As shown in the image, the dark noise variation with temperature is significant at higher InGaAs detector temperatures. After the cooling temperature reaches -10℃, the dark noise curve flattens as the temperature decreases. Observing the image, an exponential fit is performed on the relationship between the dark noise response and temperature. The fitted expression is as follows:

[0059] y = 319.0286 * e 0.072283*x +2544.24519

[0060] The above analysis reveals that the signal-to-noise ratio (SNR) of a short-wave infrared spectrometer based on an InGaAs detector is only related to the detector's own quantum efficiency signal and dark current noise. This can be approximated by the following formula, where SNR... T The approximate signal-to-noise ratio of the instrument, calculated theoretically, is represented by the average DN value of the response within the CH4 inversion band of 1630nm–1660nm, which replaces the detector quantum efficiency. Dark background noise grayscale response values ​​replace dark current noise. Substituting the above fitting expression, the result is:

[0061]

[0062] like Figure 3 As shown, the calculated signal-to-noise ratio exhibits a trend of first increasing and then decreasing with rising temperature. Calculations indicate that the theoretically approximate signal-to-noise ratio of the spectrometer reaches its maximum at 0.5℃. Therefore, it can be approximately inferred that the short-wave infrared spectrometer has the highest signal-to-noise ratio when the InGaAs detector operates at 0.5℃.

[0063] ③ Laboratory signal-to-noise ratio measurement

[0064] In actual measurements, the optical signal in a spectrometer is usually measured and calculated continuously under laboratory conditions using a stable light source at a certain brightness. The noise in the signal-to-noise ratio is usually characterized by the statistical standard deviation. Obtaining the signal-to-noise ratio during actual measurements of the spectrometer provides an important reference for detector performance testing and spectrometer measurement signal evaluation.

[0065] In this embodiment, an integrating sphere is used as the light source. The short-wave infrared spectrometer is placed in front of the integrating sphere, and the brightness of the integrating sphere is adjusted so that its response is within a suitable range of the spectrometer. 200 sets of spectral responses at different temperatures are continuously measured. The average value of these responses is used as the signal, and the standard deviation is used as the noise. The actual signal-to-noise ratio of the spectrometer is then obtained according to the following formula:

[0066]

[0067] In the formula, SNR M This represents the signal-to-noise ratio of the instrument during actual measurement. The results obtained are as follows: Figure 4As shown, the experimentally measured signal-to-noise ratio (SNR) of the spectrometer exhibits the same trend as the theoretically calculated approximate SNR curve, both showing an initial increase followed by a decrease with rising temperature. The SNR reaches its maximum value near 1℃.

[0068] ④ Conclusion

[0069] Based on theoretical calculations and actual measurement results of the signal-to-noise ratio (SNR), it was found that the SNR reaches its maximum value when the detector temperature is between -1 and 1°C. Considering the stability and effectiveness of the detector's temperature control in actual measurements, 0°C was ultimately selected as the optimal operating temperature for the InGaAs detector. This ensures both a high SNR and high imaging quality. This provides a reference for the application measurement of short-wave infrared spectrometer systems based on InGaAs detectors and lays the foundation for accurate monitoring of CH4 in the atmosphere.

[0070] The above specific embodiments are merely several optional embodiments of the present invention. Based on the technical solutions of the present invention and the relevant teachings of the above embodiments, those skilled in the art can make various alternative improvements and combinations to the above specific embodiments.

Claims

1. A method for determining the optimal operating temperature of a spectrometer detector, characterized in that, The method comprises the following steps: Theoretical analysis is performed to determine the signal-to-noise ratio formula, analyze the relationship between the detector signal and temperature, analyze the relationship between the detector noise and temperature, and theoretically calculate the relationship between the signal-to-noise ratio and temperature; the signal-to-noise ratio calculation formula is: wherein, represents the optical signal measured by the spectrometer under a fixed light source, denoted as , refers to the product of other determined parameters except the detector quantum efficiency after the structure design of the spectrometer; is the total noise of the detector during normal measurement, expressed as The detector noise is composed of readout noise , shot noise , dark current noise and fixed pattern noise ; The analysis of the relationship between the detector signal and temperature specifically comprises: Quantitative analysis of the relationship between the quantum efficiency of InGaAs detector and temperature, select the The response DN values in the band 1630nm-1660nm are averaged, and the temperature is taken as the horizontal coordinate and the average response value is taken as the vertical coordinate to perform curve fitting, and the average response value is used to replace the detector measurement signal to participate in the calculation of the relationship between the detector signal-to-noise ratio and the temperature. The analysis of the relationship between the detector noise and temperature specifically comprises: replacing the total noise in the signal-to-noise ratio calculation with the dark current noise of the detector, and theoretically calculating the relationship between the signal-to-noise ratio and temperature: The formula is: An approximation is made in which The average DN values of the inverse band responses are used instead of the detector quantum efficiency, and the dark background noise gray response values are used instead of the dark current noise. Laboratory measurement is performed, including experimental setup and data acquisition and calculation; the data acquisition and calculation comprises: 200 groups of spectral responses at different temperatures are continuously measured, the average value of the responses is taken as the signal, and the standard deviation is taken as the noise; According to the formula: The actual measurement signal-to-noise ratio of the spectrometer is obtained; The signal-to-noise ratio results of the theoretical calculation and the actual measurement are combined to determine the optimal working temperature of the InGaAs detector.

2. The method for determining the optimal working temperature of a detector of a spectrometer according to claim 1, wherein, At different temperatures, the integral time is 200 ms, 100 dark background images at the corresponding temperature are collected and averaged to obtain the dark background noise gray response value results, and the relationship between the dark noise response and the temperature is exponentially fitted.

3. The method for determining the optimal working temperature of a detector of a spectrometer according to claim 1, wherein, The experimental setup comprises: An integrating sphere is used as a light source, and the short-wave infrared spectrometer is placed in front of the integrating sphere; The brightness of the integrating sphere is adjusted so that the response is within the appropriate range of the spectrometer.

4. The method for determining the optimal working temperature of a detector of a spectrometer according to claim 1, wherein, When the detector temperature is -1-1℃, the signal-to-noise ratio of the spectrometer during measurement will reach the maximum value, combined with the stability and effectiveness of the detector temperature control in the actual measurement of the spectrometer, 0℃ is selected as the optimal working temperature of the InGaAs detector.

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