Automatic device for keeping spectral response rate of spaceborne infrared hyperspectral detector

Abstract

The application provides a kind of satellite-borne infrared hyperspectral detector spectral response rate automatic maintenance device, it relates to the technical field of satellite-borne infrared hyperspectral detection, the device includes: on-board data processor, for receiving and processing on-board blackbody measurement data and cold empty background data in real time, spectral response rate is obtained in real time in orbit calculation;Spectral response rate memory, for storing the spectral response rate data calculated;Response rate threshold comparator, for comparing the calculated spectral response rate with the preset threshold;Heating decontamination driver, for starting heating decontamination operation to restore the spectral response rate of instrument when the spectral response rate is lower than the set threshold.The application is used to characterize the signal detection capability of instrument and maintain the stability of detection capability, when calculating the spectral response rate of instrument, a large number of data samples are not needed to be counted, and temperature fluctuation factors in sensitivity statistics are not needed to be considered when calculating, so that the spectral response rate algorithm is simple, the calculation speed is fast, and the real-time performance is good.

Description

Technical Field

[0001] This invention relates to the field of spaceborne infrared hyperspectral detection technology, and specifically to an automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector. Background Technology

[0002] Effective response to Earth's radiation is a prerequisite for the on-orbit operation of a spaceborne infrared hyperspectral detector, and it is also the foundation for deriving high-precision quantitative geophysical parameters such as atmospheric temperature, relative humidity, and trace gas concentrations from observational data. Currently, the main method for characterizing the on-orbit performance of the instrument is instrument sensitivity evaluation technology. Sensitivity reflects the instrument's ability to respond to the smallest detectable signal. The sensitivity evaluation method for spaceborne infrared hyperspectral detectors mainly involves observing spectral data from onboard calibration sources (either an internal blackbody or a cold space scene), then removing the trend line from the spectral samples using a sample sequence moving average method, and finally calculating the standard deviation of the spectral residual samples after removing the trend line, thus obtaining the instrument's sensitivity spectral distribution.

[0003] However, current methods for evaluating the sensitivity of spaceborne infrared hyperspectral detectors have the following technical shortcomings:

[0004] 1. Timeliness Deficiency: Characterizing the instrument's signal detection capability by using the sensitivity derived from the on-board calibration source requires collecting a sufficient number of observation samples to reduce the impact of random errors. In addition, special consideration must be given to the additional noise or spurious trends introduced into the sensitivity assessment by internal temperature fluctuations (especially blackbody temperature), electromagnetic interference, or mechanical vibration during sample collection. Therefore, although the instrument sensitivity method can reflect the long-term detection performance of the instrument, it is statistically time-consuming (for example, the Fengyun-3 infrared hyperspectral atmospheric sounder needs to collect blackbody data for about 100 minutes per orbit for sensitivity calculation, that is, the sensitivity spectrum can only be calculated once every 100 minutes), the calculation method is complex, and it cannot reflect the rapidly changing situation of the instrument in orbit in real time.

[0005] 2. Design Flaws: Existing methods for calculating the sensitivity of spaceborne instruments are indirect means of evaluating their signal detection capabilities. When an instrument's detection performance deteriorates due to the adsorption of internal contaminants or damage to its optical coating, the sensitivity spectrum, while exhibiting accompanying degradation, does not directly reflect the cause of the decline. Furthermore, the evaluation results are also affected by the sample size. When the sample size is small, the spectral characteristics of the degraded sensitivity are susceptible to interference from noise within the sample data itself, failing to reflect the extent to which contaminant adsorption affects the instrument's detection capabilities. Summary of the Invention

[0006] In view of this, and addressing the shortcomings of existing sensitivity evaluation techniques for characterizing and monitoring the on-orbit signal detection capabilities of spaceborne instruments, such as low timeliness, complex calculation methods, and significant influence from the sample size and noise of calibration source data, the present invention aims to propose an automatic spectral response rate maintenance device for spaceborne infrared hyperspectral detectors to characterize the instrument's signal detection capabilities and maintain the stability of its detection capabilities. This device collects on-board blackbody and cold space background data, performs infrared background signal subtraction and fast Fourier transform spectral calculation to obtain the instrument's response spectrum to blackbody radiation. Then, based on the prior blackbody radiation spectrum calculated from the blackbody temperature, the instrument's blackbody response spectrum is divided by the prior radiation spectrum to obtain the instrument's spectral response rate data. Calculating the instrument's spectral response rate does not require statistical analysis of a large number of data samples, and the calculation method does not need to consider temperature fluctuation factors in sensitivity statistics. Therefore, the spectral response rate algorithm is simple, fast, and has good real-time performance, and is easily implemented by on-board data processing equipment (FPGA).

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] In view of the above objectives, in a first aspect, the present invention provides an automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector, comprising the following components:

[0009] The onboard data processor is used to receive and process onboard blackbody measurement data and cold space background data in real time, and to obtain the spectral responsivity in real time on orbit.

[0010] Spectral response rate memory is used to store the calculated spectral response rate data;

[0011] A response rate threshold comparator is used to compare the calculated spectral response rate with a preset threshold.

[0012] The heating decontamination driver is used to initiate a heating decontamination operation to restore the instrument's spectral response rate when the spectral response rate is lower than a set threshold.

[0013] As a further aspect of the present invention, the on-board data processor uses a dedicated field-programmable gate array (FPGA) to receive on-board blackbody measurement data and cold space background data for background subtraction from the on-board data memory. The FPGA is configured with an FFT IP core and an arithmetic unit, which are used to call the FFT IP core and the arithmetic unit to perform infrared background signal subtraction, fast Fourier transform (FFT) spectral calculation on the on-board blackbody measurement data and cold space background data, and calculate the spectral responsivity of the instrument, and output it to the spectral responsivity memory.

[0014] As a further aspect of the present invention, the on-board data processor performs on-orbit real-time calculation of the spectral responsivity through the following steps:

[0015] Background subtraction: This involves subtracting the received blackbody measurement data. Subtract cold air background data Blackbody data after background signal removal for: ;

[0016] Fast Fourier Transform (FFT): Utilizes the FPGA's FFT IP core to process the blackbody data after background subtraction. Perform a Fourier transform to calculate the complex form of the original blackbody spectrum. ;

[0017] Modulus operation: Taking the modulus of the original blackbody spectrum in complex form to obtain the blackbody amplitude spectrum. :

[0018] ;

[0019] Passband spectrum extraction: Extracting a spectral segment from the blackbody amplitude spectrum that matches the instrument response band as the blackbody passband spectrum;

[0020] Response rate calculation: Divide the blackbody passband spectrum by the pre-stored a priori blackbody radiation spectrum to obtain the instrument's spectral responsivity. :

[0021] ;

[0022] In the formula, Given the prior radiation spectrum of a blackbody, based on Planck's blackbody radiation equation and the blackbody passband spectral coordinates... Calculated.

[0023] As a further aspect of the present invention, the complex form of the original blackbody spectrum... It consists of two parts: the real part Real[] and the imaginary part Imag[], where:

[0024] .

[0025] As a further aspect of the present invention, the passband spectrum truncation is performed using an electronic computing device including an FPGA FFT IP core. N Point data sequence x ( n The Fast Fourier Transform (FFT) spectrum of the Nyquist frequency was obtained, with the abscissa extending from zero frequency to the Nyquist frequency. N A discrete point, namely:

[0026] σ =[0,1,2,…, N -1]· δσ

[0027] in, δσ For the spectral coordinate interval, ( N -1)· δσ This is the Nyquist frequency.

[0028] As a further aspect of the present invention δσ according to x ( n ) length N Determined, that is δσ With 1 / N Proportional to, with N Inversely proportional, because N For fixed values, δσ It is also a fixed value and is considered a built-in parameter of the instrument.

[0029] As a further aspect of the present invention, the prior radiation spectrum of the blackbody is used in the response rate calculation. The calculation formula is:

[0030] ;

[0031] In the formula, Planck's constant is =6.626×10 -34 J·s, the speed of light is =2.998×10 8 m / s, Boltzmann constant is =1.38065×10 -23 J / K, Wavenumber represents spectral coordinates, unit: cm -1 , The value is the blackbody temperature.

[0032] As a further aspect of the present invention, the spectral responsivity data stored in the spectral responsivity memory is transmitted to the ground via the on-board data transmission system for analysis and backup, and input into the responsivity threshold comparator for comparison with a set threshold. When the spectral responsivity decays to below the set threshold, the on-board heating and decontamination driver is triggered to heat and remove the substances adsorbed on the surface of the optical lens, thereby restoring the spectral responsivity.

[0033] As a further aspect of the present invention, when the spectral responsivity decays to below a set threshold, the threshold triggering logic for the on-board heating and decontamination actuator is as follows:

[0034] Trigger threshold setting: based on the response rate at the initial stage of instrument launch. Using this as a baseline, calculate the decay rate of the subsequent response rate InsRespi relative to the initial response rate. The calculation formula is:

[0035] ;

[0036] Moving average optimization: for Perform an N-point moving average to reduce noise interference;

[0037] Triggering condition: When If the concentration is below 0.8 for three consecutive days, start the heating and decontamination drive.

[0038] As a further aspect of the present invention, the spectral response rate memory is also used to store response rate threshold setting data and pre-stored a priori blackbody radiation spectrum.

[0039] Compared with existing technologies, the automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector proposed in this invention has the following advantages:

[0040] 1. This invention utilizes FPGA hardware acceleration to directly calculate the spectral responsivity using single blackbody observation data (on the order of seconds), eliminating the need for long-term data accumulation required by traditional sensitivity evaluation techniques. The single calculation provides an instant response. Furthermore, the spectral responsivity can trigger an early warning at the initial stage of pollutant adsorption, while the sensitivity NEdN requires a more severe decay before detection. This invention achieves rapid pollution detection, significantly improving real-time performance and timeliness. The ability to characterize the instrument's detection signal based on the instrument's spectral responsivity leverages the strong and high signal-to-noise ratio characteristics of on-board blackbody spectral signals, allowing for the calculation of a distinctive spectral responsivity from a single blackbody observation.

[0041] 2. This invention utilizes the strong radiation signal from an onboard blackbody to calculate the spectral response rate, and through moving average and continuous multi-day determination, effectively suppresses false triggers caused by single data fluctuations, reduces the false alarm rate, and improves detection sensitivity and noise resistance.

[0042] 3. This invention also implements on-board FFT and arithmetic operations through FPGA hardware, resulting in low spectral response rate calculation time and a small amount of data required for a single response rate calculation, thus reducing on-board storage pressure. The heating and decontamination device only starts after threshold triggering, consuming less energy compared to periodic heating schemes. The entire process from data acquisition, response rate calculation, threshold determination to heating and decontamination is completed automatically on-board, eliminating the need for manual intervention from the ground only when the satellite passes the telemetry and control station. The response delay is reduced from hours to minutes. The ground system can also remotely adjust the trigger threshold, sliding window length, and monitoring channel parameter configuration to adapt to different mission requirements. By modifying the blackbody radiation prior spectral parameters pre-stored in the FPGA, it can support compatible applications of different infrared hyperspectral detectors such as the Fengyun series, solving the problems of poor timeliness, sensitivity lag, and high resource consumption in on-orbit performance monitoring of spaceborne infrared hyperspectral detectors, significantly improving the stability of instrument detection capabilities and satellite mission benefits.

[0043] These or other aspects of this application will become more apparent from the following description of embodiments. It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the scope of this application. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the accompanying drawings used in the description of the exemplary embodiments or related technologies will be briefly introduced below. The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation thereof. In the drawings:

[0045] Figure 1 This is a block diagram of an automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector according to an embodiment of the present invention.

[0046] Figure 2 This is a flowchart illustrating the calculation of spectral response rate in an automatic spectral response rate holding device for a spaceborne infrared hyperspectral detector according to an embodiment of the present invention.

[0047] Figure 3 This is a functional architecture block diagram of an FPGA performing FFT in an automatic spectral response rate holding device for a spaceborne infrared hyperspectral detector according to an embodiment of the present invention.

[0048] Figure 4 This is a schematic diagram of the monitoring and triggering heating for decontamination of the spectral response channel of a spaceborne infrared hyperspectral detector in an automatic spectral response rate maintenance device according to an embodiment of the present invention.

[0049] Figure 5 This is a schematic diagram of the spectral response rate under strong pollution absorption calculated using single blackbody observation data in an automatic spectral response rate holding device for a spaceborne infrared hyperspectral detector according to an embodiment of the present invention.

[0050] Figure 6 This is a schematic diagram of the NEDN spectrum, which is the sensitivity of a spaceborne infrared hyperspectral detector to strong pollution absorption, calculated by statistically analyzing 30 blackbody observation data within 5 minutes, in an automatic spectral response rate holding device according to an embodiment of the present invention.

[0051] Figure 7 This is a schematic diagram of the spectral response rate absorbed by slight contamination in an automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector according to an embodiment of the present invention.

[0052] Figure 8This is a schematic diagram illustrating how the instrument sensitivity does not degrade synchronously when the spectral response rate of a spaceborne infrared hyperspectral detector experiences a slight decrease, according to an embodiment of the present invention. Detailed Implementation

[0053] The present application will now be further described in conjunction with the accompanying drawings and specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0054] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to specific examples and the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0055] It should be noted that all uses of "first" and "second" in the embodiments of the present invention are for the purpose of distinguishing two different entities or different parameters with the same name. Therefore, "first" and "second" are merely for convenience of expression and should not be construed as limiting the embodiments of the present invention. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as other steps or units inherent in a process, method, system, product, or device that includes a series of steps or units.

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0057] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0058] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0059] To address the shortcomings of existing sensitivity evaluation techniques for characterizing and monitoring the on-orbit signal detection capabilities of spaceborne instruments, such as low timeliness, complex calculation methods, and significant susceptibility to calibration source data sample size and noise, this invention proposes an automatic spectral response rate maintenance device for spaceborne infrared hyperspectral detectors. This device characterizes the instrument's signal detection capabilities and maintains the stability of its detection capabilities. By collecting onboard blackbody and cold space background data, performing infrared background signal subtraction and fast Fourier transform spectral calculation, the instrument's response spectrum to blackbody radiation is obtained. Then, based on the prior blackbody radiation spectrum calculated from the blackbody temperature, the instrument's blackbody response spectrum is divided by the prior radiation spectrum to obtain the instrument's spectral response rate data. Calculating the instrument's spectral response rate does not require statistical analysis of a large number of data samples, and the calculation method does not need to consider temperature fluctuations in sensitivity statistics. Therefore, the spectral response rate algorithm is simple, fast, and has good real-time performance, and is easily implemented by onboard data processing equipment (FPGA).

[0060] See Figures 1 to 8 As shown, an embodiment of the present invention provides an automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector, comprising the following components:

[0061] The onboard data processor is used to receive and process onboard blackbody measurement data and cold space background data in real time, and to obtain the spectral responsivity in real time on orbit.

[0062] Spectral response rate memory is used to store the calculated spectral response rate data;

[0063] A response rate threshold comparator is used to compare the calculated spectral response rate with a preset threshold.

[0064] The heating decontamination driver is used to initiate a heating decontamination operation to restore the instrument's spectral response rate when the spectral response rate is lower than a set threshold.

[0065] In this embodiment, the on-board data processor uses a dedicated field-programmable gate array (FPGA) to receive on-board blackbody measurement data and cold-space background data for background subtraction from the on-board data memory. The FPGA is configured with an FFT IP core and an arithmetic unit, which are used to call the FFT IP core and the arithmetic unit to perform infrared background signal subtraction, fast Fourier transform (FFT) spectral calculation on the on-board blackbody measurement data and cold-space background data, and calculate the spectral responsivity of the instrument, and output it to the spectral responsivity memory.

[0066] Since icing and contaminant adsorption are common problems for the cold optical components inside infrared hyperspectral detectors, leading to decreased spectral responsivity and sensitivity degradation, the device of this invention can monitor the attenuation of spectral responsivity to diagnose the instrument's signal detection capability. When the spectral responsivity attenuation exceeds a set threshold, an alarm signal is issued and an on-orbit heating and decontamination device is activated to disperse the substances adhering to the cold optical surfaces, thereby dynamically restoring the instrument's spectral responsivity and sensitivity.

[0067] In this embodiment, see Figure 1 and Figure 2 As shown, the onboard data processor performs on-orbit real-time calculation of the spectral responsivity through the following steps:

[0068] (1) Background subtraction: The received blackbody measurement data Subtract cold air background data Blackbody data after background signal removal for: ;

[0069] (2) Fast Fourier Transform (FFT): Call the FPGA's FFT IP core to process the blackbody data after background subtraction. Perform a Fourier transform to calculate the complex form of the original blackbody spectrum. ;

[0070] Among them, the FFT IP core of Fast Fourier Transform (FFT) serves as the hardware circuit for implementing Fast (Discrete) Fourier Transform (FFT) on the input data. Point discrete data The discrete Fourier transform can be expressed as:

[0071] ;

[0072] in, ; This represents the Fourier transform integral kernel. , This indicates the sequence number of the input discrete data. Indicates a virtual unit. It is a Fourier transform spectrum (complex number), where, see Figure 3 As shown, Figure 3 The diagram shows an FPGA architecture for performing a one-dimensional FFT. In this embodiment, the FPGA for performing the FFT uses an existing FPGA product to build an automatic spectral response rate holding system, which will not be described in detail here.

[0073] (3) Modulus operation: Take the modulus of the original blackbody spectrum in the complex form to obtain the blackbody amplitude spectrum. :

[0074] ;

[0075] Among them, the complex form of the original blackbody spectrum It consists of two parts: the real part Real[] and the imaginary part Imag[], where:

[0076] .

[0077] (4) Passband spectrum extraction: Extract the spectral segment from the blackbody amplitude spectrum that matches the instrument response band as the blackbody passband spectrum;

[0078] In this embodiment, the passband spectrum is truncated using an electronic computing device including an FPGA FFT IP core. N Point data sequence x ( n The Fast Fourier Transform (FFT) spectrum of the Nyquist frequency was obtained, with the abscissa extending from zero frequency to the Nyquist frequency. N A discrete point, namely:

[0079] σ =[0,1,2,…, N -1]· δσ

[0080] In the formula, δσ For the spectral coordinate interval, ( N -1)· δσ That is, the Nyquist frequency; where, δσ according to x ( n ) length N Determined, that is δσ With 1 / N Proportional to, with N Inversely proportional, because N For fixed values, δσ It is also a fixed value and is considered a built-in parameter of the instrument.

[0081] In this embodiment, the electronic computing device (including the FPGA FFT IP core) is used for computation. N Point data sequence x ( n When obtaining the FFT spectrum of a given frequency, the abscissa of the FFT spectrum extends from zero frequency to the Nyquist frequency, totaling [number missing]. N discrete points, i.e. σ =[0,1,2,…, N -1]· δσ , δσFor the spectral coordinate interval, ( N -1)· δσ This is the Nyquist frequency. For the practical application of infrared hyperspectral detectors, δσ depending on x ( n ) length N ,Right now δσ With 1 / N Proportional to, with N Inversely proportional, because N For fixed values, δσ This is also a fixed value and can be considered a built-in parameter of the instrument. Taking a real-world spaceborne infrared hyperspectral detector as an example... δσ 0.5cm -1 , N Since it is 10000, its spectral abscissa is σ =[0,1,2,…,10000-1]·0.5=[0, 0.5, 1.0,…, 4999.5]cm -1 However, the detectors of actual instruments cannot respond to distances of 0–4999.5 cm. -1 Such a wide spectrum, such as Figure 5 The image shows only 600~1200 cm -1 The interval contains valid values, 0~600 cm. -1 and 1200~4999.5 cm -1 The range includes invalid values ​​on the order of noise (which can be simply considered as 0). Since spectral responsivity calculation only requires truncating the blackbody amplitude spectrum... S NetBB The middle corresponds to 600~1200 cm -1 The value of the interval can be used, therefore 600≤ σ The method ≤1200 is used to obtain the discrete sequence index that meets the conditions, such as σ =600 corresponds to the sequence number N1. σ =1200 corresponds to the sequence number N2, then from S NetBB The blackbody passband spectrum is obtained by extracting the segments numbered N1…N2 from the sequence 1~N.

[0082] (5) Response rate calculation: Divide the blackbody passband spectrum by the pre-stored blackbody radiation prior spectrum to obtain the instrument spectral response rate. .

[0083] In the formula, Given the prior radiation spectrum of a blackbody, based on Planck's blackbody radiation equation and the blackbody passband spectral coordinates... Calculated.

[0084] In this embodiment, for the spaceborne infrared hyperspectral detector, the onboard blackbody needs precise temperature control; for example, the blackbody temperature T... BB =300K, so we can use Planck's blackbody radiation equation and the aforementioned blackbody passband spectral coordinates... σ Calculate the prior radiation spectrum of a blackbody within the range [600, 1200]. When calculating the responsivity, the prior radiation spectrum of the blackbody is used. The calculation formula is:

[0085] ;

[0086] In the formula, Planck's constant is =6.626×10 -34 J·s, the speed of light is =2.998×10 8 m / s, Boltzmann constant is =1.38065×10 -23 J / K, Wavenumber represents spectral coordinates, unit: cm -1 , The value is the blackbody temperature. The data is constant and can be pre-calculated and stored in the onboard data storage. Furthermore, the formula for calculating the instrument's spectral responsivity, InsResp, is:

[0087] ;

[0088] As mentioned above, see Figure 4 As shown, σ =800cm -1 This is the spectral channel with the most severe contamination absorption; therefore, the corresponding index (denoted as N3) can be found using the coordinate index lookup method, and InsResp can be extracted. i The value of (800) is monitored. R insr The attenuation of (800) is used to drive and trigger the heating and decontamination device in a timely manner. Figure 4 This is a long-term monitoring graph of the spectral response rate of a spaceborne infrared hyperspectral detector, where the spectral contamination monitoring channel is selected at 801.2 cm⁻¹. -1 1259.29cm -1 2339.2cm -1 Three channels, due to 801.2cm -1The channel was the most severely contaminated, so onboard heating for decontamination was triggered when the channel's spectral responsivity decreased to 0.25. Since the automatic spectral responsivity holding mechanism was not yet fully designed at the time, the threshold limit of 0.25 was too low. This invention, considering both the stability of the instrument's spectral responsivity and the resources consumed by onboard heating for decontamination, proposes that the threshold limit should be set to 0.8.

[0089] In this embodiment, the spectral responsivity data stored in the spectral responsivity memory is transmitted to the ground via the onboard data transmission system for analysis and backup. The data is then input to the responsivity threshold comparator for comparison with a set threshold. When the spectral responsivity decays below the set threshold, the onboard heating and decontamination driver is triggered to heat and remove the substances adsorbed on the surface of the optical lens, thereby restoring the spectral responsivity, which is the instrument's ability to respond to signals.

[0090] Specifically, the threshold triggering logic for the onboard heating and decontamination actuator when the spectral responsivity decays below a set threshold is as follows:

[0091] Trigger threshold setting: based on the response rate at the initial stage of instrument launch. Using this as a baseline, calculate the decay rate of the subsequent response rate InsRespi relative to the initial response rate. The calculation formula is:

[0092] ;

[0093] Moving average optimization: for Perform an N-point moving average to reduce noise interference;

[0094] Triggering condition: When If the concentration is below 0.8 for three consecutive days, start the heating and decontamination drive.

[0095] Here, spectral responsivity is a set of data where the horizontal axis represents wavenumber and the vertical axis represents responsivity, such as... Figure 5 As shown, for example, based on the spectral analysis of pollutants conducted by the ground laboratory before the satellite instrument launch, the pollutants can be measured at a wavenumber of 800 cm⁻¹. -1 It has a strong absorption band at 1050 cm. -1 It exhibits a secondary strong absorption band at 800 cm⁻¹. -1 Taking the strong absorption band as an example, as pollutants accumulate on the optical lenses in orbit, the wavelength at 800 cm⁻¹ in the hyperspectral radiation entering the instrument... -1 The radiation component will be attenuated due to absorption by pollutants, thus failing to reach the detector; the corresponding spectral responsivity is around 800 cm⁻¹. -1The spectral response is also correspondingly low, and continues to decrease. Generally, the instrument's condition and spectral response are best during the initial on-orbit period after satellite launch, at 800 cm⁻¹. -1 The response rate did not decrease significantly, so the initial value was InsResp0 (800) at the beginning of the emission, and the value at subsequent times was recorded as InsResp. i (800), if the ratio of the two is R insr If (800) is less than 1, it indicates that the instrument's spectral response has attenuated, i.e.:

[0096] ;

[0097] Regarding the setting of the spectral response rate threshold, the method used is... R insr (800) = 0.8 is the threshold limit. The specific implementation method is: the instrument calculates InsResp once a day at the same time while in orbit. i (800), and compare it with InsResp0(800) on the first day of launch. If R insr If (800) ≥ 0.8, the onboard heating and decontamination device will not be triggered. R insr If (800) < 0.8, the onboard heating and decontamination device will be triggered. Considering potential calculation errors due to noise, the onboard FPGA can perform an N-point moving average on the spectral response time series stored in memory, i.e. R insr_smooth (800) = smooth( R insr (800)), smooth() is a smoothing function that can be pre-programmed into the FPGA. Therefore, a robust trigger heating decontamination scheme is one where the smoothed response rate ratio is... R insr_smooth (800) If the value is less than 0.8 for three consecutive days, heating to remove dirt will be triggered.

[0098] In this embodiment, the spectral response rate memory is also used to store response rate threshold setting data and pre-stored a priori blackbody radiation spectrum.

[0099] See Figure 5 As shown, characterizing the instrument's ability to detect signals based on its spectral responsivity utilizes the strong and high signal-to-noise ratio characteristics of the onboard blackbody spectral signal. Therefore, a single blackbody observation can yield a spectral responsivity with distinctive features. Since the onboard blackbody observation data is mainly used for radiometric calibration of Earth observation data by the spaceborne infrared hyperspectral detector, its observation period is approximately several seconds, allowing for near real-time spectral responsivity calculation. Figure 5The display shows a distribution between 600 and 1200 cm. -1 An example of the long-wavelength infrared spectral responsivity curve in the range is shown in the figure, which clearly reveals the response at 800 cm⁻¹. -1 and 1050cm -1 At both spectral positions, the spectral response rate exhibits attenuation dips due to the adsorption of contaminants inside the instrument.

[0100] See Figure 6 As shown, when the signal detection capability is characterized based on sensitivity, although blackbody observation data is also used, the noise equivalent radiation variance (NEdN) representing sensitivity cannot be statistically calculated from a single observation. Figure 6 The sensitivity NEDN spectrum shown is the result of statistical analysis of 30 blackbody observations over 5 minutes, at 800 cm⁻¹. -1 and 1050cm -1 At two spectral positions, due to decreased instrument signal detection capability and a low signal-to-noise ratio, the NEdN spectrum exhibits two abnormal peaks. Although NEdN spectral anomalies can also reflect the phenomenon of decreased instrument signal detection capability caused by pollutant adsorption, the responsiveness of statistical analysis every 5 minutes is clearly slower than the spectral response rate of every few seconds. Figure 6 The NEDN data statistics shown in the 5-minute chart are still significantly affected by noise.

[0101] It should be pointed out that, Figure 5 , Figure 6 This example demonstrates how pollutant adsorption leads to a decrease in spectral responsivity and a degradation in instrument sensitivity under conditions of heavy pollutant adsorption. When adsorption is less severe, the sensitivity of the NEdN spectrum is affected by noise and does not readily reflect the decline in the instrument's signal detection capability. Figure 7 The spectral response is shown to be at 800 cm⁻¹ -1 and 1050cm -1 The spectral position has decreased slightly, but Figure 8 The corresponding sensitivity of the NEdN spectrum did not show signs of degradation in a timely manner, demonstrating the advantage of spectral responsivity as a better indicator of an instrument's signal detection capability than instrument sensitivity itself. Figure 7 When the adsorption of pollutants is low, the spectral response is at 800 cm⁻¹. -1 and 1050cm -1 The position has slightly decreased; Figure 8 The spectral response rate showed a slight decrease, but the instrument sensitivity did not degrade accordingly.

[0102] Therefore, using spectral responsivity to characterize the instrument's ability to detect radiation signals has better speed and sensitivity, and is more suitable for computing conditions where onboard computing resources are limited. When pollutants accumulate to the point that the spectral responsivity drops below a set threshold, the device of this invention can promptly activate the onboard heating and decontamination device to restore the spectral responsivity, thereby ensuring the stability of the instrument's signal detection capability.

[0103] It should be noted that: Figure 3 The distribution calculated according to the formula is between 600 and 1200 cm. -1 The spectral responsivity InsResp in the range is an example calculated from real data of a spaceborne infrared hyperspectral detector.

[0104] Figure 4 This method uses NEDN sensitivity to determine whether a spectral channel is contaminated. If the spectral channel is not severely contaminated, its spectral responsivity is as follows: Figure 5 As shown (note 800cm) -1 There are no obvious depressions nearby caused by pollution absorption, corresponding to NEDN, such as Figure 6 As shown (800cm) -1 There are no protrusions nearby); if the spectral channel is severely contaminated, Figure 3 InsResp at 800cm -1 A noticeable depression appeared nearby, corresponding to Figure 4 The NEDN spectrum is also at 800 cm⁻¹ -1 A noticeable bulge appeared nearby. Figures 3-6 In summary, when contamination absorption is severe, both the InsResp depression and the NEDN protrusion can be used to determine that the instrument is contaminated and its response performance has deteriorated (example shown). Figures 3-4 However, when the contamination is not very severe, such as after each heating and decontamination process, InsResp from Figure 3 Restore to Figure 5 And in the early stages of the next round of degradation, InsResp may have already developed a slight indentation ( Figure 5 However, NEDN did not produce a significant bulge. Figure 6 This demonstrates that using NEdN to determine the degradation of instrument response performance is less sensitive than using InsResp. For example, if InsResp has decayed to below 0.8 of its initial value, while NEdN has not changed significantly, this is detrimental to maintaining the long-term stability of instrument performance if heating for cleaning is not triggered. Therefore, this invention proposes using InsResp parameter data to maintain the long-term stability of instrument performance, which has a sensitivity advantage over the original method of using NEdN degradation as a criterion. Furthermore, calculating NEdN requires a large amount of data samples (using blackbody spectroscopy). S BBThe formula for calculating NEDN is as follows. Ground-based analytical instruments typically need to accumulate data for one orbit of the satellite (approximately 102 minutes). If implemented on-board, this would consume a large amount of computing and storage resources from onboard FPGAs and other computing devices, and the sample accumulation time would be relatively long (collecting 102 minutes of data, as is the case with ground-based NEDN calculations, would be a significant overhead for onboard computing devices). In contrast, calculating InsResp does not require accumulating a large number of samples. For example, if a blackbody is observed onboard every 8 seconds, InsResp can be calculated using only the spectrum from the blackbody observation. This places a much lighter burden on onboard computing devices, and the calculation time is relatively faster.

[0105] ;

[0106] in, M Where j is the total sample size, and j is the sample number. This indicates that the average of the samples is taken.

[0107] Therefore, this invention designs an automatic on-board spectral response rate maintenance device for an infrared hyperspectral detector using InsResp attenuation as the criterion. Comparing the instrument response performance attenuation detection sensitivity and on-board computing efficiency, the InsResp attenuation criterion is more advantageous than the commonly used NEdN degradation criterion.

[0108] This invention utilizes FPGA hardware acceleration to directly calculate the spectral responsivity using single blackbody observation data (on the order of seconds), eliminating the need for long-term data accumulation required by traditional sensitivity evaluation techniques. The single calculation provides an instant response. Furthermore, the spectral responsivity can trigger an early warning at the initial stage of pollutant adsorption, while the sensitivity NEdN requires significant attenuation before detection. This invention achieves rapid pollution detection with significant real-time performance and timeliness. It leverages the strong and high signal-to-noise ratio of onboard blackbody spectral signals to characterize the instrument's ability to detect signals, allowing for the calculation of a distinctive spectral responsivity from a single blackbody observation.

[0109] This invention utilizes the strong radiation signal from an onboard blackbody to calculate the spectral response rate, and through moving average and continuous multi-day determination, effectively suppresses false triggers caused by single data fluctuations, reduces the false alarm rate, and improves detection sensitivity and noise resistance.

[0110] This invention also implements on-board FFT and arithmetic operations through FPGA hardware, resulting in low spectral response rate calculation time and a small amount of data required for a single response rate calculation, thus reducing on-board storage pressure. The heating and decontamination device only starts after a threshold trigger, consuming less energy compared to periodic heating schemes. The entire process from data acquisition, response rate calculation, threshold determination to heating and decontamination is completed automatically on-board, eliminating the need for manual intervention from the ground only when the satellite passes the telemetry and control station. The response delay is reduced from hours to minutes. The ground system can also remotely adjust the trigger threshold, sliding window length, and monitoring channel parameter configuration to adapt to different mission requirements. By modifying the blackbody radiation prior spectral parameters pre-stored in the FPGA, it can support the compatible application of different infrared hyperspectral detectors such as the Fengyun series. This solves the problems of poor timeliness, sensitivity lag, and high resource consumption in on-orbit performance monitoring of spaceborne infrared hyperspectral detectors, significantly improving the stability of instrument detection capabilities and the benefits of satellite missions.

[0111] It should be noted that: the on-board data processor of this invention uses a dedicated FPGA, but a Digital Signal Processor (DSP) can be used as an alternative; steps 1) and 2) of the algorithm for calculating the spectral responsivity of this invention first subtract the cold space data from the blackbody data to achieve background subtraction, and then perform FFT spectral calculation. An alternative could be to first perform FFT spectral calculation on the blackbody data and the cold space data separately, and then subtract the blackbody spectrum from the cold space spectrum to achieve the same effect of background subtraction. Steps 4) and 5) of the algorithm for calculating the spectral responsivity of this invention first extract the spectrum from the blackbody amplitude spectrum that matches the instrument's response band as the blackbody passband spectrum, and then calculate the spectral responsivity. An alternative could be to first calculate the full-band spectral responsivity using the blackbody amplitude spectrum, and then extract the passband spectral responsivity that matches the instrument's response band, thus achieving the same effect as this invention; this invention uses monitoring the trend of spectral responsivity changes to automatically maintain the instrument's signal detection capability, but an alternative could be to monitor the instrument's sensitivity on-board to automatically maintain the instrument's signal detection capability. While alternative solutions may differ in form from this invention, they do not possess the same advantages in sensitivity and timeliness. Any other alternative solution that meets at least one of the above conditions is considered to conflict with this invention and will not be protected.

[0112] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.

[0113] It should be understood that, as used herein, the singular form "a" is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, "and / or" refers to any and all possible combinations of one or more of the associatedly listed items. The embodiment numbers disclosed above are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0114] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. An automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector, characterized in that, include: The onboard data processor is used to receive and process onboard blackbody measurement data and cold space background data in real time, and to obtain the spectral responsivity in real time on orbit. Spectral response rate memory is used to store the calculated spectral response rate data; A response rate threshold comparator is used to compare the calculated spectral response rate with a preset threshold. A heating decontamination driver is used to initiate a heating decontamination operation to restore the instrument's spectral responsivity when the spectral responsivity is below a set threshold. The on-board data processor uses a dedicated field-programmable gate array (FPGA) to receive on-board blackbody measurement data and cold space background data for background subtraction from the on-board data memory. The FPGA is equipped with an FFT IP core and an arithmetic unit, which are used to call the FFT IP core and the arithmetic unit to perform infrared background signal subtraction and fast Fourier transform spectral calculation on the on-board blackbody measurement data and cold space background data, and calculate the spectral responsivity of the instrument, and output it to the spectral responsivity memory. The on-board data processor performs real-time on-orbit calculation of the spectral responsivity through the following steps: Background subtraction: This involves subtracting the received blackbody measurement data. Subtract cold air background data Blackbody data after background signal removal for: ; Fast Fourier Transform: Utilizing the FPGA's FFT IP core to process the blackbody data after background subtraction. Perform a Fourier transform to calculate the complex form of the original blackbody spectrum. ; Modulus operation: Taking the modulus of the original blackbody spectrum in complex form to obtain the blackbody amplitude spectrum. : ； Passband spectrum extraction: Extracting a spectral segment from the blackbody amplitude spectrum that matches the instrument response band as the blackbody passband spectrum; Response rate calculation: Divide the blackbody passband spectrum by the pre-stored a priori blackbody radiation spectrum to obtain the instrument's spectral responsivity. : ； In the formula, Given the prior radiation spectrum of a blackbody, based on Planck's blackbody radiation equation and the blackbody passband spectral coordinates... Calculated.

2. The automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector as described in claim 1, characterized in that, Complex form of the original spectrum of a blackbody It consists of two parts: the real part Real[] and the imaginary part Imag[], where: 。 3. The automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector as described in claim 2, characterized in that, Passband spectrum extraction is performed using electronic computing devices including FPGA FFT IP cores. N Point data sequence x ( n The Fast Fourier Transform (FFT) spectrum of the Nyquist frequency was obtained, with the abscissa extending from zero frequency to the Nyquist frequency, totaling [number missing]. N A discrete point, namely: σ =[0,1,2,…, N -1]· δσ in, δσ For the spectral coordinate interval, ( N -1)· δσ This is the Nyquist frequency.

4. The automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector as described in claim 3, characterized in that, δσ according to x ( n ) length N Determined, that is δσ With 1 / N Proportional to, with N Inversely proportional, because N For fixed values, δσ It is also a fixed value and is considered a built-in parameter of the instrument.

5. The automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector as described in claim 4, characterized in that, When calculating the responsivity, the prior radiation spectrum of the blackbody is used. The calculation formula is: ； In the formula, Planck's constant is =6.626×10 -34 J·s, the speed of light is =2.998×10 8 m / s, Boltzmann constant is =1.38065×10 -23 J / K, Wavenumber represents spectral coordinates, unit: cm -1 , The value is the blackbody temperature.

6. The automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector as described in claim 5, characterized in that, The spectral responsivity data stored in the spectral responsivity memory is transmitted to the ground via the onboard data transmission system for analysis and backup. It is then input into the responsivity threshold comparator for comparison with a set threshold. When the spectral responsivity decays below the set threshold, the onboard heating and decontamination driver is triggered to heat and remove the substances adsorbed on the surface of the optical lens, thereby restoring the spectral responsivity.

7. The automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector as described in claim 6, characterized in that, When the spectral responsivity decays below a set threshold, the threshold triggering logic for the onboard heating and decontamination actuator is as follows: Trigger threshold setting: based on the response rate at the initial stage of instrument launch. Using this as a baseline, calculate the decay rate of the subsequent response rate InsRespi relative to the initial response rate. The calculation formula is: ； Moving average optimization: for Perform an N-point moving average to reduce noise interference; Triggering condition: When If the concentration is below 0.8 for three consecutive days, start the heating and decontamination drive.

8. The automatic spectral response rate maintenance device for a spaceborne infrared hyperspectral detector as described in claim 1, characterized in that, The spectral response rate memory is also used to store response rate threshold setting data and pre-stored a priori blackbody radiation spectra.

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