阅读说明：本技术 一种红外高光谱干涉仪关键定标参数在轨优化方法 (On-orbit optimization method for key calibration parameters of infrared hyperspectral interferometer ) 是由 陆其峰 倪卓娅 徐一树 吴春强 王富 于 2021-08-18 设计创作，主要内容包括：一种红外高光谱干涉仪关键定标参数在轨优化方法,包括以下步骤：根据仪器参数和定标参数,建立红外高光谱干涉仪的观测与定标仿真模型；构建表示度量观测值与理想值之间距离的代价函数；求解所述代价函数关于关键辐射定标参数的梯度；利用最优化算法求得控制变量的最优值。本发明的红外高光谱干涉仪关键定标参数在轨优化方法,通过仪器定标后的观测数据与参考数据,利用变化同化的方法,寻找定标参数的最优解,思路清晰,方法简单可行,提高了在轨定标精度。(An on-orbit optimization method for key calibration parameters of an infrared hyperspectral interferometer comprises the following steps: establishing an observation and calibration simulation model of the infrared hyperspectral interferometer according to the instrument parameters and the calibration parameters; constructing a cost function representing the distance between the measurement observed value and the ideal value; solving the gradient of the cost function about the key radiometric calibration parameter; and (4) obtaining the optimal value of the control variable by using an optimization algorithm. According to the on-orbit optimization method for the key calibration parameters of the infrared hyperspectral interferometer, the optimal solution of the calibration parameters is found by using the change assimilation method through the observation data and the reference data after the instrument calibration, the thought is clear, the method is simple and feasible, and the on-orbit calibration precision is improved.)

1. An on-orbit optimization method for key calibration parameters of an infrared hyperspectral interferometer is characterized by comprising the following steps of:

establishing an observation and calibration simulation model of the infrared hyperspectral interferometer according to the instrument parameters and the calibration parameters;

constructing a cost function representing the distance between the measurement observed value and the ideal value;

solving the gradient of the cost function about the key radiometric calibration parameter;

and (4) obtaining the optimal value of the control variable by using an optimization algorithm.

2. The method of claim 1, wherein the observation and calibration simulation model is formulated as:

wherein x is a control variable and R is a radiometric calibration result.

3. The method according to claim 1, wherein the step of establishing an observation and calibration simulation model of the infrared hyperspectral interferometer based on the instrument parameters and the calibration parameters further comprises,

acquiring an ideal interferogram of input energy according to the input RTTOV simulated spectrum;

obtaining an ideal spectrum corresponding to the ideal interference pattern;

adding off-axis effect to obtain a spectrum containing the off-axis effect;

adding nonlinearity to obtain a spectrum containing an off-axis effect and a nonlinear effect;

obtaining an off-axis corrected spectrum according to the spectrum containing the off-axis effect and the nonlinear spectrum;

carrying out non-linear correction on the off-axis corrected spectrum to obtain an off-axis effect and a non-linear effect corrected spectrum;

and carrying out radiometric calibration on the corrected spectrum, and constructing a complete observation and calibration simulation model.

4. The method of claim 3, wherein said step of scaling said off-axis and non-linear effect corrected spectra for radiometric calibration to create an observation and calibration simulation model further comprises radiometric calibration with a low temperature target and a high temperature target using three-point calibration.

5. The method of claim 1, wherein the step of constructing a cost function representing a measure of the distance between the observed value and the ideal value further comprises constructing the cost function as:

where J is the cost function, D is the ideal calibration radiation, which corresponds to the reference calibration radiation, R (x, c) is calculated from the given initial calibration parameters, W is the weight coefficient, x is the control variable, and c is the parameter in the calibration model.

6. The method of claim 5, further comprising the step of iteratively satisfying a decreasing of the cost function to obtain an optimal value of the control variable.

7. The method of claim 1, wherein said step of solving a gradient of said cost function with respect to a key radiometric calibration parameter, further comprises,

deriving the cost function, wherein the gradient of the cost function with respect to the control variable x is:

wherein the content of the first and second substances,is the first order partial derivative of the observation and calibration simulation model R with respect to the control variable X, D is the ideal calibration radiation, and W is the weight coefficient.

8. The method of claim 1, wherein said step of solving a gradient of said cost function with respect to a key radiometric calibration parameter, further comprises,

and selecting the blackbody temperature, the blackbody emissivity and the nonlinear parameters as key radiation calibration parameters, and obtaining a Jacobian matrix by the observation and calibration simulation model.

9. An electronic device, comprising a memory and a processor, wherein the memory stores a computer program running on the processor, and the processor executes the steps of the method for on-orbit optimization of key calibration parameters of an infrared hyperspectral interferometer according to any of claims 1 to 8 when running the computer program.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that said computer program is adapted to execute the steps of the method for on-orbit optimization of key calibration parameters of an infrared hyperspectral interferometer according to any of the claims 1 to 8 when running.

Technical Field

The invention relates to the technical field of infrared interferometers, in particular to an on-orbit optimization method for key calibration parameters of an infrared hyperspectral interferometer.

Background

Under the condition of the performance of the existing instrument, the optimization of the instrument calibration process is important to improve the data precision. In the ground vacuum test, part of the parameters are generally measured by a measurement mode, but the measurement mode is difficult and expensive, and whether the ground measurement parameters can be used after the satellite is in orbit needs to be reevaluated. When the ground measurement is carried out, the change of one parameter is considered at a time, other parameters are fixed, and the measurement result can be regarded as a special solution. As a practical matter, most of the instrument parameters change and cannot be measured after the satellite is in orbit, and need to be estimated by the parameters of the in-orbit data. At present, single parameters are mainly considered in the parameter estimation of on-orbit data, such as nonlinear parameter estimation, instrument polarization estimation, internal blackbody radiation model establishment and the like. In fact, the errors caused by the variation of the instrument parameters are coupling errors caused by the variation of a plurality of parameters.

In the prior art, due to the difference between the on-orbit state of the instrument and the vacuum state of a laboratory, errors may be brought when laboratory calibration parameters are used for on-orbit data calibration, the acquisition cost of the laboratory calibration parameters is high, and the calibration parameters cannot be directly obtained after the instrument is in orbit. After the satellite is in orbit, available data mainly comprises instrument parameters measured in a laboratory and satellite observation data, and on the basis of the existing data, a method capable of solving errors of a coupling instrument is urgently needed to solve the common problem and is suitable for errors of the coupling instrument of any control parameter change combination.

Disclosure of Invention

In order to solve the defects in the prior art, the invention aims to provide an on-orbit optimization method for key calibration parameters of an infrared hyperspectral interferometer detector.

In order to achieve the aim, the in-orbit optimization method for the key calibration parameters of the infrared hyperspectral interferometer detector provided by the invention comprises the following steps:

establishing an observation and calibration simulation model of the infrared hyperspectral interferometer according to the instrument parameters and the calibration parameters;

constructing a cost function representing the distance between the measurement observed value and the ideal value;

solving the gradient of the cost function about the key radiometric calibration parameter;

and (4) obtaining the optimal value of the control variable by using an optimization algorithm.

Further, the formula of the observation and calibration simulation model is as follows:

R＝H(x，c)

wherein x is a control variable and R is a radiometric calibration result.

Further, the step of establishing an observation and calibration simulation model of the infrared hyperspectral interferometer according to the instrument parameters and the calibration parameters also comprises the steps of,

acquiring an ideal interferogram of input energy according to the input RTTOV simulated spectrum;

obtaining an ideal spectrum corresponding to the ideal interference pattern;

adding off-axis effect to obtain a spectrum containing the off-axis effect;

adding nonlinearity to obtain a spectrum containing an off-axis effect and a nonlinear effect;

obtaining an off-axis corrected spectrum according to the spectrum containing the off-axis effect and the nonlinear spectrum;

carrying out non-linear correction on the off-axis corrected spectrum to obtain an off-axis effect and a non-linear effect corrected spectrum;

and carrying out radiometric calibration on the corrected spectrum, and constructing a complete observation and calibration simulation model.

Further, the step of performing calibration radiation on the spectrum after the off-axis effect and the nonlinear effect are corrected and constructing an observation and calibration simulation model further comprises the step of performing radiation calibration through a low-temperature target and a high-temperature target by adopting three-point calibration.

Further, the step of constructing a cost function representing a distance between the measurement observation value and the ideal value further includes the step of constructing the cost function as:

where J is the cost function, D is the ideal calibration radiation, which corresponds to the reference calibration radiation, R (x, c) is calculated from the given initial calibration parameters, W is the weight coefficient, x is the control variable, and c is the parameter in the calibration model.

Further, the method also comprises a step of obtaining the optimal value of the control variable by iterating to continuously reduce the cost function.

Further, the step of solving the gradient of the cost function with respect to the key radiometric calibration parameter further comprises,

deriving the cost function, wherein the gradient of the cost function with respect to the control variable x is:

wherein, A (X)₀) Is the first order partial derivative of the observation and calibration simulation model R with respect to the control variable X, D is the ideal calibration radiation, and W is the weight coefficient.

Further, the step of solving the gradient of the cost function with respect to the key radiometric calibration parameter further comprises,

and selecting the blackbody temperature, the blackbody emissivity and the nonlinear parameters as key radiation calibration parameters, and obtaining a Jacobian matrix by the observation and calibration simulation model.

In order to achieve the above object, the present invention further provides an electronic device, which includes a memory and a processor, where the memory stores a computer program running on the processor, and the processor executes the computer program to execute the steps of the in-orbit optimization method for key calibration parameters of an infrared hyperspectral interferometer detector as described above.

To achieve the above object, the present invention further provides a computer-readable storage medium having stored thereon a computer program which, when executed, performs the steps of the method for on-orbit optimization of key calibration parameters of an infrared hyperspectral interferometer detector as described above.

Compared with the prior art, the on-orbit optimization method for the key calibration parameters of the infrared hyperspectral interferometer detector has the following beneficial effects:

quantitatively analyzing the deviation of different calibration parameters from calibration errors by using the observation data and the reference data; by adopting the idea of variation assimilation, based on an infrared hyperspectral interferometer observation and calibration simulation model, a cost function of observation data and reference data is constructed, the gradient of the cost function about a key calibration parameter is solved, the optimal value of the calibration parameter is obtained through the most optimized algorithm, calibration radiation corresponding to the optimal value, the initial value and the reference value of the calibration parameter is compared, and the improvement of the calibration precision of the optimized value of the calibration parameter relative to the initial value is obvious.

Due to the difference between the on-orbit state of the instrument and the vacuum state of the laboratory, when the laboratory calibration parameters are used for on-orbit data calibration, errors can be caused, the acquisition cost of the laboratory calibration parameters is high, and the calibration parameters cannot be directly obtained after the instrument is in orbit. The patent provides a simple and easy scheme, and the optimal solution of calibration parameters is found by changing and assimilating the observation data and the reference data after instrument calibration, so that the on-orbit calibration precision is improved.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

Drawings

The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

FIG. 1 is a flow chart of an in-orbit optimization method for key calibration parameters of an infrared hyperspectral interferometer according to the invention;

FIG. 2 is a flow chart of a method for constructing an observation and calibration simulation model according to the present invention;

FIG. 3 is a schematic diagram of the variation of the cost function and gradient versus iteration number according to the present invention;

FIG. 4 is a graph illustrating a comparison between a calibrated bright temperature difference after optimization of calibration parameters and a calibrated bright temperature difference corresponding to an initial value according to the present invention;

fig. 5 is a schematic structural diagram of an electronic device according to the present invention.

Detailed Description

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.

The method for optimizing key calibration parameters of the infrared hyperspectral interferometer in orbit is based on a simulation and calibration model of the infrared hyperspectral interferometer, gives Jacobian matrixes of calibration radiation to different key calibration parameters by using a variational assimilation method, constructs a cost function by using the calibration radiation and a reference radiation value, and obtains the optimized values of the key calibration parameters by an optimization method. Because the state of the instrument after the satellite is in orbit is different from the state of the laboratory, part of key calibration parameters bring calibration errors, and the real calibration parameters are difficult to obtain. The variation and assimilation is an analysis method for fusing multi-source observation data which are irregularly distributed in space and time into a numerical prediction mode based on physical laws. The application of the variation assimilation method in the optimization of the calibration parameters of the infrared hyperspectral interferometer is to optimize key calibration parameters by using an observation and calibration simulation model of infrared hyperspectrum as a constraint condition and using the calibrated observation radiance, and infer the variation of the key calibration parameters from a calibration result.

Example 1

Fig. 1 is a flowchart of an in-orbit optimization method for key calibration parameters of an infrared hyperspectral interferometer according to the invention, and the in-orbit optimization method for key calibration parameters of the infrared hyperspectral interferometer of the invention is described in detail with reference to fig. 1.

Firstly, in step 101, an observation and calibration simulation model of the infrared hyperspectral interferometer is established according to the instrument parameters and the calibration parameters.

In the embodiment of the invention, an observation and calibration simulation model of the infrared hyperspectral interferometer is established based on the working principle of the infrared hyperspectral interferometer and a calibration theoretical model. The instrument effects that are mainly considered are off-axis effects and non-linear effects. The off-axis effect shifts the spectrum towards the lower wavenumber end. Due to material and process limitations, the detectors exhibit non-linearity, resulting in-band energy loss of the observed spectrum and small energy signals out-of-band, requiring a reduction in energy loss through non-linear correction.

At step 102, a cost function is constructed that represents a distance between the measured observation and the ideal.

In the embodiment of the invention, assuming that an observation and calibration simulation model of infrared hyperspectrum is as formula 1, the calibration radiation is regarded as a function with a radiometric calibration equation H as constraint:

r ═ H (x, c) formula 1

Wherein x is a control variable in the model and represents a variable key calibration parameter (such as a nonlinear coefficient, blackbody emissivity, blackbody temperature and the like) in the calibration process, R represents a radiometric calibration result and is called a dependent variable, and c represents a parameter in the calibration model. On the basis, calibration radiation corresponding to an ideal calibration parameter is defined as an ideal value D, calibration radiation corresponding to an actual calibration parameter is defined as an observed value R, a cost function J is used for measuring the distance between the observed value and the ideal value, the smaller the cost function value is, the better the approximation degree between the observed value and an ideal reference value is, x is a control variable, and the cost function can be defined as:

where the ideal calibration radiation D corresponds to the reference calibration radiation and is known, R (x, c) is calculated given initial calibration parameters, W is a weighting factor, the value of which varies with the control variable. The core of data assimilation is that the cost function is continuously reduced through iteration, the optimal value of x is obtained, wherein x mainly refers to a nonlinear coefficient, the black body emissivity and the black body temperature, and the optimized value of x is as follows:

Y^(k+1)＝X^(k)-λ^(k)[A(X^(k))]^TW[R(X^(k))-D]equation 3

Wherein k is the iteration number, and λ is the iteration step length. The problem is then a one-dimensional search problem, and a suitable step length is found to enable the cost function corresponding to the calibration parameter after iteration to quickly fall to the minimum value.

At step 103, the gradient of the cost function with respect to the key radiometric calibration parameter is solved.

In the embodiment of the present invention, as a derivative of formula 2, the gradient of the cost function with respect to the control variable x may be represented as:

equation 4 illustrates that the gradient of the cost function with respect to the control variable can be solved by observing and scaling the adjoint matrix of the Jacobian matrix of the simulation model, where A (X)₀) The first-order partial derivative of an observation and calibration simulation model R relative to a control variable X is also called a Jacobian matrix, the approximation degree of different control variables to a model result is represented, the Jacobian matrix defines the influence of the change of the control variables on a dependent variable, and the change of calibration radiation can be observed by adding small disturbance on the basis of an initial calibration parameter.

A^*Is the companion matrix of matrix a. The spatial inner product of the vectors also reflects the conversion between different vectors with equal Hilbert spatial inner products. By means of the adjoint matrix, the gradient of the cost function defines the influence of the perturbation of the dependent variable on the control variable, i.e. the shift of the key scaling parameter can be deduced from the variation of the scaling radiation. After the satellite is in orbit, the state of the satellite is different from the ground vacuum environment, and calibration errors can be introduced by using calibration parameters measured by the ground vacuum environment. The concomitant assimilation method provides a way to estimate the critical scaling parameter offset from the target's scaled radiometric error and is able to separate the offsets of different critical scaling parameters from the coupled scaling errors.

Calibration parameters related in the radiation calibration process mainly include black body emissivity and black body temperature T_ICTBlack body ambient temperature, cold air emissivity, coldAir temperature, cold air ambient temperature. The blackbody temperature T is chosen here in view of the fact that blackbody radiation is of a much larger magnitude than cold air radiation_ICTBlack body emissivity eict and nonlinear parameter alpha₂As three key radiometric calibration parameters, the Jacobian matrix obtained by the observation and calibration simulation model is as follows:

wherein C represents a nonlinear spectrum, Cco represents a nonlinear corrected spectrum, V represents a direct current voltage corresponding to the nonlinear spectrum, wherein C1 and C2 are first and second radiation constant targets, ES represents ground, DS represents cold air, ICT represents black body, R represents black body, and C represents a linear constant target_ESRepresenting the ground-scaled radiation.

At step 104, an optimization algorithm is used to find an optimal value for the control variable x.

In the embodiment of the invention, based on formulas 2, 3 and 5, an optimization algorithm (one-dimensional search algorithm) is used for obtaining the optimal value of x.

FIG. 3 is a schematic diagram of the variation of the cost function and the gradient to the iteration number according to the present invention, as shown in FIG. 3, showing that the cost function gradually approaches 0 and stops iteration as the iteration number increases in the iteration process; the gradient change of the cost function about the calibration parameter black body temperature is given, and the gradient about the calibration parameter gradually tends to 0 along with the increase of the iteration times; the gradient change of the cost function about the blackbody emissivity is given, and the gradient about the calibration parameter gradually tends to 0 along with the increase of the iteration times; given the gradient variation of the cost function with respect to the non-linear coefficients, the gradient with respect to the scaling parameter gradually goes to 0 as the number of iterations increases.

Table 1 shows the comparison of the iteration of the scaling parameters from the initial values to the optimal values with the reference values. As the number of iterations increases, the scaling parameter gradually approaches the reference value from the initial value. This procedure illustrates that the variation of the scaling parameter can be estimated from the variation of the scaling radiation, finding the optimal value of the scaling parameter.

TABLE 1 comparison of iteration values of scaling parameters with reference values

In the embodiment of the invention, table 1 shows the comparison of the change of the value in the iteration process of the calibration parameter and the reference calibration parameter, the initial calibration parameter and the optimal calibration parameter are substituted into the calibration equation to obtain the observation calibration radiation, and the observation calibration radiation is compared with the reference calibration radiation respectively, and the brightness temperature deviation is as shown in fig. 4. The brightness temperature deviation corresponding to the initial value is found to be about-0.5K, and the brightness temperature deviation corresponding to the optimized calibration parameter is found to be about 0K.

Fig. 2 is a flow chart of observation and calibration simulation model construction according to the present invention, and the following describes in detail the work flow of observation and calibration simulation model construction according to the present invention with reference to fig. 2.

In step 201, an ideal interferogram of the input energy is obtained according to the input RTTOV simulated spectrum.

In step 202, fourier transform is performed on the interferogram to obtain an ideal spectrum corresponding to the ideal interferogram.

In step 203, an off-axis factor matrix is calculated according to the off-axis effect of the probe element, and the off-axis factor matrix is multiplied by the ideal spectrum to obtain a spectrum containing the off-axis effect.

In step 204, a spectrum containing nonlinear effects is calculated based on the nonlinear principle, the nonlinear relationship between the input light intensity and the output light intensity. In step 205, the spectrum after off-axis correction is obtained by multiplying the spectrum containing the off-axis effect and the nonlinear spectrum by the inverse matrix of the off-axis correction matrix.

In step 206, the currently used spectrum nonlinear correction using out-of-band wavelets is selected to obtain the corrected spectrum of the off-axis effect and the nonlinear effect.

In step 207, the spectrum after off-axis effect and non-linear effect correction is radiometrically calibrated, and an observation and calibration simulation model is constructed.

In the embodiment of the invention, three-point calibration is adopted for radiometric calibration, and radiometric calibration is carried out through a low-temperature target and a high-temperature target (calibration black body), wherein the calibration formula is as follows:

R_ICT＝ε_ICTB(T_ICT)+(1-ε_ICT)B(T_ICT，env)

R_DS＝ε_DSB(T_DS)+(1-ε_DS)B(T_DS，env)

R_ICTrepresenting the actual radiation, epsilon, of the black body_ICTEmissivity of black body, B (T)_ICT) Represents the Planckian radiation dose, B (T), of a black body_ICT,env) Planck radiation, R, caused by black body environment_DSRepresenting the actual radiation, epsilon, of the cold air_DSShows the cold air emissivity, B (T)_DS) Planck radiation energy, B (T) representing cold air_DS,env) Representing the Brookfield energy, R, of a cold air environment_ESActual radiation observed to earth

Example 2

An embodiment of the present invention further provides an electronic device, fig. 5 is a schematic structural diagram of an electronic device according to the present invention, and as shown in fig. 5, the electronic device 50 of the present invention includes a processor 501 and a memory 502, wherein,

the memory 502 stores a computer program which, when being read and executed by the processor 501, executes the steps of the above-mentioned embodiment of the on-orbit optimization method for key calibration parameters of the infrared hyperspectral interferometer.

Example 3

Embodiments of the present invention further provide a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the steps in the above-mentioned embodiment of the method for in-orbit optimization of key calibration parameters of an ir-ht-spectroscopy interferometer when running.

In this embodiment, the computer-readable storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.

Those of ordinary skill in the art will understand that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.