A method for fast compensation of drift in an infrared radiation calibration system

Abstract

The application discloses a drift fast compensation method for an infrared radiation calibration system, which is based on two ambient temperature calibrations and two test distance calibrations, and is used for correcting temperature drift and path attenuation respectively. The blackbody temperature, the ambient temperature and the test distance are set to have at least two values respectively. In the linear response interval of the detector of the infrared radiation calibration system, the values of two factors are fixed, the infrared image gray values of the blackbody at the two values of the third factor are obtained, and at least four infrared image gray values are obtained. The expression equations of the four infrared image gray values are solved to obtain the blackbody radiation brightness response, the temperature drift compensation coefficient, the distance drift coefficient and the detector response bias. According to the solving result, the fast compensation of the gray value attenuation caused by the changes of the ambient temperature and the test distance is realized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of optics and photonics, and relates to infrared radiation measurement, in particular to a drift fast compensation method for an infrared radiation calibration system. BACKGROUND

[0002] The infrared radiation calibration system is a system for measuring and analyzing the infrared radiation emitted or reflected by an object, which can be used for temperature measurement, infrared imaging, infrared spectrum analysis and other applications. The work of radiation calibration is to fit the relationship between the input infrared radiation and the output image gray value, obtain the corresponding calibration coefficient of the system, and further inversely calculate the incident radiation characteristics of the target according to the output image gray value.

[0003] The change of ambient temperature during calibration and measurement will cause the output gray drift of the infrared imaging system, which limits the accuracy of radiation measurement, so it is usually required that calibration and measurement are carried out under the same stable environmental conditions. In fact, the calibration process of the infrared system is often cumbersome, but the measurement task requires a short time, which leads to the fact that calibration and measurement cannot be carried out at the same time, and even due to the limitation of field conditions, the calibration process can only be completed in advance in the laboratory. Therefore, the calibration duration is long, and the interval time between calibration and measurement can also be long, and the drift caused by the temperature change during calibration and the drift caused by the difference of ambient temperature between calibration and measurement will affect the accuracy of radiation measurement. In addition, if the duration of the radiation measurement task is long, the change of ambient temperature in this period of time will also affect the measurement accuracy, and the output gray drift at each time is difficult to predict. In practical applications, the calibration coefficient is fixedly used to quantitatively detect the target, although the temperature of the target is weakly related to the imaging distance, but the spectral recognition characteristics of the target are extremely weak with the increase of the imaging distance, and if the traditional radiation characteristic measurement idea is used, the same calibration parameters will be used at different imaging distances, which will increase the temperature measurement error of the target. SUMMARY

[0004] In order to overcome the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide a drift fast compensation method for an infrared radiation calibration system, so as to quickly compensate the infrared image measurement error caused by temperature drift and measurement distance drift.

[0005] In order to achieve the above-mentioned purpose, the technical scheme adopted by the present application is:

[0006] A drift fast compensation method for an infrared radiation calibration system, the response output of the infrared radiation calibration system under different ambient temperatures is constructed, the integration time of the infrared detection system is fixed, the infrared radiation calibration system is calibrated at a short distance for an extended source at two ambient temperatures respectively, two infrared image gray values are obtained, and the temperature drift compensation coefficient R is obtained by simultaneous solution. s; construct the response output of the infrared radiation calibration system under different test distances, fix the integration time of the infrared detection system, respectively calibrate the infrared radiation calibration system under two test distances by using the extended source, obtain two infrared image gray values, and solve the distance drift compensation coefficient R by combination k ; according to the temperature drift compensation coefficient R s and the distance drift compensation coefficient R k , the rapid compensation of the gray value attenuation caused by the change of the ambient temperature and the test distance is realized.

[0007] In one embodiment, the response output of the infrared radiation calibration system under different ambient temperatures is expressed as follows:

[0008] DN = R·L(T bb ) + R s ·L(T amb ) + DN dark

[0009] The response output of the infrared radiation calibration system under different test distances is expressed as follows:

[0010] DN = R·L(T bb ) + k·R k ·L(T bb ) + DN dark

[0011] In the formula, R is the blackbody radiation brightness response, T bb represents the target temperature, T amb represents the ambient temperature, k represents the test distance, L(T amb ) represents the radiation brightness when the ambient temperature is T amb , L(T bb ) represents the radiation brightness when the target temperature is T bb , and DN dark is the detector response bias of the infrared detection system.

[0012] In one embodiment, the two ambient temperatures are T amb1 and T amb2 , the two test distances are k1 and k2, and the calculation of the temperature drift compensation coefficient R s and the distance drift compensation coefficient R k is as follows:

[0013]

[0014] wherein DN(T amb1 ) and DN(T amb2 ) respectively represent the ambient temperature as T amb1 and T amb2The corresponding infrared image grayscale values, DN(k1) and DN(k2) are the infrared image grayscale values ​​corresponding to k1 and k2 respectively, L(T amb1 ) and L(T amb2 ) are respectively T amb1 and T amb2 The corresponding radiance.

[0015] In one embodiment, the drift compensation value under different ambient temperatures is as follows:

[0016] ΔDN=R s ·[L(T amb ′)-L(T amb )]

[0017] The drift compensation values ​​at different test distances are as follows:

[0018] ΔDN=R k ·Δk

[0019] In the formula, T amb ′ represents the initial calibration ambient temperature, and Δk represents the change in test distance.

[0020] The present invention also provides another method for rapid drift compensation in an infrared radiation calibration system, comprising the following steps:

[0021] Step 1: Set at least two values ​​for each of the three factors: blackbody temperature, ambient temperature, and test distance;

[0022] Step 2: Within the linear response range of the detector in the infrared radiation calibration system, fix the values ​​of two factors and obtain the infrared image grayscale values ​​of the blackbody for the three factors at the two values, thus obtaining at least four infrared image grayscale values.

[0023] Step 3: Simultaneously solve the four equations expressing the grayscale values ​​of the infrared images to obtain the blackbody radiance response R and the temperature drift compensation coefficient R0. s Distance drift coefficient R k and detector response bias DN dark ;

[0024] Step 4: Based on the solution results of Step 3, quickly compensate for the grayscale value attenuation caused by changes in ambient temperature and test distance.

[0025] In one embodiment, the blackbody temperature is set to one of two values, T. bb1 and T bb2 The two possible values ​​for the ambient temperature are T. amb1 and T amb2 The test distance can take two values, k1 and k2.

[0026] In step 2, T is first fixed.amb1 and k1, the infrared image gray value DN(T bb1 and T bb2 at the time of T bb1 , T amb1 , k1) and DN(T bb2 , T amb1 , k1); then fix T bb2 and k1, the infrared image gray value DN(T amb2 , T bb2 , k1) at the time of T amb2 ; finally fix T bb2 and T amb2 , the infrared image gray value DN(T bb2 , T amb2 , k2) at the time of k2.

[0027] In one embodiment, each of the infrared image gray values is expressed as:

[0028] DN(T bb1 , T amb1 , k1) = R·L(T bb1 ) + R s ·L(T amb1 ) + k1·R k ·L(T bb1 ) + DN dark

[0029] DN(T bb2 , T amb1 , k1) = R·L(T bb2 ) + R s ·L(T amb1 ) + k1·R k ·L(T bb2 ) + DN dark

[0030] DN(T bb2 , T amb2 , k1) = R·L(T bb2 ) + R s ·L(T amb2 ) + k1·R k ·L(T bb2 ) + DN dark

[0031] DN(T bb2 , T amb2 , k2) = R·L(T bb2 ) + R s ·L(T amb2 ) + k2·R k ·L(T bb2 ) + DNdark

[0032] wherein L(T bb1 ) and L(T bb2 ) are the radiance at T bb1 and T bb2 respectively, and L(T amb1 ) and L(T amb2 ) are the radiance at T amb1 and T amb2 respectively.

[0033] In one embodiment, the step 3, the expression equation of each of the infrared image gray value is solved to obtain:

[0034]

[0035] In one embodiment, the step 4, the radiance of the target under any environment and test distance is:

[0036]

[0037] wherein T bb represents the target temperature, T amb represents the environment temperature, k represents the test distance, L(T amb ) represents the radiance at T amb , and L(T bb ) represents the radiance at T bb .

[0038] Compared with the prior art, the present application can improve the compensation efficiency, obtain the calibration model, avoid the long calibration time, reduce the influence of the environment temperature and the test distance change on the calibration, and thus improve the calibration and radiance measurement precision of the system. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 The figure is the main component schematic diagram of the infrared radiance calibration system relied on for realizing the compensation.

[0040] Figure 2 The figure is the temperature drift compensation correction flow chart.

[0041] Figure 3 The figure is the test distance compensation correction flow chart.

[0042] Figure 4 The figure is the system temperature drift and test distance compensation correction flow chart. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific implementation described herein is only used to explain the present application and does not limit the present application.

[0044] The infrared radiation measurement system is one of the most important means for obtaining the radiation characteristics of a measured target in an optical target range, early detection and identification of the target and effective evaluation of the infrared waveband stealth effect. Infrared radiation calibration is the basis for completing the infrared radiation characteristic measurement, and the purpose is to obtain its own response parameters (mainly including response rate and its own bias response), so as to establish a quantitative relationship between the radiation amount of the radiation source output and the digital output gray value of the infrared radiation measurement system. As shown in Figure 1 The present application realizes compensation by mainly including an infrared detection system, an optical system, a surface source blackbody and an environmental thermometer. When the target is detected by the infrared radiation calibration system, the infrared radiation of the target and the background is transmitted through a path into the optical system, and finally imaged on the detector, and the radiation characteristics of the target need to be obtained by inverse calculation and analysis according to the infrared image gray value.

[0045] The present application is based on two environmental temperature calibrations and two test distance calibrations, and the temperature drift and the path attenuation are corrected, and then a drift fast compensation method for the infrared radiation calibration system is proposed.

[0046] The infrared radiation measurement system is significantly affected by the environmental temperature, and the temperature drift refers to the change of the output image gray value caused by the change of the internal stray radiation of the optical system due to the change of the environmental temperature, which is essentially the change of the detector target surface receiving energy caused by the system temperature change due to the design defects of the infrared system. The temperature drift will affect the response bias coefficient of the calibration equation of the infrared radiation calibration system, so the temperature drift compensation can be derived by the infrared radiation calibration model at different environmental temperatures.

[0047] As a radiation source, the temperature distribution, surface emissivity and other factors of the optical and mechanical structure of the infrared radiation calibration system determine the size of the spontaneous radiation energy, and at the same time, the optical and mechanical structure as a reflection surface also needs to consider its reflectivity, refractive index and other factors, so the internal stray radiation transmission mechanism is very complex, and a simplified model of the stray radiation related to the environmental temperature needs to be established for analysis.

[0048] For a fixed infrared radiation calibration system, the influence of the solid angle, reflectivity, transmittance and other factors is fixed, so the stray radiation simplified model (i.e. the radiation flux generated by the internal stray radiation) of the infrared radiation calibration system can be expressed as the stray radiation flux Φ stary , as shown in the following formula.

[0049] Φ stary =Rstary • L λ (T amb ) (1)

[0050] where R stary is the linear conversion factor from the stray radiation luminance to the stray radiation flux, which can be regarded as a constant for an infrared radiation calibration system with fixed optical-mechanical structure. L λ (T amb ) is the equivalent blackbody radiation luminance of the detector of the optical-mechanical structure of the infrared detection system at its response wavelength range and at the temperature T amb . According to the simplified model of the internal stray radiation of the infrared radiation calibration system, the stray radiation received by the detector is closely related to the ambient temperature, and the internal stray radiation generated by the infrared radiation calibration system is proportional to the equivalent blackbody radiation luminance at the ambient temperature T amb .

[0051] The deviation of the response bias coefficient of the infrared radiation calibration system mainly comes from the change of the internal stray radiation. When the stray radiation is considered, the response output of the infrared radiation calibration system is established as shown in the following formula.

[0052] DN = R d • (Φ tar + Φ stary ) + DN dark (2)

[0053] where DN is the infrared image gray value of the response output, R d is the response gain of the detector to the incident radiation flux, Φ tar is the radiation flux of the measured target, and DN dark is the background noise charge generated by the detector in the absence of incident radiation, that is, the response bias of the detector of the infrared detection system. When a blackbody is used as the measured target, the relationship between its radiation flux and radiation luminance is

[0054] Φ bb = K bb • L(T bb ) (3)

[0055] where K bb is a constant, and L(T bb ) represents the radiation luminance at the temperature T bb of the target.

[0056] Similarly, the relationship between the radiation flux generated by the internal stray radiation of the infrared radiation calibration system and the equivalent blackbody radiation luminance of the ambient temperature is

[0057] Φ stary = K amb • L(T amb ) (4)

[0058] In the formula, K amb L(T) is a constant. amb () indicates that the ambient temperature is T amb The radiance at that time.

[0059] By combining the simplified model of stray radiation, formula (2) can be rewritten as follows.

[0060] DN = R·L(T) bb )+R s ·L(T amb )+DN dark (5)

[0061] In the formula, R = R d ·K bb , where is the blackbody radiance response, representing the detector's response to radiance L(T) in an infrared detection system. bb The gain of R. s =R d ·K amb , where is the temperature drift compensation coefficient, representing the detector's response to radiance L(T) in the infrared detection system. amb The gain of ).

[0062] Equation (5) is the radiometric calibration model in the infrared radiometric calibration system that takes into account the ambient temperature. It can be seen that the grayscale value of the image is related to three parts of the response: target radiance related to the target temperature, stray radiation within the system related to the ambient temperature, and the noise signal of the detector itself. To compensate for the grayscale value caused by temperature drift, the temperature drift compensation coefficient R needs to be calculated theoretically first. s .

[0063] Based on the above, this invention constructs a temperature drift compensation model based on two ambient temperature calibrations, such as... Figure 2 As shown, firstly, the integration time of the infrared detection system is fixed, and the ambient temperature is set to T. amb1 The infrared radiation calibration system is calibrated using a near-range extended source, and the resulting output infrared image grayscale value is:

[0064] DN(T amb1 )=R·L(T bb )+R s ·L(T amb1 )+DN dark (6)

[0065] Then, the ambient temperature was changed from T amb1 Change to T amb2 The infrared radiation calibration system is calibrated using a near-range extended source, and the resulting output infrared image grayscale value is:

[0066] DN(T amb2 )=R·L(T bb )+R s ·L(T amb2 )+DN dark (7) Combining the above two formulas, we obtain the temperature drift compensation coefficient R. s The expression is as follows:

[0067]

[0068] Where DN(T) amb1 ) and DN(T amb2 ) are respectively T amb1 and T amb2 The corresponding infrared image grayscale value, L(T) amb1 ) and L(T amb2 ) are respectively T amb1 and T amb2 The corresponding radiance.

[0069] The drift compensation values ​​under different ambient temperatures are as follows:

[0070] ΔDN=R s ·[L(T amb ′)-L(T amb (9)

[0071] In the formula, T amb ′ represents the initial calibration ambient temperature.

[0072] Meanwhile, changes in the test distance between the target and the infrared radiation calibration system will also cause changes in the radiation reaching the detector, which will ultimately be reflected in the gray value deviation. Therefore, the radiation attenuation can be derived through the infrared radiation calibration model, and then the radiation brightness of the target can be calculated.

[0073] When radiation propagates through a medium, the radiation flux Φ of the target is attenuated due to absorption and scattering by the medium. Assuming that the medium only absorbs radiation, if a parallel radiation beam travels a distance k in a uniform medium, the relative value of the radiation flux ΔΦ absorbed by the medium, ΔΦ / Φ, is proportional to the distance traveled, Δk. Here, α is the absorption coefficient of the medium. Therefore, changes in the test distance will cause changes in the radiation reaching the detector, which will ultimately be reflected in the grayscale value deviation. The higher the temperature of the calibration data points, the greater the error between the calibration data, and the data error at the same temperature points increases with increasing distance. As the distance increases, the calibration gain response parameter and bias response parameter change. The gain parameter decreases with increasing distance, which also indicates that the air in the imaging path has a certain attenuation effect on infrared radiation.

[0074] Therefore, for different test distances, distance correction can be made by calibration, and ΔΦ = -α·Δk·Φ can be obtained by transformation of the above formula, and it can be concluded that the change of radiant flux is determined by the medium absorption coefficient and the radiant flux when the test distance is changed.

[0075] As Figure 3 shown, to compensate for the change of infrared image gray value due to the change of distance, the change of gray value caused by the change of distance needs to be calculated theoretically. Therefore, the response output of infrared radiation under different test distances is established according to the above formula as follows:

[0076] DN = R·L(T bb ) + k·R k ·L(T bb ) + DN dark (10)

[0077] In the formula, R k is the attenuation compensation coefficient of radiant flux with distance change, that is, the distance drift coefficient, and k is the test distance. It can be seen from the formula that the key to the establishment of the infrared radiation calibration model under different test distances is the solution of R k .

[0078] First, set the test distance to k1 under the fixed integration time, calibrate the infrared radiation calibration system with the extended source, and the response output of the infrared image gray value is:

[0079] DN(k1) = R·L(T bb ) + k1·R k ·L(T bb ) + DN dark (11)

[0080] Then, keep the integration time the same, change the test distance from k1 to k2, calibrate the infrared radiation calibration system with the extended source, and the response output of the infrared image gray value is:

[0081] DN(k2) = R·L(T bb ) + k2·R k ·L(T bb ) + DN dark (12)

[0082] The above two formulas are combined, and the distance drift compensation coefficient R k is shown as follows:

[0083]

[0084] DN(k2) = R·L(T bb ) + k2·R k ·L(T bb ) + DN dark (12)

[0082] The above two formulas are combined, and the distance drift compensation coefficient R k is shown as follows:

[0083]

[0084] DN(k2) = R·L(T bb ) + k2·R k ·L(T bb ) + DN dark (12)

[0082] The above two formulas are combined, and the distance drift compensation coefficient R k is shown as follows:

[0085]

[0086] In the formula, Δk is the change in test distance.

[0087] Although the above-mentioned calibration-based temperature drift and distance drift measurement and compensation methods can meet the drift compensation requirements, they require the acquisition of a large number of calibration images one by one at a preset integration time, followed by fitting analysis. This is labor-intensive, cumbersome, inefficient, time-consuming, and has poor real-time performance.

[0088] Therefore, this invention further proposes a rapid method for compensating for temperature drift and measurement distance drift, in order to improve the efficiency of compensation, avoid excessive calibration time, reduce the impact of changes in ambient temperature and test distance on calibration, and thereby improve the calibration and radiation measurement accuracy of the system.

[0089] Based on the aforementioned foundation, when considering ambient temperature and test distance, the infrared radiation calibration model is as follows:

[0090] DN(T bb ,T amb ,k)=R·L(T bb )+R s ·L(T amb )+k·R k ·L(T bb )+DN dark (15)

[0091] The above calibration equation has four unknown parameters: the blackbody radiance response R, the temperature drift compensation coefficient R0, and the temperature drift compensation coefficient R0. s Distance drift coefficient R k and detector response bias DN dark Therefore, only a minimum of four equations are needed to solve for the relevant calibration parameters and complete the drift measurement and compensation, such as... Figure 4 As shown, the specific process is as follows:

[0092] Step 1: Within the linear response range of the detector, set the blackbody temperature to T. bb1 The ambient temperature is set to T. amb1 If the test distance is set to k1, then the grayscale value DN(T) of the acquired infrared image is obtained according to the above formula (15). bb1 ,T amb1 k1) is represented as:

[0093] DN(T bb1 ,T amb1 ,k1)=R·L(T bb1 )+R s ·L(T amb1 )+k1·Rk • L(T bb1 )+ DN dark (16)

[0094] Step 2, the blackbody temperature is changed from T bb1 to T bb2 , the ambient temperature is kept as T amb1 , and the test distance is kept as k1, then the collected infrared image gray value DN(T bb2 , T amb1 , k1) is expressed as:

[0095] DN(T bb2 , T amb1 , k1) = R • L(T bb2 ) + R s • L(T amb1 ) + k1 • R k • L(T bb2 ) + DN dark (17)

[0096] Step 3, the blackbody temperature is kept as T bb2 , the ambient temperature is changed from T amb1 to T amb2 , and the test distance is kept as k1, then the collected infrared image gray value DN(T bb2 , T amb2 , k1) is expressed as:

[0097] DN(T bb2 , T amb2 , k1) = R • L(T bb2 ) + R s • L(T amb2 ) + k1 • R k • L(T bb2 ) + DN dark (18)

[0098] Step 4, the blackbody temperature is kept as T bb2 , the ambient temperature is kept as T amb2 , and the test distance is changed from k1 to k2, then the collected infrared image gray value DN(T bb2 , T amb2 , k2) is expressed as:

[0099] DN(T bb2 , T amb2 , k2) = R • L(T bb2 ) + R s • L(T amb2 ) + k2 • R k • L(T bb2)+DN dark (19)

[0100] Step 5, by collecting the above four calibration images, four equations can be obtained to solve four unknown parameters, and the simultaneous equations are obtained:

[0101]

[0102] Solving by inverse operation of matrix:

[0103]

[0104] According to the solution of the above formula, the blackbody calibration equation of any environmental temperature and any test distance can be obtained, and the rapid measurement and compensation of the attenuation of gray value caused by the change of environmental temperature and test distance are realized. Therefore, the radiant brightness of the target under any environment and test distance is:

[0105]

[0106] In the formula, T bb represents the target temperature, T amb represents the environmental temperature, k represents the test distance, L(T amb ) represents the radiant brightness when the environmental temperature is T amb , and L(T bb ) represents the radiant brightness when the target temperature is T bb .

Claims

1. A method for rapid drift compensation in an infrared radiation calibration system, characterized in that: The response outputs of an infrared radiometric calibration system under different ambient temperatures are constructed. With the integration time of the infrared detection system fixed, near-range extended source calibration is performed on the infrared radiometric calibration system under both ambient temperatures, yielding two infrared image grayscale values. The temperature drift compensation coefficient R is then obtained by simultaneously solving these solutions. s ; The response outputs of the infrared radiometric calibration system at different test distances are constructed. With the integration time of the infrared detection system fixed, extended source calibration is performed on the infrared radiometric calibration system at both test distances, yielding two infrared image grayscale values. The range drift compensation coefficient R is then obtained by simultaneously solving these solutions. k ; According to the temperature drift compensation coefficient R s and distance drift compensation coefficient R k This enables rapid compensation for grayscale value attenuation caused by changes in ambient temperature and test distance.

2. The method for rapid drift compensation in an infrared radiation calibration system according to claim 1, characterized in that, The response output of the infrared radiation calibration system under different ambient temperatures is expressed as follows: DN=R·L(T bb )+R s ·L(T amb )+DN dark The response output of the infrared radiometric calibration system at different test distances is expressed as follows: DN=R·L(T bb )+k·R k ·L(T bb )+DN dark In the formula, R is the blackbody radiance response, and T is the blackbody radiance response. bb T represents the target temperature. amb L represents the ambient temperature, k represents the test distance, and L(T) represents the ambient temperature. amb () indicates that the ambient temperature is T amb Radiance at time, L(T) bb ) indicates that the target temperature is T bb Radiance at time, DN dark This is the detector response bias for the infrared detection system.

3. The method for rapid drift compensation in an infrared radiation calibration system according to claim 2, characterized in that, The two ambient temperatures are T. amb1 and T amb2 The two test distances are k1 and k2, and the temperature drift compensation coefficient R is... s and distance drift compensation coefficient R k The calculations are as follows: Where DN(T) amb1 ) and DN(T amb2 ) are respectively T amb1 and T amb2 The corresponding infrared image grayscale values, DN(k1) and DN(k2) are the infrared image grayscale values ​​corresponding to k1 and k2 respectively, L(T amb1 ) and L(T amb2 ) are respectively T amb1 and T amb2 The corresponding radiance.

4. The method for rapid drift compensation in an infrared radiation calibration system according to claim 3, characterized in that, The drift compensation values ​​under different ambient temperatures are as follows: ΔDN=R s ·[L(T amb ′)-L(T amb )] The drift compensation values ​​at different test distances are as follows: ΔDN=R k ·Δk In the formula, T amb ′ represents the initial calibration ambient temperature, and Δk represents the change in test distance.

5. A method for rapid drift compensation in an infrared radiation calibration system, characterized in that, Includes the following steps: Step 1: Set at least two values ​​for each of the three factors: blackbody temperature, ambient temperature, and test distance; Step 2: Within the linear response range of the detector in the infrared radiation calibration system, fix the values ​​of two factors and obtain the infrared image grayscale values ​​of the blackbody for the three factors at the two values, thus obtaining at least four infrared image grayscale values. Step 3: Simultaneously solve the four equations expressing the grayscale values ​​of the infrared images to obtain the blackbody radiance response R and the temperature drift compensation coefficient R0. s Distance drift coefficient R k and detector response bias DN dark ; Step 4: Based on the solution results of Step 3, quickly compensate for the grayscale value attenuation caused by changes in ambient temperature and test distance.

6. The method for rapid drift compensation in an infrared radiation calibration system according to claim 5, characterized in that, The two possible values ​​for the blackbody temperature are T. bb1 and T bb2 The two possible values ​​for the ambient temperature are T. amb1 and T amb2 The test distance can take two values, k1 and k2. In step 2, T is first fixed. amb1 And k1, we get T bb1 and T bb2 The grayscale value DN(T) of the infrared image at that time bb1 ,T amb1 ,k1) and DN(T bb2 ,T amb1 ,k1); then fix T bb2 And k1, we get T amb2 The grayscale value DN(T) of the infrared image at that time bb2 ,T amb2 ,k1); finally fix T bb2 and T amb2 The infrared image grayscale value DN(T) at k2 is obtained. bb2 ,T amb2 ,k2).

7. The method for rapid drift compensation in an infrared radiation calibration system according to claim 6, characterized in that, The grayscale values ​​of each infrared image are represented as follows: DN(T bb1 ,T amb1 ,k1)=R·L(T bb1 )+R s ·L(T amb1 )+k1·R k ·L(T bb1 )+DN dark DN(T bb2 ,T amb1 ,k1)=R·L(T bb2 )+R s ·L(T amb1 )+k1·R k ·L(T bb2 )+DN dark DN(T bb2 ,T amb2 ,k1)=R·L(T bb2 )+R s ·L(T amb2 )+k1·R k ·L(T bb2 )+DN dark DN(T bb2 ,T amb2 ,k2)=R·L(T bb2 )+R s ·L(T amb2 )+k2·R k ·L(T bb2 )+DN dark In the formula, L(T) bb1 ) and L(T bb2 ) are respectively T bb1 and T bb2 Radiance at time, L(T) amb1 ) and L(T amb2 () indicates that the ambient temperature is T. amb1 and T amb2 The radiance at that time.

8. The method for rapid drift compensation in an infrared radiation calibration system according to claim 7, characterized in that, In step 3, by simultaneously solving the equations representing the grayscale values ​​of the infrared images, we obtain:

9. The method for rapid drift compensation in an infrared radiation calibration system according to claim 8, characterized in that, In step 4, the radiance of the target under any environment and test distance is: In the formula, T bb T represents the target temperature. amb L represents the ambient temperature, k represents the test distance, and L(T) represents the ambient temperature. amb () indicates that the ambient temperature is T amb Radiance at time, L(T) bb ) indicates that the target temperature is T bb The radiance at that time.

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