A method for measuring infrared spectral radiation characteristics of long-distance point targets

Abstract

The present invention relates to a method for measuring infrared spectral radiation characteristics, and in particular to a method for measuring infrared spectral radiation characteristics of a long-distance point target, which is used to solve the problem that the traditional surface source or point source target characteristic processing method cannot meet the measurement accuracy requirements of infrared spectral radiation characteristics of long-distance point targets. The method for measuring infrared spectral radiation characteristics of long-distance point targets first pre-processes a dynamic infrared spectral image, then performs spectral calibration in combination with a theoretical spectral distribution curve of blackbody radiation reaching an infrared thermal imager detector, and finally performs an inversion of the target infrared radiation characteristics based on the approximate equality of emissivity in two adjacent narrow bands to obtain the target temperature T e And the spectral emissivity of the target to achieve the measurement of the target's true infrared radiation characteristics.

Description

Technical Field

[0001] The invention relates to a method for measuring infrared spectrum radiation characteristics, and in particular to a method for measuring infrared spectrum radiation characteristics of a long-distance point target. Background Art

[0002] The measurement of target infrared spectrum radiation characteristics is one of the basic technologies for obtaining target surface radiation temperature distribution information and detecting and identifying infrared targets. The target infrared spectrum radiation characteristics measurement system mainly adopts a single-band measurement method, that is, using a single-band image, combined with radiation calibration and radiation characteristics inversion, to obtain information such as target and background radiation characteristics and temperature distribution. However, the radiation characteristics measured by a single band are based on the assumption of target emissivity, so they can only reflect relative information such as the apparent radiation characteristics and radiation brightness temperature of the target, and cannot measure the real temperature.

[0003] In addition, for infrared imaging of long-distance point targets, since the targets are far away, they are generally presented as point targets on the detector target surface, showing as diffuse spots. If the traditional surface source or point source target characteristic processing method is used, the infrared radiation characteristic measurement system will have a large measurement error and cannot meet the actual accuracy requirements. Summary of the invention

[0004] The purpose of the present invention is to solve the problem that the traditional surface source or point source target characteristic processing method cannot meet the measurement accuracy requirements of infrared spectral radiation characteristics of long-distance point targets, and to provide a method for measuring infrared spectral radiation characteristics of long-distance point targets.

[0005] In order to solve the deficiencies of the above-mentioned prior art, the present invention provides the following technical solutions:

[0006] A method for measuring infrared spectral radiation characteristics of a long-distance point target is based on a measurement system, wherein the measurement system comprises a main telescope, a spectroscopic element, an infrared thermal imager, and a data processing unit arranged in sequence along an optical path;

[0007] The main telescope is used to receive and compress infrared radiation of the target at different temperatures and output parallel light. The spectroscopic element is used to perform spectral splitting on the parallel light. The infrared thermal imager is used to collect the output light of the spectroscopic element to obtain a dynamic infrared spectrum image of the target and output it to the data processing unit. The data processing unit is used to perform data processing, spectrum calibration and inversion of the infrared radiation characteristics of the target on the received dynamic infrared spectrum image in sequence.

[0008] The infrared thermal imager collects dynamic infrared spectrum images of the target and outputs them to the data processing unit for sequential data processing, spectrum calibration and inversion of the target infrared radiation characteristics;

[0009] Its special feature is that it includes the following steps:

[0010] Step 1: Data processing;

[0011] The spectral distribution curve of the gray value of the long-distance point target without spectral calibration is obtained by a data processing unit according to the dynamic infrared spectrum image;

[0012] Step 2, spectral calibration of the spectral distribution curve;

[0013] The root mean square error between the theoretical spectral distribution curve of the black body radiation reaching the infrared thermal imager detector and the spectral distribution curve obtained in step 1 is set as the objective function, the start and end wavelengths are determined by minimizing the objective function, the band range of the spectral distribution curve is optimized, the relationship between the infrared thermal imager detector pixel point and the wavelength is obtained, and the spectral calibration of the spectral distribution curve is realized;

[0014] Step 3: Inversion of target infrared radiation characteristics;

[0015] Step 3.1, linearly fit the blackbody radiation brightness and grayscale value of each pixel at different temperatures to obtain the spectral slope K and spectral bias B corresponding to each pixel;

[0016] Step 3.2, based on the premise that the emissivity in two adjacent narrow bands is approximately equal, the emissivity ratio between adjacent bands is 1, and a multi-band radiation characteristic measurement calibration model is established. The relationship between the ratio of the radiation brightness of adjacent bands of blackbody radiation R and the blackbody temperature T is used to obtain the RT curves in different bands;

[0017] Step 3.3: Use the ratio R between the grayscale values ​​of pixels in adjacent bands v Equal to R value, solve the target temperature T e , and at the same time calculate the target emissivity to achieve the measurement of the target's true infrared radiation characteristics.

[0018] Furthermore, the step 1 is specifically as follows: perform Gaussian fitting on each column of the dynamic infrared spectrum image collected by the infrared thermal imager to obtain the mean and variance of each column, take the mean of each column as the central row, take 2.35 times the mean of the variance of each column as the half-maximum full width, calculate the mean grayscale value of all rows within the half-maximum full width range, and obtain the spectral distribution curve without spectral calibration.

[0019] Furthermore, in step 3.2, the multi-band radiation characteristic measurement calibration model is:

[0020]

[0021] R(T) represents the ratio of the brightness of adjacent bands of blackbody radiation R and the curve of the blackbody temperature T, K i , K i+1 represent the spectral slopes of bands i and i+1 respectively, Respectively represent the atmospheric transmittance of band i and i+1, They represent the blackbody radiation brightness with temperature T in bands i and i+1 respectively. They represent the atmospheric radiation brightness in bands i and i+1 respectively, and bands i and i+1 are adjacent infrared narrow bands.

[0022] Furthermore, in step 3.3, the target temperature T is calculated. e Specifically, the target multi-band radiation characteristic measurement model is established by combining the spectral slope K, spectral offset B and atmospheric parameters, and then the R measured in different bands of the target is calculated. v -T e curve;

[0023] The target multi-band radiation characteristic measurement model is as follows:

[0024]

[0025] Where R v (T e ) represents the ratio R between the measured grayscale values ​​of pixels in adjacent bands v With the target temperature T e The change curve of h i 、h i+1 Represents the grayscale value of band i and i+1 respectively, B i , B i+1 represents the spectral bias of bands i and i+1, represents the atmospheric radiation in bands i and i+1;

[0026] Calculate the target temperature T e When the calibrated RT curve and the measured R v -T e The curve is averaged along the spectral dimension to obtain the mean curve of the two. The calibrated RT curve and the measured R v -T e The corresponding target temperature T e .

[0027] Further, in step 3.3, the target emissivity is calculated by calculating the RT curves calibrated at all temperature points and the measured R v -T e The mean R of the curve λ and R v,λ , using R v,λ With R λ The ratio between them can be used to obtain the spectral emissivity of the target.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention discloses a method for measuring infrared spectral radiation characteristics of a long-distance point target. After receiving and compressing the infrared radiation of the long-distance point target through a main telescope, the infrared radiation is parallelly incident on a spectroscopic element for spectral splitting. Then, an infrared thermal imager collects a dynamic infrared spectral image of the target and outputs it to a data processing unit. The data processing unit first pre-processes the dynamic infrared spectral image, and then performs spectral calibration in combination with a theoretical spectral distribution curve of black body radiation reaching the infrared thermal imager detector. Finally, based on the approximate equality of emissivity in two adjacent narrow bands, the infrared radiation characteristics of the target are inverted to obtain the target temperature T e And the spectral emissivity of the target, to achieve the measurement of the real infrared radiation characteristics of the target; the present invention can achieve high-precision measurement of the real infrared radiation characteristics of long-distance point targets, and can be widely used in tracking and measuring the infrared radiation characteristics of long-distance point targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 A schematic diagram of the structure of a measurement system applicable to a method for measuring infrared spectrum radiation characteristics of a long-distance point target according to the present invention;

[0031] Figure 2 A dynamic infrared spectrum image collected by a measurement system in one embodiment of the present invention;

[0032] Figure 3 The spectral distribution curves at each target temperature obtained in step 1;

[0033] Figure 4 The spectrum distribution curve obtained in step 2 after band optimization;

[0034] Figure 5 The RT curves calibrated by blackbody radiation in different bands obtained in step 3.1;

[0035] Figure 6 The R measured at different wavelengths for the target obtained in step 3.2 v -T e curve;

[0036] Figure 7 for Figure 5 The RT curve and Figure 6 R v -T e The mean curve of the curve;

[0037] Figure 8 for Figure 7 Measurement error curves at different temperatures;

[0038] Fig. 9 is the spectral emissivity curve of the target.

[0039] The following are the descriptions of the reference numerals:

[0040] 1- Main telescope; 2- Spectral element; 3- Infrared thermal imager; 4- Data processing unit. DETAILED DESCRIPTION

[0041] The present invention will be further described below in conjunction with the accompanying drawings and exemplary embodiments.

[0042] A method for measuring infrared spectral radiation characteristics of a long-distance point target is based on a measurement system, wherein the measurement system comprises a main telescope 1, a spectroscopic element 2, an infrared thermal imager 3, and a data processing unit 4 arranged in sequence along an optical path;

[0043] Reference Figure 1 , Figure 2 The infrared radiation of the target at different temperatures is received and compressed by the main telescope 1, and then incident in parallel to the spectroscopic element 2 for spectral spectrometry. Then, the infrared thermal imager 3 collects the outgoing light of the spectroscopic element 2 to obtain the dynamic infrared spectrum image of the target, and outputs it to the data processing unit 4 for data processing, spectral calibration and inversion of the infrared radiation characteristics of the target in sequence; the infrared thermal imager 3 includes a focal plane array detector and an optical lens;

[0044] The long-distance point target is simulated by using a cavity black body and a collimator;

[0045] Step 1: Data processing;

[0046] right Figure 2 Gaussian fitting is performed on each column of the dynamic infrared spectrum image shown in the figure to obtain the mean and variance of each column. The mean of each column is taken as the central row, and 2.35 times of the mean of the variance of each column is taken as the half-height full width. The mean gray value of all rows within the half-height full width is calculated, and the following is obtained: Figure 3 The spectral distribution curve shown without spectral calibration;

[0047] Step 2, spectral calibration of the spectral distribution curve;

[0048] The Planck formula is used to calculate the black body radiation of known temperature, and the theoretical spectral distribution curve of the black body radiation reaching the focal plane array detector is obtained by combining the spectral response of the spectroscopic element 2 and the focal plane array detector;

[0049] The root mean square error between the theoretical spectral distribution curve and the spectral distribution curve obtained in step 1 is set as the objective function. The start and end wavelengths are determined by minimizing the objective function, and the band range of the spectral distribution curve is optimized to obtain the relationship between the focal plane array detector pixel point and the wavelength, thereby realizing the spectral calibration of the spectral distribution curve, such as Figure 4 As shown;

[0050] Step 3: Inversion of target infrared radiation characteristics;

[0051] Step 3.1, linearly fit the blackbody radiation brightness and grayscale value of each pixel at different temperatures to obtain the spectral slope K and spectral bias B corresponding to each pixel;

[0052] Step 3.2: Based on the premise that the emissivity in two adjacent narrow bands is approximately equal, and the ratio of emissivity between adjacent bands is 1, a multi-band radiation characteristic measurement calibration model is established as follows:

[0053]

[0054] R(T) represents the ratio of the brightness of adjacent bands of blackbody radiation R and the curve of the blackbody temperature T, K i , K i+1 represent the spectral slopes of bands i and i+1 respectively, Respectively represent the atmospheric transmittance of band i and i+1, They represent the blackbody radiation brightness with temperature T in bands i and i+1 respectively. Respectively represent the atmospheric radiation brightness in bands i and i+1, where bands i and i+1 are adjacent infrared narrow bands;

[0055] Using the relationship between the ratio of the radiation brightness of adjacent bands of blackbody radiation R and the blackbody temperature T, the RT curves of blackbody radiation calibration in different bands are calculated as follows: Figure 5 As shown;

[0056] Step 3.3: Use the ratio R between the grayscale values ​​of pixels in adjacent bands v Equal to the R value, the target multi-band radiation characteristic measurement model is established by combining the spectral slope K, spectral bias B and atmospheric parameters as follows:

[0057]

[0058] Where R v (T e ) represents the ratio R between the measured grayscale values ​​of pixels in adjacent bands v With the target temperature T e The change curve of h i 、h i+1 Represents the grayscale value of band i and i+1 respectively, B i , B i+1 represents the spectral bias of bands i and i+1, represents the atmospheric radiation in bands i and i+1;

[0059] Calculate the R measured at different bands of the target v -T e Curve like Figure 6 As shown;

[0060] Calculate the target temperature Te When the calibrated spectrum RT curve and the measured spectrum R v -T e The curve is averaged along the spectral dimension to obtain the mean curve of the two, such as Figure 7 As shown in the figure, the calibrated RT curve and the measured R v -T e The corresponding target temperature T e , to achieve the measurement of the target temperature, the measurement error at different temperatures is as follows Figure 8 Show;

[0061] When measuring the target spectral emissivity, calculate the calibrated RT curve and the measured R at all temperatures v -T e The mean R of the curve λ and R v,λ , using R v,λ With R λ The ratio between them can be used to obtain the spectral emissivity of the target, such as Fig. 9 shown.

[0062] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. For ordinary professional and technical personnel in the field, the specific technical solutions recorded in the aforementioned embodiments can be modified, or some of the technical features therein can be replaced by equivalents, and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions protected by the present invention.

Claims

1. A method for measuring infrared spectral radiation characteristics of a long-distance point target, based on a measurement system, the measurement system comprising a main telescope (1), a spectroscopic element (2), an infrared thermal imager (3), and a data processing unit (4) arranged in sequence along an optical path; The main telescope (1) is used to receive and compress infrared radiation of a target at different temperatures and output parallel light; the spectroscopic element (2) is used to perform spectral splitting on the parallel light; the infrared thermal imager (3) is used to collect the output light of the spectroscopic element (2) to obtain a dynamic infrared spectrum image of the target and output it to a data processing unit (4); the data processing unit (4) is used to sequentially perform data processing, spectrum calibration and inversion of the infrared radiation characteristics of the target on the received dynamic infrared spectrum image; It is characterized in that The steps include: Step 1: Data processing; The spectral distribution curve of the gray value of the long-distance point target without spectral calibration is obtained by a data processing unit according to the dynamic infrared spectrum image; Step 2, spectral calibration of the spectral distribution curve; The root mean square error between the theoretical spectral distribution curve of the black body radiation reaching the infrared thermal imager (3) detector and the spectral distribution curve obtained in step 1 is set as the objective function, the start and end wavelengths are determined by minimizing the objective function, the band range of the spectral distribution curve is optimized, the relationship between the pixel point and the wavelength of the infrared thermal imager (3) detector is obtained, and the spectral calibration of the spectral distribution curve is realized; Step 3: Inversion of target infrared radiation characteristics; Step 3.1, linearly fit the blackbody radiation brightness and grayscale value of each pixel at different temperatures to obtain the spectral slope K and spectral bias B corresponding to each pixel; Step 3.2, based on the premise that the emissivity in two adjacent narrow bands is approximately equal, using the emissivity ratio between adjacent bands as 1, a multi-band radiation characteristic measurement calibration model is established, and the relationship between the ratio of the radiation brightness of adjacent bands of blackbody radiation R and the blackbody temperature T is used to obtain the calibrated RT curves in different bands; Step 3.3: Use the ratio R between the grayscale values ​​of pixels in adjacent bands v Equal to R value, solve the target temperature T e , and at the same time calculate the target emissivity to achieve the measurement of the target's true infrared radiation characteristics.

2. A method for measuring infrared spectral radiation characteristics of a long-distance point target according to claim 1, Features: The step 1 specifically comprises: performing Gaussian fitting on each column of the dynamic infrared spectrum image collected by the infrared thermal imager (3) to obtain the mean and variance of each column, taking the mean of each column as the central row, taking 2.35 times the mean of the variance of each column as the half-maximum full width, calculating the mean grayscale value of all rows within the half-maximum full width range, and obtaining a spectral distribution curve without spectral calibration.

3. A method for measuring infrared spectral radiation characteristics of a long-distance point target according to claim 2, Features: In step 3.2, the multi-band radiation characteristic measurement calibration model is: R(T) represents the ratio of the brightness of adjacent bands of blackbody radiation R and the blackbody temperature T, K i , K i+1 represent the spectral slopes of bands i and i+1 respectively, Respectively represent the atmospheric transmittance of band i and i+1, They represent the blackbody radiation brightness with temperature T in bands i and i+1 respectively. They represent the atmospheric radiation brightness in bands i and i+1 respectively, and bands i and i+1 are adjacent narrow infrared bands.

4. A method for measuring infrared spectral radiation characteristics of a long-distance point target according to claim 3, Features: In step 3.3, the target temperature T is calculated e Specifically, the target multi-band radiation characteristic measurement model is established by combining the spectral slope K, spectral offset B and atmospheric parameters, and then the R measured in different bands of the target is calculated. v -T e curve; The target multi-band radiation characteristic measurement model is as follows: Where R v (T e ) represents the ratio R between the measured grayscale values ​​of pixels in adjacent bands v With the target temperature T e The change curve of h i 、h i+1 Represents the grayscale value of band i and i+1 respectively, B i , B i+1 represents the spectral bias of bands i and i+1, represents the atmospheric radiation in bands i and i+1; The calibrated RT curve and the measured R v -T e The curves are averaged along the spectral dimension to obtain the mean curves of each temperature change. v -T e The value of the curve corresponds to the value of the calibrated RT curve, and the corresponding target temperature T is obtained. e .

5. A method for measuring infrared spectrum radiation characteristics of a long-distance point target according to claim 4, Features: In step 3.3, the target emissivity is calculated by calculating the calibrated RT curves of all temperature points and the measured R v -T e The average value of the curve along the temperature direction is R λ and R v,λ , using R v,λ With R λ The ratio between them is used to obtain the spectral emissivity of the target.

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