Infrared imaging system operating distance performance prediction method based on laboratory calibration

Abstract

The invention discloses an infrared imaging system operating distance performance prediction method based on laboratory calibration, and relates to the technical field of infrared imaging system performance prediction, and the method comprises the following steps: carrying out the calibration of a spatial frequency-minimum distinguishable temperature difference curve under the ideal condition of an infrared imaging system through a laboratory; converting into a spatial frequency-minimum distinguishable radiation difference curve; collecting a target actual measurement imaging result of the infrared imaging system through an external field experiment, and calculating a radiation difference between a target and a background; reversely deducing the actual spatial frequency; calculating an ideal spatial frequency; and calculating the operating distance decline rate of the infrared imaging system according to the actual spatial frequency and the ideal spatial frequency. The spatial frequency-minimum distinguishable temperature difference curve is calibrated and converted into the spatial frequency-minimum distinguishable radiation difference curve through a laboratory, the spatial frequency-minimum distinguishable radiation difference curve is coupled with a target actual measurement imaging result of an external field experiment, dynamic response to a complex environment is achieved, and the accuracy of operating distance performance prediction is improved.

Description

Technical Field

[0001] The present application relates to the technical field of infrared imaging system performance prediction, and in particular to a method for predicting the range performance of an infrared imaging system based on laboratory calibration. Background Art

[0002] Infrared imaging technology is widely used in military, industrial, medical diagnostic, and astronomical fields. It is essentially a wavelength conversion technique, whereby infrared radiation is converted by the infrared imaging system into an image that can be visually resolved by the human eye, with grayscale values ​​corresponding to temperature values. During this process, the range performance of an infrared imaging system is primarily influenced by the radiation distribution between the target and background, atmospheric attenuation, and the system's inherent performance. The range equation combines these three factors to provide a method for calculating the range. The minimum resolvable temperature difference (MRTD) is a key parameter for comprehensively evaluating the spatial and temperature resolution of a thermal imager. It incorporates both the system's inherent characteristics and the subjective influence of the observer. Therefore, a range model based on MRTD is generally used to predict the range of image detection.

[0003] In the prior art, Chinese patent CN114199388A discloses a performance evaluation method for the range of an infrared imaging system, including: for a target with a spatial frequency f, the actual temperature difference between it and the background, when transmitted through the atmosphere to the thermal imaging system, should still be greater than or equal to the MRTD(f) of the corresponding frequency of the imaging system, and at the same time, the target's angle to the system should be greater than or equal to the minimum viewing angle required for the detection level.

[0004] Traditional range prediction relies on a theoretical MRTD model. While this model accounts for factors such as background temperature differences, system parameters, and atmospheric transmittance, it lacks adaptability to dynamic changes in complex environments. For example, ambient light intensity, time-of-day variations, and weather conditions (such as haze and rainfall) significantly affect the actual range of an optoelectronic system, but theoretical models struggle to quantify these variables in real time. However, the aforementioned existing technologies fail to address these issues and lack dynamic response to complex environments, resulting in poor accuracy in predicting the range performance of infrared imaging systems. Summary of the Invention

[0005] This application provides a method for predicting the range performance of an infrared imaging system based on laboratory calibration, which is used to solve the problem that the existing technology lacks dynamic response to complex environments and the accuracy of the range performance prediction of the infrared imaging system is poor.

[0006] In one aspect, the present application provides a method for predicting the range performance of an infrared imaging system based on laboratory calibration, comprising the following steps:

[0007] Step 1: Calibrate the spatial frequency-minimum resolvable temperature difference curve of the infrared imaging system under ideal conditions in a laboratory, and convert the spatial frequency-minimum resolvable temperature difference curve into a spatial frequency-minimum resolvable radiation difference curve.

[0008] Step 2: Collect the target measured imaging results of the infrared imaging system through an outdoor experiment, and calculate the radiation difference between the target and the background based on the target measured imaging results.

[0009] Step three: according to the radiation difference, inversely deduce the actual spatial frequency from the spatial frequency-minimum resolvable radiation difference curve.

[0010] Step 4: Calculate the ideal spatial frequency based on the distance between the target and the infrared imaging system during field experiment measurement.

[0011] Step five: calculating the range drop rate of the infrared imaging system, that is, the range performance, according to the actual spatial frequency and the ideal spatial frequency.

[0012] In one possible implementation, in step 1, the calibration of the spatial frequency-minimum resolvable temperature difference curve of the infrared imaging system under ideal conditions in a laboratory includes:

[0013] Calculate target size in the laboratory.

[0014] Build a laboratory experimental environment.

[0015] The minimum resolvable temperature difference was measured under the laboratory experimental environment.

[0016] A spatial frequency-minimum resolvable temperature difference curve is drawn according to the minimum resolvable temperature difference and the corresponding spatial frequency.

[0017] In one possible implementation, setting up a laboratory experimental environment includes:

[0018] Based on the target size in the laboratory, a laboratory environment is prepared, a laboratory target is prepared, and an infrared imaging system in the laboratory is adjusted to form a laboratory experimental environment.

[0019] In a possible implementation, in step 1, the spatial frequency-minimum resolvable temperature difference curve is converted into a spatial frequency-minimum resolvable radiation difference curve using Planck's formula.

[0020] In a possible implementation, in step 2, collecting the measured imaging results of the target by the infrared imaging system through an outdoor experiment includes:

[0021] Build an outdoor experimental environment.

[0022] The target measured imaging results of the infrared imaging system are collected in the field experimental environment.

[0023] In one possible implementation, setting up an outdoor experimental environment includes:

[0024] Prepare field experiment targets, adjust the infrared imaging system for the field experiment, set up temperature difference monitoring equipment and environmental monitoring equipment, and form a field experiment environment.

[0025] In a possible implementation, in step 2, calculating the radiation difference between the target and the background based on the measured imaging result of the target includes:

[0026] Combining the measured imaging results of the target, the number of voltage quantization bits and the performance parameters of the infrared imaging system, the target radiation intensity and background radiation intensity are dequantized.

[0027] The difference between the target radiation intensity and the background radiation intensity, ie, the radiation difference, is calculated.

[0028] The method for predicting the range performance of infrared imaging systems based on laboratory calibration in this application has the following advantages:

[0029] The spatial frequency-minimum resolvable temperature difference curve is calibrated in the laboratory and converted into a spatial frequency-minimum resolvable radiation difference curve, which is coupled with the measured imaging results of the target in the field experiment to achieve dynamic response to complex environments and improve the accuracy of the range performance prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0031] Figure 1 A flow chart of a method for predicting the range performance of an infrared imaging system based on laboratory calibration provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0033] Specifically, the basic requirements for estimating the line-of-sight of extended source targets using MRTD are: for a target with a spatial frequency of f, the actual temperature difference between it and the background, when transmitted through the atmosphere to the thermal imaging system, should still be greater than or equal to the MRTD(f) of the corresponding frequency of the imaging system. At the same time, the angle of the target to the system should be greater than or equal to the minimum viewing angle required by the detection level, that is, satisfying formula (1):

[0034]

[0035] Where f is the spatial frequency of the target; θ is the target field of view; h is the target height; N e = is the number of equivalent strips required to detect, locate, identify, and clearly recognize the target according to the Johnson criterion; R is the distance to the target; ΔT is the apparent temperature difference between the target and the background at the entrance pupil of the thermal imaging system; MRTD(f) is the minimum resolvable temperature difference of the thermal imaging system when the spatial frequency is equal to f. The distance R when the equal sign is taken in formula (1) is the system's effective range. In general calculations, the apparent temperature difference at the entrance pupil is calculated by multiplying the apparent temperature difference between the target and the background at zero line of sight by the path average atmospheric transmittance, that is, formula (2):

[0036] ΔT=ΔT0·τ(R) (2)

[0037] Where ΔT0 is the target-background temperature difference at zero line of sight; τ(R) is the atmospheric transmittance at distance R. Atmospheric transmittance reflects the degree of atmospheric attenuation of radiant energy, not the degree of temperature attenuation. To reduce the calculation error, equation (1) needs to be corrected to obtain equation (3):

[0038]

[0039] Where △M is the apparent radiation emittance difference between the target and the background, △M MRTD(f) is the radiance when the target background temperature difference is the minimum resolvable temperature difference. t and M b To express the radiation emittance of the target and background at the entrance pupil of the infrared thermal imaging system, according to the working principle of the infrared thermal imaging system, there is formula (4):

[0040]

[0041] Among them, M t0 and M b0 Respectively represent the radiation emittance of the target and background at zero sight distance, M R is the atmospheric radiation on the path. Subtracting the two equations in equation (4) yields equations (5) and (6):

[0042] ΔM=ΔM0·τ(R) (5)

[0043]

[0044] Among them, T b is the background temperature, c1 and c2 are the first and second radiation constants respectively, and λ is the wavelength.

[0045] In order to calculate the range degradation efficiency of the infrared imaging system under different weather conditions, different time phases, and different target sizes based on the measured target characteristic data, based on the above theoretical basis, combined with the laboratory calibration infrared imaging system f-MRTD curve and the revised range calculation formula, the range degradation rate of the system under ideal conditions and measured conditions is indirectly calculated. Figure 1 As shown, the embodiment of the present application provides a method for predicting the range performance of an infrared imaging system based on laboratory calibration, comprising the following steps:

[0046] Step 1: Calibrate the spatial frequency-minimum resolvable temperature difference curve of the infrared imaging system under ideal conditions in a laboratory, and convert the spatial frequency-minimum resolvable temperature difference curve into a spatial frequency-minimum resolvable radiation difference curve.

[0047] Step 2: Collect the target measured imaging results of the infrared imaging system through an outdoor experiment, and calculate the radiation difference between the target and the background based on the target measured imaging results.

[0048] Step three: according to the radiation difference, inversely deduce the actual spatial frequency from the spatial frequency-minimum resolvable radiation difference curve.

[0049] Step 4: Calculate the ideal spatial frequency based on the distance between the target and the infrared imaging system during field experiment measurement.

[0050] Step five: calculating the range drop rate of the infrared imaging system, that is, the range performance, according to the actual spatial frequency and the ideal spatial frequency.

[0051] For example, in step 1, the calibration of the spatial frequency-minimum resolvable temperature difference curve of the infrared imaging system under ideal conditions in a laboratory includes:

[0052] Calculate target size in the laboratory.

[0053] Build a laboratory experimental environment.

[0054] The minimum resolvable temperature difference was measured under the laboratory experimental environment.

[0055] A spatial frequency-minimum resolvable temperature difference curve is drawn according to the minimum resolvable temperature difference and the corresponding spatial frequency.

[0056] Specifically, in order to accurately calibrate the MRTD of the infrared imaging system in a laboratory environment and ensure that the spatial frequency characteristics of targets of different sizes in field experiments remain consistent with those in the laboratory, the target size used for MRTD curve calibration in the laboratory needs to be calculated based on the performance parameters of the infrared imaging system.

[0057] Due to the long-term data collection in the field and the difficulty in moving the target / infrared imaging system, the imaging distance (R act-meas ), collect target imaging characteristic data under different weather conditions, different time phases, and different target sizes. Assume that the target size used in the field experiment is a act-meas ×b act-meas , can calculate the target size a for MRTD curve calibration in the laboratory ideal ×b ideal As shown in formula (7):

[0058]

[0059] Among them, R ideal It is the distance between the infrared imaging system and the target in the laboratory, which depends on the distance in the laboratory.

[0060] Exemplarily, the setting up of a laboratory experimental environment includes:

[0061] Based on the target size in the laboratory, a laboratory environment is prepared, a laboratory target is prepared, and an infrared imaging system in the laboratory is adjusted to form a laboratory experimental environment.

[0062] Specifically, in this embodiment, preparing the laboratory environment includes:

[0063] Control the laboratory temperature: Maintain the ambient temperature between 20°C and 25°C to avoid temperature fluctuations. Use air conditioners, temperature control boxes, and other equipment to ensure the stability of the ambient temperature.

[0064] Reduce air movement: Turn off laboratory ventilation equipment to avoid temperature changes caused by air movement.

[0065] Ensure the equipment is warmed up: Allow the infrared imaging system and optical components to fully warm up, which usually takes at least 30 minutes. Ensure the performance of the imaging system is stable.

[0066] In this embodiment, preparing the laboratory target includes:

[0067] Target selection and placement: Choose a standard four-bar target and ensure that its stripes are clear and of moderate width (common frequencies include 1lp / mm, 2lp / mm, etc.).

[0068] Target distance setting: Set the distance R between the target and the infrared imaging system according to the experimental requirements ideal , and keep it stable. Make sure the relative angle between the target and the detector remains consistent and the target should be in the center of the field of view.

[0069] Setting the target temperature difference: Use heating or cooling equipment (such as temperature-controlled heating plates or temperature-controlled boxes) to adjust the temperature of the target so that it maintains a known temperature difference ΔT with the background. ideal The background temperature should be kept consistent with the ambient temperature (or slightly deviated from it), and the target temperature difference can be set by adjusting the heat source.

[0070] Temperature monitoring: Use an infrared thermometer or thermocouple sensor to monitor the temperature difference between the target and the background in real time to ensure its accuracy.

[0071] In this embodiment, adjusting the infrared imaging system in the laboratory includes:

[0072] Optical system adjustment: Adjust the focal length of the imaging system so that the target is clearly imaged in the center of the field of view. Ensure that the optical resolution of the imaging system is sufficient to distinguish the fringes on the target, especially the high-frequency fringes.

[0073] Exposure settings: Adjust the exposure time to ensure a clear image and avoid overexposure or darkening. The exposure time should be moderate to ensure that target details are not lost. Ensure that the detector is not overheated and maintain low noise.

[0074] Elimination of environmental interference: Ensure that there is no strong external infrared or visible light interference in the laboratory. Ambient light interference can be reduced by using a light shield or light shielding screen.

[0075] In this embodiment, measuring the minimum resolvable temperature difference in a laboratory experimental environment includes:

[0076] Adjust the temperature difference gradually: start with a smaller temperature difference (e.g. 0.1°K), gradually increase the temperature difference (e.g. increase by 0.1°K to 0.5°K each time), and record the minimum spatial frequency f that the system can resolve at each temperature difference.

[0077] Record the resolvable spatial frequency: For each temperature difference, record the minimum fringe width (i.e., spatial frequency) that the system can resolve. If the system cannot resolve the target's fringes, record the maximum spatial frequency corresponding to that temperature difference. To ensure the reliability of the experimental results, perform at least three measurements at each temperature difference and take the average to reduce random errors.

[0078] The resolution (minimum resolvable temperature difference) and the corresponding spatial frequency data at each temperature difference are organized into a table. A spatial frequency-minimum resolvable temperature difference curve is plotted with spatial frequency (f) as the horizontal axis and minimum resolvable temperature difference (MRTD) as the vertical axis.

[0079] In this embodiment, the precautions for step 1 are as follows:

[0080] Stable ambient temperature: The laboratory temperature should be stable to avoid measurement errors caused by temperature fluctuations.

[0081] Avoid air flow interference: Factors such as air flow and temperature difference in the laboratory may affect the experimental results. The influence of air flow on temperature difference should be avoided.

[0082] Target temperature uniformity: Ensure that the temperature on the target surface is uniform to avoid experimental errors caused by uneven temperature distribution.

[0083] Precise temperature difference control: Use high-precision temperature control equipment to adjust the temperature difference of the target and keep the temperature difference between the target and the background within the set range.

[0084] Calibration of temperature sensors: Temperature sensors need to be calibrated regularly to ensure accurate measurement values.

[0085] Optical system alignment: Ensure that the optical system is accurately aligned with the target to avoid image blur due to defocus.

[0086] Exposure time adjustment: Adjust the exposure time to avoid image quality degradation due to too long or too short exposure time.

[0087] Multiple measurements: Multiple measurements should be taken at each temperature difference and the average value should be taken to reduce accidental errors and ensure data reliability.

[0088] Experimental repeatability: Repeat the experiment at different times, with different experimenters and equipment to verify the consistency of the results.

[0089] Exemplarily, in step 1, the spatial frequency-minimum resolvable temperature difference curve is converted into a spatial frequency-minimum resolvable radiation difference curve using Planck's formula.

[0090] Specifically, the minimum resolvable radiation difference M corresponding to the minimum resolvable temperature difference MRTD is calculated by Planck formula: λ That is, the minimum resolvable temperature difference corresponds to the minimum resolvable radiation difference, as shown in formula (8):

[0091]

[0092] The spatial frequency-minimum resolvable temperature curve is converted into a spatial frequency-minimum resolvable radiation difference curve.

[0093] For example, in step 2, collecting the measured imaging results of the target by the infrared imaging system through an outdoor experiment includes:

[0094] Build an outdoor experimental environment.

[0095] The target measured imaging results of the infrared imaging system are collected in the field experimental environment.

[0096] Exemplarily, the setting up of the field experiment environment includes:

[0097] Prepare field experiment targets, adjust the infrared imaging system for the field experiment, set up temperature difference monitoring equipment and environmental monitoring equipment, and form a field experiment environment.

[0098] Specifically, in this embodiment, preparing the field experiment target includes: using a standard four-bar target (or other suitable target), ensuring that the target size and spacing meet the requirements of the experimental design, and selecting a target with high contrast (such as black and white stripes) to improve imaging clarity and ensure that it is not affected by different weather conditions.

[0099] In this embodiment, adjusting the infrared imaging system for the field experiment includes ensuring that the optical components and detector of the infrared imaging system have been preheated and calibrated to optimal working conditions. Adjusting the imaging system's exposure time, focus, and gain to account for varying weather and lighting conditions is also important.

[0100] In this embodiment, setting up the temperature difference monitoring device includes: during the test process, using a temperature sensor to accurately measure the temperature difference between the target and the background to ensure that the temperature difference between the target and the background remains stable.

[0101] In this embodiment, setting up environmental monitoring equipment includes: using environmental sensors to monitor weather conditions (such as temperature, humidity, wind speed, etc.) and using a visibility meter (such as a laser rangefinder) to monitor environmental visibility in rainy or foggy weather.

[0102] In this embodiment, the target measured imaging results of the infrared imaging system are collected in the field experimental environment. To ensure the extensiveness and repeatability of the experiment, data collection is planned to be performed every hour, and multiple measurements are performed in special weather conditions (such as rain, fog, and cloudy weather) to ensure that the imaging distance R act-meas During each test, record the following information in detail:

[0103] Weather conditions: sunny, rainy, cloudy, foggy, etc.

[0104] Time: Day or night.

[0105] Target size: large, medium, and small targets.

[0106] Temperature difference (ΔT act-meas ): Temperature difference between target and background.

[0107] Environmental parameters: humidity, temperature, wind speed, visibility, etc.

[0108] Imaging system settings: exposure time, gain, focal length, lens type, etc.

[0109] Imaging results: image resolution, image quality, minimum resolvable temperature difference, spatial frequency, etc.

[0110] Exemplarily, in step 2, calculating the radiation difference between the target and the background based on the measured imaging result of the target includes:

[0111] Combining the measured imaging results of the target, the number of voltage quantization bits and the performance parameters of the infrared imaging system, the target radiation intensity and background radiation intensity are dequantized.

[0112] The difference between the target radiation intensity and the background radiation intensity, ie, the radiation difference, is calculated.

[0113] Specifically, the digital grayscale value D of each pixel is usually obtained through a quantization process in an infrared imaging system. The digital grayscale value D is a value between 0 and 2n- 1 Integers between (where n is the number of voltage quantization bits), as shown in formula (9):

[0114]

[0115] Among them, V out is the voltage value output by the infrared imaging system, V min is the minimum voltage quantization value, V max Assume that the output voltage of the system is V out With the radiation intensity M λ There is a linear relationship between them, and the gain G and offset B are known (these can be obtained through the radiation calibration of the system), then the radiation intensity can be calculated using formula (10):

[0116] ΔV out =G·M λ +B (10)

[0117] Where, ΔV out is the voltage output value of the photoelectric system. During the field experiment, the voltage is inversely quantized into the target radiation intensity and background radiation intensity by combining the measured imaging results of the target, the voltage quantization bit number and the performance parameters of the infrared imaging system, and combining equations (9) and (10), as shown in equations (11) and (12):

[0118]

[0119] Among them D tar-act-meas is the target grayscale value, D bac-act-meas is the background gray value.

[0120] Calculate the radiation difference △M between the target and the backgroundact-meas As shown in formula (13):

[0121] ΔM act-meas =M tar-act-meas -M bac-act-meas (13)

[0122] Among them, M tar-act-meas is the target radiation intensity, M bac-act-meas is the background radiation intensity.

[0123] Specifically, in step 3, the radiation difference △M between the target and the background is act-meas As the resolvable radiation benchmark of the infrared imaging system, the actual spatial frequency f is deduced from the calibrated spatial frequency-minimum resolvable radiation difference curve. act-meas .

[0124] Specifically, in step 4, the size of the four-bar target and the imaging distance R during actual measurement are known. act-meas , the ideal spatial frequency f of the target can be calculated ideal As shown in formula (14):

[0125]

[0126] Among them, θ stripe is the angle corresponding to the target fringe period (mrad). For periodic fringe targets, the fringe spacing p t Affects spatial frequency, θ stripe As shown in formula (15):

[0127]

[0128] Specifically, in step 5, the range reduction rate d of the infrared imaging system is calculated based on the actual spatial frequency and the ideal spatial frequency. descent rate , as shown in formula (16):

[0129]

[0130] The embodiment of the present application calibrates the spatial frequency-minimum resolvable temperature difference curve in the laboratory and converts it into a spatial frequency-minimum resolvable radiation difference curve, which is coupled with the measured imaging results of the target in the field experiment, thereby achieving a dynamic response to complex environments and improving the accuracy of the range performance prediction.

[0131] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0132] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for predicting the range performance of an infrared imaging system based on laboratory calibration, characterized in that: The following steps are involved: Step 1: Calibrate the spatial frequency-minimum resolvable temperature difference curve of the infrared imaging system under ideal conditions in a laboratory, and convert the spatial frequency-minimum resolvable temperature difference curve into a spatial frequency-minimum resolvable radiation difference curve; Step 2: collecting the target measured imaging results of the infrared imaging system through an outdoor experiment, and calculating the radiation difference between the target and the background based on the target measured imaging results; Step 3: Determine the actual spatial frequency from the spatial frequency-minimum resolvable radiation difference curve according to the radiation difference; Step 4: Calculate the ideal spatial frequency based on the distance between the target and the infrared imaging system during field experiment measurement; Step five: calculating the range drop rate of the infrared imaging system, that is, the range performance, according to the actual spatial frequency and the ideal spatial frequency.

2. The method for predicting the range performance of an infrared imaging system based on laboratory calibration according to claim 1, characterized in that: In step 1, the calibration of the spatial frequency-minimum resolvable temperature difference curve of the infrared imaging system under ideal conditions in the laboratory includes: Calculate target size in the laboratory; Set up laboratory experimental environment; Measuring the minimum resolvable temperature difference under the laboratory experimental environment; A spatial frequency-minimum resolvable temperature difference curve is drawn according to the minimum resolvable temperature difference and the corresponding spatial frequency.

3. The method for predicting the range performance of an infrared imaging system based on laboratory calibration according to claim 2, characterized in that: The construction of the laboratory experimental environment includes: Based on the target size in the laboratory, a laboratory environment is prepared, a laboratory target is prepared, and an infrared imaging system in the laboratory is adjusted to form a laboratory experimental environment.

4. The method for predicting the range performance of an infrared imaging system based on laboratory calibration according to claim 1, characterized in that: In step 1, the spatial frequency-minimum resolvable temperature difference curve is converted into a spatial frequency-minimum resolvable radiation difference curve using Planck's formula.

5. The method for predicting the range performance of an infrared imaging system based on laboratory calibration according to claim 1, characterized in that: In step 2, collecting the measured imaging results of the target by the infrared imaging system through field experiments includes: Build an outdoor experimental environment; The target measured imaging results of the infrared imaging system are collected in the field experimental environment.

6. The method for predicting the range performance of an infrared imaging system based on laboratory calibration according to claim 5, characterized in that: The field experiment environment is constructed as follows: Prepare field experiment targets, adjust the infrared imaging system for the field experiment, set up temperature difference monitoring equipment and environmental monitoring equipment, and form a field experiment environment.

7. The method for predicting the range performance of an infrared imaging system based on laboratory calibration according to claim 1, characterized in that: In step 2, the calculation of the radiation difference between the target and the background based on the measured imaging result of the target includes: Combining the measured imaging results of the target, the number of voltage quantization bits and the performance parameters of the infrared imaging system, the target radiation intensity and background radiation intensity are dequantized; The difference between the target radiation intensity and the background radiation intensity, ie, the radiation difference, is calculated.

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