CN118817256A - A moving target detection performance evaluation method for infrared optoelectronic imaging system based on NVThermIP model - Google Patents

Abstract

The present invention provides a method for evaluating the moving target detection performance of an infrared optoelectronic imaging system based on the NVThermIP model. The method comprehensively considers the maneuverability of the target, the radiation difference between the target and the background, the contrast threshold function of the infrared system and the influence of the human eye vision model on the target detection performance, and takes the spatial frequency weighted integral value of the target contrast exceeding the contrast threshold of the infrared optoelectronic system as the target information amount obtained by the infrared system, thereby obtaining the target equivalent period number under the set observation distance, and calculating the detection probability in combination with the target transfer probability function, so that the calculation result of the infrared moving target detection performance is more in line with reality.

Description

A moving target detection performance evaluation method for infrared optoelectronic imaging system based on NVThermIP model

Technical Field

The present invention belongs to the technical field of infrared optoelectronic imaging system performance evaluation, and specifically relates to a method for evaluating the moving target detection performance of an infrared optoelectronic imaging system based on an NVThermIP model.

Background Art

Optoelectronic imaging systems are widely used in security monitoring, unmanned driving, industrial inspection and other fields. With the continuous improvement of infrared optoelectronic imaging system technology, structure and design technology, higher requirements are put forward for the optimization and improvement of infrared optoelectronic imaging system performance evaluation methods, so as to improve the accuracy of demonstration, design and analysis of infrared optoelectronic imaging systems. In view of the shortcomings of experimental methods and semi-physical simulation methods, such as poor adaptability to complex and changing environments, high funding requirements, and difficulty in achieving system performance prediction and parameter optimization, the optoelectronic system evaluation method based on the performance theoretical model can break through the above technical difficulties, realize the performance evaluation and optimization design of the optoelectronic system, and help analyze the system performance, which has important guiding significance for the accurate evaluation of the performance prediction of infrared optoelectronic imaging systems.

At present, there are generally three models for evaluating the performance of optoelectronic systems. The first is the MRTD model based on the Johnson criterion, which ignores the limitation of the eye contrast threshold and has subjective factors, and the accuracy of performance evaluation needs to be improved; the second is the triangle orientation discrimination threshold performance model (TOD) based on the Johnson criterion, which ignores the transfer characteristics within the highest spatial resolution of the system and cannot accurately evaluate the performance of the focal plane infrared optoelectronic imaging system and the digital image processing system; the third is the NVThermIP model based on the target task performance (TTP) criterion, which introduces the imaging characteristics of the sensor and the visual mechanism of the human eye, and still has good prediction results under low contrast conditions, but generally evaluates the static performance of the optoelectronic imaging system and cannot achieve accurate evaluation of the detection performance of maneuvering targets.

Based on the above research, there are methods for evaluating the detection distance and detection probability of moving targets, such as SVM method, frame difference method, and deep learning method. However, most of these methods do not consider the impact of human vision on moving target detection during the evaluation process, resulting in poor accuracy of the evaluation results; at the same time, the model itself is based on the perspective of target detection, and the research on the performance parameters and detection capabilities of infrared optoelectronic imaging systems is not perfect, making it difficult to achieve accurate evaluation of moving target detection capabilities.

Summary of the invention

The purpose of the present invention is to overcome the shortcomings of the existing optoelectronic imaging system detection performance evaluation method that cannot realize the evaluation of maneuvering target detection performance or has poor evaluation accuracy, and provide an infrared optoelectronic imaging system moving target detection performance evaluation method based on the NVThermIP model. The method comprehensively considers the influence of the maneuverability of the target, the radiation difference between the target and the background, the contrast threshold function of the infrared system and the human eye vision model on the moving target detection performance, so that the infrared moving target detection performance evaluation result is more in line with reality, and the accurate prediction of the maneuvering target detection performance of the optoelectronic imaging system is realized.

To achieve the above purpose, the technical solution provided by the present invention is:

A moving target detection performance evaluation method for an infrared optoelectronic imaging system based on the NVThermIP model includes the following steps:

Step 1, building an infrared optoelectronic imaging system moving target detection performance evaluation system, the evaluation system comprising an infrared optoelectronic imaging system, a standard black body source, a rangefinder, a black target, a movable vehicle, a black background and a radiation meter;

The standard black body source is installed on a movable trolley, and the black target is installed at the window of the standard black body source;

The infrared photoelectric imaging system and the radiometer are mounted outside the movable vehicle, and the radiometer is used to collect the intrinsic temperature of the target;

Step 2, starting the movable vehicle, performing a black target movement simulation, continuously collecting target imaging features, and obtaining measurement parameters of a standard black body source at different temperatures, wherein the measurement parameters include target temperature, background temperature, and detection distance;

Step 3, calculating the atmospheric transmittance of the target and the infrared photoelectric imaging system at different detection distances, and obtaining a relationship curve τ(R) between the detection distance and the atmospheric transmittance;

Step 4: construct a moving target detection probability calculation model based on NVThermIP and initialize the parameters of the probability calculation model; the parameters include target temperature, background temperature, detection distance and infrared photoelectric imaging system parameters;

Step 5, calculating the target radiation emittance _MT and the background radiation emittance _MB according to the measurement parameters obtained in step 2, and calculating the target background contrast _Ctgt according to the target radiation emittance and the background radiation emittance;

The target background contrast

Where, _MT is the target radiation emittance, _MB is the background radiation emittance, ΔT is the temperature difference between the target and the background, and _TB is the background temperature;

Step 6, calculating and obtaining the system contrast threshold function CTF _sys according to the modulation transfer function MTF of the infrared optoelectronic imaging system and the contrast threshold function CTF _eye (f) of the human eye;

The modulation transfer function MTF of the infrared optoelectronic imaging system is MTF _op ·MTF _det ·MTF _cic ·MTF _dis ,

Where, MTF _op , MTF _det , MTF _cic and MTF _dis are the modulation transfer function of the optical system, the modulation transfer function of the infrared photoelectric imaging system, the modulation transfer function of the photoelectric conversion circuit and the modulation transfer function of the display, respectively;

Where f is the spatial frequency, σ is the displayed RMS noise, L is the display brightness, and α is the correction factor for noise to brightness;

b＝0.3(1+100/L) ^0.15 ,

c＝0.06,

Where θ is the target angle, _Atgt is the target area, M is the system magnification, and R is the distance between the target and the infrared optoelectronic imaging system;

Step 7, replace the limit spatial frequency in the Johnson criterion with the spatial frequency at which the target background contrast C _tgt exceeds the system contrast threshold function CTF _sys by weighted integration, calculate the target task performance TTP, and obtain the target image information;

In the formula: ξ _high and ξ _low are the upper and lower limits of the spatial frequency, ξ _high is the spatial frequency value corresponding to the intersection of the system contrast threshold function CTF _sys and the target background contrast C _tgt , and ξ _low is taken as 0; the unit is cyc/mrad.

Step 8, according to the target observation distance and the critical characteristic size of the target, calculate the target task equivalent cycle number at the corresponding observation distance,

The equivalent cycle number of the target task is

The critical characteristic size of the target is obtained by taking the square root of the target area A _tgt ;

Step 9, using the target transfer probability function where 50% of the points fall on the target task performance curve TTP, the moving target detection probability P is calculated;

E＝1.51+0.24(V/V ₅₀ ),

Where E is the target detection task level; _V50 is the number of resolvable cycles with a task completion probability of 50%, which is obtained by experimental measurement; and V is the number of equivalent cycles of the target task.

Furthermore, the step 2 comprises the following steps:

Step 2.1, set the temperature of the standard blackbody source, and collect the blackbody equivalent temperature of the target and background through the radiometer;

Step 2.2, setting the moving speed, moving trajectory and detection distance of the movable car, and continuously collecting the infrared imaging characteristics of the target when the car moves;

Step 2.3, adjust the temperature of the standard blackbody source, repeat steps 2.1 and 2.2, and obtain the measurement parameters at different blackbody temperatures.

Furthermore, the step 3 comprises the following steps:

Step 3.1, fix the position of the infrared photoelectric imaging system and the height of the target, adjust the distance from the radiometer to the target at equal distances, and collect the intrinsic temperature of the target at different detection distances;

Step 3.2, place a black body with a temperature equivalent to the intrinsic temperature of the target at different positions, measure the radiation brightness of the black body in the infrared photoelectric imaging system, and calculate the black body radiation brightness value by Planck's formula, and take the ratio of the target body radiation brightness value to the black body radiation brightness value as the atmospheric transmittance at the corresponding detection distance;

Step 3.3, according to the atmospheric transmittance at different detection distances obtained in step 3.2, obtain a relationship curve τ(R) between the detection distance and the atmospheric transmittance.

Furthermore, in step 3.1, the distance between the radiation meter and the target is adjusted at equal intervals with 1 meter as the interval distance.

Furthermore, in step 5, the target radiation emittance _MT and the background radiation emittance _MB are calculated according to the following formula:

The target radiation emittance _MT calculation formula is:

The background radiation emittance _MB calculation formula is:

Wherein, C ₁ is the first radiation constant, C ₁ =(3.7415±0.0003)×10 ⁸ (W·μm ⁴ ·m ^-2 ); λ ₁ and λ ₂ are the upper and lower limits of the spectral range of the infrared optoelectronic imaging system, in μm; C ₂ is the second radiation constant, C ₂ =(1.43879±0.00019)×10 ⁴ (μm·K); _TT is the target temperature, _TB is the background temperature, in K; ε(λB) and ε(λT) are the background spectral emissivity and target spectral emissivity, respectively.

The advantages of the present invention are:

In the method of the present invention, an evaluation experimental system is firstly built, and the imaging features of the target are continuously collected by the infrared photoelectric imaging system under test. In the process of calculating the detection probability based on the NVThermIP model, the maneuverability of the target, the radiation difference between the target and the background, the infrared system contrast threshold function and the human eye vision model are comprehensively considered to affect the detection performance of the moving target. The spatial frequency weighted integral value of the target contrast exceeding the contrast threshold of the infrared photoelectric system is used as the target information obtained by the infrared system, so as to obtain the target equivalent cycle number under a certain observation distance, and the detection probability is obtained by combining the target transfer probability function calculation. By comparing with the experimental results, the evaluation results of the method of the present invention are highly accurate, making the evaluation results of the infrared moving target detection performance more in line with the actual situation.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

FIG1 is a schematic diagram of an evaluation system constructed in the method of the present invention;

FIG2 is a flowchart of calculating the moving target detection performance probability using the model method of the present invention;

FIG3 is a flowchart of the evaluation calculation process of the probability of detecting moving targets by manual discrimination;

FIG. 4 is a comparison diagram of the evaluation results of the method of the present invention and the theoretical results.

Explanation of the reference numerals: 1- movable trolley, 2- blackbody fixing bracket, 3- standard blackbody source, 4- hollow target, 5- infrared photoelectric imaging system, 6- radiation meter.

DETAILED DESCRIPTION

Embodiments of the present invention are described in detail below. The embodiments are exemplary and intended to be used to explain the present invention, but should not be construed as limiting the present invention.

1-2, a method for evaluating the moving target detection performance of an infrared optoelectronic imaging system based on the NVThermIP model specifically includes the following steps:

Step 1: Build an evaluation experimental system.

Referring to Figure 1, the evaluation experimental system includes a movable trolley 1, a black body fixing bracket 2, a standard black body source 3, a hollow target 4, an infrared photoelectric imaging system 5, a rangefinder, a radiation meter 6 and a black cardboard. The pre-experimental preparations reflect the consideration of experimental equipment, environment, calibration comprehensiveness and mobility to ensure that the experiment can proceed smoothly and obtain accurate and reliable calibration results. In addition, the experiment takes into account the maneuverability of the target, making the infrared moving target detection performance evaluation method more comprehensive, accurate and practical, and improving the performance and reliability of the system.

In order to simulate the contour characteristics of targets of different types, black cardboard was cut into different shapes as hollow targets to facilitate multiple tests and evaluate the detection performance of the infrared optoelectronic imaging system for moving targets.

First, a cut hollow target is pasted at the window position of the standard black body source 3, and then the standard black body source 3 is installed on the movable trolley 1 through the black body fixing bracket 2. The infrared photoelectric imaging system 5 and the radiometer 6 are placed outside the movable trolley. The infrared photoelectric imaging system 5 is used to collect the imaging characteristics of the target under different temperatures and shapes, and the radiometer 6 is used to obtain the target intrinsic temperature. When conducting the evaluation, the calibration of the infrared photoelectric imaging system needs to be completed first.

Black cardboard was used as the target background to simulate a uniform background.

The temperature of the standard black body source 3 is set, and the standard black body source is fixed by using a target fixing device.

Step 2: Target radiation data collection and target trajectory simulation.

Set the temperature of the standard blackbody source, use this temperature as the target temperature, and collect the blackbody equivalent temperature of the target and background through the radiometer.

The moving speed, moving trajectory and detection distance of the movable car are set, the movable car is started, the position of the infrared photoelectric imaging system 5 is kept unchanged, and the imaging features of the hollowed-out target on the movable car are continuously collected by the infrared photoelectric imaging system.

By adjusting the temperature of the standard blackbody source and specifying different target movement speeds, target sizes, imaging distances and other conditions, the position of the infrared photoelectric imaging system is kept unchanged and the imaging features of the target are continuously collected.

During the experiment, the measurement parameters at different panel blackbody temperatures are obtained, including target temperature, background temperature, detection distance, etc. These parameters provide data for subsequent model calculations.

Step 3, obtaining the atmospheric transmittance between the hollow target 4 and the infrared photoelectric imaging system.

First, the position of the infrared photoelectric imaging system and the height of the target are fixed, and the distance from the radiometer 6 to the target, i.e., the detection distance, is adjusted every one meter to collect the target intrinsic temperature;

Then, a black body with a temperature equivalent to the intrinsic temperature of the target is placed at different positions, and the radiation brightness of the black body in the infrared photoelectric imaging system is measured. At the same time, the black body radiation brightness value is calculated by Planck's formula, and the ratio of the target body radiation brightness value to the black body radiation brightness value is used as the atmospheric transmittance at the corresponding detection distance.

By adopting the above method, the atmospheric transmittance data of the target and the infrared photoelectric imaging system at different detection distances are obtained, and the relationship curve τ(R) between the detection distance and the atmospheric transmittance is obtained accordingly.

Step 4: Establish a moving target detection probability calculation model based on NVThermIP and initialize the parameters of the probability calculation model, which include target temperature, background temperature, detection distance and infrared photoelectric imaging system parameters.

Considering the influence of target background contrast, system noise contrast threshold, detection distance and target transfer function on detection performance, the constructed moving target detection probability calculation model includes parameter initialization module, target background contrast calculation module, infrared optoelectronic imaging system MTF calculation module, human eye and display noise degradation calculation module, system contrast threshold calculation module, target task performance TTP calculation module and detection probability calculation module.

Step 5: Calculate the target-background contrast.

The target-background contrast ratio is calculated by setting the target and background with different temperature differences and combining the relationship curve between the distance and the atmospheric transmittance τ(R) obtained in step 3.

First, according to the temperature data of the hollowed-out target and background obtained in step 2, the target radiation emittance _MT and the background radiation emittance _MB are calculated according to the following formula;

Wherein, C ₁ is the first radiation constant, C ₁ =(3.7415±0.0003)×10 ⁸ (W·μm ⁴ ·m ^-2 ); λ ₁ and λ ₂ are the upper and lower limits of the spectral range of the infrared optoelectronic imaging system;

C ₂ is the second radiation constant, C ₂ =(1.43879±0.00019)×10 ⁴ (μm·K); _TT is the target temperature, _TB is the background temperature, the unit is K; ε(λB) and ε(λT) are the background spectral emissivity and the target spectral emissivity, respectively.

Then, the target background contrast C _tgt is calculated according to the formula, and the target background contrast calculation formula is:

Where _MT is the target radiation emittance, _MB is the background radiation emittance, ΔT is the temperature difference between the target and the background, and _TB is the background temperature.

Step 6: Calculate the system contrast threshold function CTF _sys .

The system contrast threshold function is obtained by superimposing the modulation effects of each module of the system to obtain the infrared photoelectric system imaging degradation effect. In the calculation process, the human eye contrast threshold function CTF _eye is introduced to calculate the system contrast threshold function CTF _sys . The human eye and display noise are modeled by assuming the observer's CTF degradation. The modulation transfer function MTF of the infrared photoelectric imaging system is MTF = MTF _op ·MTF _det ·MTF _cic ·MTF _dis ,

Where MTF _op , MTF _det , MTF _cic and MTF _dis are the modulation transfer function of the optical system, the modulation transfer function of the infrared photoelectric imaging system, the modulation transfer function of the photoelectric conversion circuit and the modulation transfer function of the display, respectively.

The signal in the scene is modulated by the optical system of the sensor, the infrared photoelectric imaging system, the electronic circuit, the display and the human eye, and the image degradation MTF introduced above is calculated. The noise effect is modeled by the human eye contrast threshold function CTF:

Where f is the spatial frequency, σ is the displayed RMS noise, L is the display brightness, and α is the correction factor for noise to brightness;

b＝0.3(1+100/L) ^0.15 ,

c＝0.06,

Where θ is the target angle, _Atgt is the target area, M is the system magnification, and R is the distance between the target and the infrared optoelectronic imaging system.

Step 7, the spatial frequency at which the target background contrast C _tgt exceeds the system contrast threshold function CTF _sys is used for weighted integration to replace the limit spatial frequency in the Johnson criterion, calculate the target task performance TTP, and obtain the target image information amount.

When the target signal exceeds the threshold of the system, it is considered that the target information can be obtained. The spatial frequency weighted integral value of the target contrast exceeding the contrast threshold of the infrared optoelectronic system is used as the target information obtained by the infrared system to define the TTP function:

Where ξ _high and ξ _low are the upper and lower limits of the spatial frequency, ξ _high is the spatial frequency value corresponding to the intersection of the system contrast threshold function CTF _sys and the target background contrast C _tgt , and ξ _low is 0; the unit is cyc/mrad.

Step 8, combining the target observation distance and the critical characteristic size of the target, calculate the target task equivalent cycle number V of the target at this distance.

The equivalent cycle number of the target task is

The critical characteristic size of the target is obtained by taking the square root of the target area;

Step 9, calculate the target detection probability P using the target transfer probability function where 50% of the points fall on the target recognition task curve TTP.

The target detection probability calculation formula is:

E = 1.51 + 0.24 (V/V ₅₀ ).

Where E is the target detection task level; _V50 is the number of resolvable cycles with a 50% probability of completing the task, which is obtained by experimental measurement; and V is the number of equivalent cycles of the target task.

In order to verify the moving target detection performance evaluation method of the infrared optoelectronic imaging system based on the NVThermIP model of the present invention, the accuracy of the detection performance evaluation of the infrared optoelectronic imaging system for moving targets under different target shapes, imaging distances, target sizes, and target movement speeds was evaluated. Under the condition that the system parameter input settings were consistent, the experimental measurement results based on human eye vision were compared with the evaluation results of the method of the present invention.

3 , for targets with different shapes and different target background differences, the target detection probability is calculated by manual discrimination. According to the same setting temperature as the method of the present invention, the standard black body source temperature T ₁ , T ₂ , ..., T _n is adjusted, the imaging characteristics of each target at different temperatures are collected, and multiple personnel are organized to interpret the imaging results of each target respectively. The observer must judge whether the target is detectable, that is, whether the target is detectable or not. By calculating the ratio between the number of people who can detect the target and the total number of observers, the experimental target detection probability under different target sizes and target background temperature differences is obtained.

The method of the present invention is used to evaluate the detection probability of different targets of the infrared optoelectronic imaging system under the same conditions, and then the evaluation results of the present invention are compared and analyzed with the artificial level evaluation results (theoretical results), as shown in Figure 4. The results show that the infrared moving target detection performance evaluation method proposed in the present invention can detect moving targets, and the greater the speed of the moving target and the greater the background temperature difference, the higher the detection probability, that is, the detection performance of the method of the present invention for moving targets is better than that for static targets.

The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should be included in the protection scope of the present invention.

Claims (5)

1. A method for evaluating the moving target detection performance of an infrared optoelectronic imaging system based on the NVThermIP model, characterized in that it comprises the following steps: Step 1, building an infrared optoelectronic imaging system moving target detection performance evaluation system, the evaluation system comprising an infrared optoelectronic imaging system, a standard black body source, a rangefinder, a black target, a movable vehicle, a black background and a radiation meter; The standard black body source is installed on a movable trolley, and the black target is installed at the window of the standard black body source; The infrared photoelectric imaging system and the radiometer are mounted outside the movable vehicle, and the radiometer is used to collect the intrinsic temperature of the target; Step 2, starting the movable vehicle, performing a black target movement simulation, continuously collecting target imaging features, and obtaining measurement parameters at different standard blackbody source temperatures, wherein the measurement parameters include target temperature, background temperature, and detection distance; Step 3, calculating the atmospheric transmittance of the target and the infrared photoelectric imaging system at different detection distances, and obtaining a relationship curve τ(R) between the detection distance and the atmospheric transmittance; Step 4: construct a moving target detection probability calculation model based on NVThermIP and initialize the parameters of the probability calculation model; the parameters include target temperature, background temperature, detection distance and infrared photoelectric imaging system parameters; Step 5, calculating the target radiation emittance _MT and the background radiation emittance _MB according to the measurement parameters obtained in step 2, and calculating the target background contrast _Ctgt according to the target radiation emittance and the background radiation emittance; The target background contrast Where, _MT is the target radiation emittance, _MB is the background radiation emittance, ΔT is the temperature difference between the target and the background, and _TB is the background temperature; Step 6, calculating and obtaining the system contrast threshold function CTF _sys according to the modulation transfer function MTF of the infrared optoelectronic imaging system and the contrast threshold function CTF _eye (f) of the human eye; The modulation transfer function MTF of the infrared optoelectronic imaging system is MTF _op ·MTF _det ·MTF _cic ·MTF _dis , Where, MTF _op , MTF _det , MTF _cic and MTF _dis are the modulation transfer function of the optical system, the modulation transfer function of the infrared photoelectric imaging system, the modulation transfer function of the photoelectric conversion circuit and the modulation transfer function of the display, respectively; Where f is the spatial frequency, σ is the displayed RMS noise, L is the display brightness, and α is the correction factor for noise to brightness; b＝0.3(1+100/L) ^0.15 , c＝0.06, Where θ is the target angle, _Atgt is the target area, M is the system magnification, and R is the distance between the target and the infrared optoelectronic imaging system; Step 7, replace the limit spatial frequency in the Johnson criterion with the spatial frequency at which the target background contrast C _tgt exceeds the system contrast threshold function CTF _sys by weighted integration, calculate the target task performance TTP, and obtain the target image information; In the formula: ξ _high and ξ _low are the upper and lower limits of the spatial frequency, ξ _high is the spatial frequency value corresponding to the intersection of the system contrast threshold function CTF _sys and the target background contrast C _tgt , and ξ _low is taken as 0; the unit is cyc/mrad. Step 8: Calculate the target mission equivalent cycle number of the target at the corresponding observation distance according to the target observation distance and the critical characteristic size of the target. The target task equivalent cycle number is The critical characteristic size of the target is obtained by taking the square root of the target area A _tgt ; Step 9, using the target transfer probability function where 50% of the points fall on the target task performance curve TTP, the moving target detection probability P is calculated; E＝1.51+0.24(V/V ₅₀ ), Where E is the target detection task level; _V50 is the number of resolvable cycles with a task completion probability of 50%, which is obtained by experimental measurement; and V is the number of equivalent cycles of the target task. 2. According to the method for evaluating the moving target detection performance of the infrared optoelectronic imaging system of claim 1, it is characterized in that the step 2 comprises the following steps: Step 2.1, set the temperature of the standard blackbody source, and collect the blackbody equivalent temperature of the target and background through the radiometer; Step 2.2, setting the moving speed, moving trajectory and detection distance of the movable car, and continuously collecting the infrared imaging characteristics of the target when the car moves; Step 2.3, adjust the temperature of the standard blackbody source, repeat steps 2.1-2.2, and obtain the measurement parameters of the standard blackbody source at different temperatures. 3. According to the method for evaluating the moving target detection performance of the infrared optoelectronic imaging system of claim 1, it is characterized in that the step 3 comprises the following steps: Step 3.1, fix the position of the infrared photoelectric imaging system and the height of the target, adjust the distance from the radiometer to the target at equal distances, and collect the intrinsic temperature of the target at different detection distances; Step 3.2, place a black body with a temperature equivalent to the intrinsic temperature of the target at different positions, measure the radiation brightness of the black body in the infrared photoelectric imaging system, and calculate the black body radiation brightness value by Planck's formula, and take the ratio of the target body radiation brightness value to the black body radiation brightness value as the atmospheric transmittance at the corresponding detection distance; Step 3.3, according to the atmospheric transmittance at different detection distances obtained in step 3.2, obtain a relationship curve τ(R) between the detection distance and the atmospheric transmittance. 4. The method for evaluating the moving target detection performance of an infrared optoelectronic imaging system according to claim 3 is characterized in that in step 3.1, the distance from the radiation meter to the target is adjusted at equal intervals with an interval of 1 meter. 5. The method for evaluating the moving target detection performance of an infrared optoelectronic imaging system according to claim 1, characterized in that in step 5, the target radiation emittance _MT and the background radiation emittance _MB are calculated according to the following formula: The target radiation emittance _MT calculation formula is: The background radiation emittance _MB calculation formula is: Wherein, C ₁ is the first radiation constant, C ₁ =(3.7415±0.0003)×10 ⁸ (W·μm ⁴ ·m ^-2 ); λ ₁ and λ ₂ are the upper and lower limits of the spectral range of the infrared optoelectronic imaging system; C ₂ is the second radiation constant, C ₂ =(1.43879±0.00019)×10 ⁴ (μm·K); _TT is the target temperature, _TB is the background temperature, the unit is K; ε(λB) and ε(λT) are the background spectral emissivity and the target spectral emissivity, respectively.