Short-range ground target linear array infrared detection signal rapid simulation method

Abstract

The invention discloses a short-range ground target infrared detection signal rapid simulation method, and belongs to the technical field of infrared detection. The implementation method comprises the following steps: considering spontaneous radiation of a target and environmental radiation including solar radiation, atmospheric radiation and ground radiation, combining a geometric measurement model of a linear array infrared detection system, establishing an external optical channel response model of the linear array infrared detection system, and quantifying pixel-level entrance pupil infrared radiation of a short-range infrared detection system; an optical system, a linear array infrared detector and a signal processing circuit are considered, an internal electric signal response model of the linear array infrared detection system is established through a mixed mode of parametric modeling and analog circuit analysis, and an external optical channel response model is connected in parallel to establish a full-link physical response model of the linear array infrared detection system; a cross-platform joint simulation application program is established, a full-link physical response model is driven based on a three-dimensional virtual environment in combination with a parallel ray tracing and multi-domain synchronous calculation method, and rapid simulation of output signals of the linear array infrared detection system is achieved.

Description

Technical Field

[0001] The invention relates to a method for quickly simulating infrared detection signals of a short-range ground target linear array, belonging to the technical field of infrared detection. Background Art

[0002] Infrared detection technology for short-range ground targets is primarily used in infrared fuzes. During the dynamic rendezvous between a moving platform and a target, a linear array infrared detection system is used to capture the target by responding to the infrared radiation difference between the target surface and the background, and to control the detonation of ammunition according to a predetermined strategy. However, the effective implementation of intelligent sensing and control requires extensive data collection. Real battlefield data is limited and subject to privacy restrictions, and the cost of equivalent experiments is high, seriously hindering the development of intelligent weaponry. Therefore, using computer simulation to generate high-fidelity data has become an important research method. By establishing key battlefield elements in a virtual environment and building a precise model of the infrared radiation transmission process, the required infrared target detection data under various battlefield conditions can be controlled and obtained, which can quickly provide a data source for algorithm design and testing.

[0003] A linear array infrared detection system consists of a receiving optical system, a linear array infrared detector, and signal processing circuitry. It relies on the target's radiation characteristics for passive detection, distinguishing the target from the surrounding environment through differences in the output electrical signal. Current research on infrared target detection simulation is primarily divided into physical modeling and data-driven approaches. Physical modeling approaches, based on infrared radiation theory and atmospheric attenuation, model infrared radiation characteristics along the radiation path by taking into account solar radiation, atmospheric transmission, and target self-heating under different operating conditions. Finally, static three-dimensional infrared detection signals are generated through scaling or computer rendering techniques. However, these approaches fail to comprehensively model both the external and internal responses of infrared detection systems, and effective simulation methods for linear array infrared detection systems in dynamic intersection scenarios are still lacking. Data-driven approaches primarily utilize deep learning techniques for cross-domain conversion from visible light images to infrared images. Effective network components are designed to enhance the adaptability of infrared image generation to diverse scenarios. These generative approaches rely on large datasets and primarily focus on infrared images, with little attention paid to signal-level simulation.

[0004] In the application of short-range ground target infrared detection, subtle differences in the output electrical signals of the linear array infrared detection system affect the subsequent execution of the control strategy. Unified modeling of the external and internal responses of the linear array infrared detection system can achieve high-fidelity pixel-level infrared detection signal simulation, providing effective data support for algorithm design and testing, which is of great significance to the development of short-range infrared detection technology. Summary of the Invention

[0005] In response to the lack of data on linear array infrared detection signals for short-range ground targets, the present invention aims to provide a method for rapid simulation of linear array infrared detection signals for short-range ground targets. This method comprehensively considers the coupling relationship between the target, environment, and sensor, and combines the external optical channel response model and internal electrical signal response model of the linear array infrared detection system to establish a full-link physical response model of the linear array infrared detection system. Taking into account the actual application scenarios of the linear array infrared detection system, a dynamic simulation method based on parallel ray tracing and multi-domain synchronous computing is established by building a cross-platform joint simulation framework. According to the dynamic simulation method, a hybrid simulation of numerical calculation and circuit analysis of the linear array infrared detection system is deployed to achieve rapid simulation of the signals of the linear array infrared detection system for short-range ground targets.

[0006] The purpose of the present invention is achieved through the following technical solutions:

[0007] The present invention discloses a method for rapid simulation of infrared detection signals of short-range ground targets. The method considers the spontaneous radiation of the target and the environmental radiation including solar radiation, atmospheric radiation and ground radiation, combines the geometric measurement model of the linear array infrared detection system, establishes an external optical channel response model of the linear array infrared detection system, and quantifies the pixel-level entrance pupil infrared radiation of the short-range infrared detection system; considers the optical system, linear array infrared detector and signal processing circuit, establishes the internal electrical signal response model of the linear array infrared detection system through a hybrid mode of parametric modeling and analog circuit analysis, and establishes the full-link physical response model of the linear array infrared detection system in parallel with the external optical channel response model; establishes a cross-platform joint simulation application, constructs scene elements covering terrain, lighting, targets and linear array infrared detection systems based on a three-dimensional virtual environment, simulates the dynamic intersection process, combines parallel ray tracing with multi-domain synchronous calculation methods to drive the full-link physical response model, and realizes rapid simulation of the output signal of the linear array infrared detection system.

[0008] The present invention discloses a method for rapidly simulating a short-range ground target linear array infrared detection signal, comprising the following steps:

[0009] Step 1: Establish an infrared radiation model that covers the target's spontaneous radiation, solar radiation, sky radiation, and ground radiation, and calculate the total infrared radiation per unit area of ​​the target;

[0010] The infrared radiation model is used to characterize the zero-line-of-sight infrared radiation of ground targets. The modeling of each radiation component is as follows:

[0011] Step 1.1: Spontaneous radiation. The target's own radiation is considered isotropic. The equivalent blackbody radiation generated by any object with an absolute temperature above 0 degrees is calculated as follows:

[0012]

[0013] Where T is the temperature, λ1 and λ2 represent the infrared band range, and c1 is the first radiation constant, which is c1 = 3.741 × 10 -16 W·m 2 , c2 is the second radiation constant, and its value is 1.438×10 -2 m.K.

[0014] Step 1.2: Solar radiation. The infrared radiation E that reaches the upper boundary of the atmosphere sun The calculation is as follows:

[0015]

[0016] Where, E const represents the solar constant, which is approximately 1367W / m 2 ; σ is the Stefan-Boltzmann constant, which is 5.6704×10 -8 W / (m 2 ·K 4 );T sum is the average temperature of the sun's equivalent black body, which is about 5770K. The irradiance E of the solar radiation per unit area is d The calculation is as follows:

[0017] E d =E sun C s p m cosθ (3)

[0018] Where C s represents the correction factor caused by the change in the distance between the sun and the earth, p m represents atmospheric attenuation, p is atmospheric transparency, m is atmospheric mass coefficient, and θ is the solar incidence angle.

[0019] Step 1.3: Sky radiation. Sky radiation consists of solar scattered radiation and atmospheric radiation, and is affected by atmospheric conditions. The radiation generated by solar scattered radiation E s1 The calculation is as follows:

[0020]

[0021] Where, α s is the solar altitude angle. Considering weather factors, a full-day atmospheric infrared radiation model related to clear sky radiation and cloud coefficient is established, and the calculation is as follows:

[0022]

[0023] Where C d represents cloud factor, RH represents relative humidity, E cs represents the radiation under clear sky conditions, ε csClear sky radiation emissivity. Considering the target surface element inclination angle β, the sky radiation E s It is the superposition of two parts and is calculated as follows:

[0024]

[0025] Step 1.4: Ground radiation. Ground radiation includes self-radiation and reflection of solar and sky radiation. The ground’s self-radiation E g0 By calculating the equivalent blackbody radiation, combining equations (3) and (6), we can get the ground radiation E g The calculation is as follows:

[0026]

[0027] Where, ε g is the ground emissivity, ρ g is the ground reflectivity, and ε is defined o is the target unit surface emissivity, ρ t is the reflectivity of the target unit surface element, the total radiation E of the target unit surface element is calculated as follows:

[0028] E=ε o E o +ρ t (E d +E s +E g ) (8)

[0029] Equations (1), (6), (7) and (8) constitute the infrared radiation model.

[0030] Step 2: Construct a geometric measurement model of the linear array infrared detection system. Combined with the infrared radiation model in step 1, the external optical channel response model of the linear array infrared detection system is obtained to quantify the pixel-level entrance pupil infrared radiation of the linear array infrared detection system.

[0031] The linear array infrared detection system uses a push-broom detection system. When the dynamic platform is in flight, the linear array infrared detection system can only respond to infrared radiation within a certain field of view. The optical center of the linear array infrared detection system is defined as the coordinate origin, the direction of motion is the positive direction of the x-axis, and the positive direction of the z-axis is upward. The single-pixel detection field of view is equivalent to a rectangular area. The normalized direction vector from the origin to the center of the rectangle is calculated as follows:

[0032]

[0033] Where ψ represents the angle of attack, is the angle between the detection direction of the i-th pixel and the x-axis direction. The length l and width w of the single pixel detection field of view are calculated as follows:

[0034]

[0035] Where r represents the detection distance, s l Represents the length of a single pixel of the array detector, s w Represents the width of a single pixel, and F represents the focal length of the optical system. Equations (8) and (9) constitute the geometric measurement model. Assuming that the target surface conforms to the radiation characteristics of the Lambertian surface, the infrared radiation E of a single pixel reaching the entrance pupil of the optical system is in The calculation is as follows:

[0036]

[0037] Where n represents the number of surface elements covered in the l×w detection field of view determined by a single pixel, τ atm Represents the atmospheric transmittance between the target and the infrared detection system, A opt and A i are the optical lens cross section and target surface area, ζ i1 and ζ i2 Represent the normal line of the optical lens cross section surface element and the target surface element normal and r i Angle.

[0038] Equations (8) and (11) constitute the external optical channel response model of the linear array infrared detection system.

[0039] Step 3: Establish an internal electrical signal response model of the linear array infrared detection system covering the receiving optical system, linear array infrared detector and signal processing circuit. Combined with the external optical channel response model in step 2, establish a full-link physical response model of the linear array infrared detection system.

[0040] The infrared radiation entering the pupil is focused onto the photosensitive surface of the detector through the receiving optical system. Its radiation flux is calculated from the optical system parameters as follows:

[0041]

[0042] Where, τ opt Represents the transmittance of the optical lens, A d is the area of ​​the detector's photosensitive surface, and D is the diameter of the optical system's entrance pupil. The photocurrent generated by the photoelectric effect is calculated by the following formula:

[0043]

[0044] In the formula, η represents the quantum efficiency; q is the elementary charge; h is the Planck constant; and c is the speed of light. Equations (12) and (13) form the photoelectric effect model. The weak photocurrent generated by the incident pupil infrared radiation is converted into a voltage signal through a bias circuit. Calibration testing is performed to determine the operating bias current that achieves the optimal signal-to-noise ratio. The converted voltage signal is then amplified by a two-stage operational amplifier circuit connected in series. A high-pass filter is then configured to avoid amplifying noise signals. The output of the amplifier circuit is the internal electrical signal response of the linear array infrared detection system.

[0045] The external optical channel response model and the internal electrical signal response model of the linear array infrared detection system are combined to form a full-link physical response model of the linear array infrared detection system.

[0046] Step 4. Establish a cross-platform joint simulation application, simulate dynamic intersection scenarios based on a three-dimensional virtual environment, construct scene elements covering terrain, lighting, targets, and linear array infrared detection systems, drive the full-link physical response model through parallel ray tracing and multi-domain synchronous calculation methods, output the linear array infrared detection system simulation signal, and realize rapid simulation of the linear array infrared detection system output signal.

[0047] To achieve hybrid simulation of numerical calculations and analog circuit signals, a Simulink-PSpice co-simulation application was constructed. Based on actual application scenarios, scene elements covering terrain, lighting, targets, and the linear array infrared detection system were established to simulate dynamic intersection processes in a 3D virtual environment. Parallel ray tracing was used to deploy the geometric measurement model. Based on the infrared radiation model, pixel-by-pixel numerical calculations of the linear array infrared detection system's entrance pupil infrared radiation were performed to drive the external optical channel response model. PSpice was used to establish the linear array infrared detection system's simulation circuitry, driving the internal electrical signal response model. The co-simulation application was used to achieve hybrid simultaneous simulation of numerical calculations and analog circuits, generating simulation signals for the linear array infrared detection system and enabling rapid simulation of the system's output signals.

[0048] Step 5: Establish evaluation indicators, verify the simulation data based on the evaluation indicators and measured data, and select simulation models that meet the preset accuracy.

[0049] The root mean square error (RMSE) and Pearson correlation coefficient (PCC) are used to evaluate the similarity between the simulated output signal and the measured signal. Given two sets of time series signals, the root mean square error is calculated as follows:

[0050]

[0051] Where n represents the number of sequence sampling points; x i represents the simulation value; yi The RMSE value of the overall signal is less than ±10% within the measurement range, which proves its effectiveness. The Pearson correlation coefficient is calculated as follows:

[0052]

[0053] Where μx and μy represent the average of the simulated and measured values, respectively. The PCC range is -1 to 1, with approaches to 1 indicating a positive linear correlation and approaches to -1 indicating a negative linear correlation. A PCC value of the overall signal greater than 0.85 indicates validity. When both RMSE and PCC meet the validation criteria, the simulation model is exported and packaged for subsequent engineering applications.

[0054] It also includes step six, using the simulation model in step five to simulate various dynamic intersection scenarios by setting different parameters, and obtaining rapid simulation data of the linear array infrared detection signal of short-range ground targets through simulation prediction, establishing a simulation data set of the linear array infrared detection signal of short-range ground targets, and applying it to the linear array infrared detection system module optimization and control algorithm verification.

[0055] Beneficial effects:

[0056] 1. The present invention discloses a method for rapid simulation of a linear array infrared detection signal for a short-range ground target. By combining the infrared radiation model of the short-range ground target with the geometric measurement model of the linear array infrared detection system under the push-scan detection system, an external optical channel response model of the airborne linear array infrared detection system is established. By quantifying the pixel-level entrance pupil infrared radiation of the linear array infrared detection system, the numerical simulation accuracy of the target infrared radiation is improved.

[0057] 2. The present invention discloses a method for rapid simulation of linear array infrared detection signals for short-range ground targets. The method establishes an internal electrical signal response model of the linear array infrared detection system through a hybrid mode of the photoelectric effect model and the analog circuit, thereby realizing full-link physical response modeling of the linear array infrared detection system and improving the fidelity of the output signal.

[0058] 3. The present invention discloses a method for rapid simulation of short-range ground target linear array infrared detection signals. By integrating a cross-platform joint simulation application and driving the full-link physical response model through parallel ray tracing and multi-domain synchronous calculation methods, it can achieve rapid generation of linear array infrared detection system simulation signals, establish a short-range ground target linear array infrared detection signal simulation data set, and apply it to the linear array infrared detection system module optimization and control algorithm verification. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a flow chart of a method for rapid simulation of infrared detection signals of a short-range ground target linear array disclosed in the present invention;

[0060] Figure 2This is the ground target temperature distribution simulation result of step 1 in this embodiment.

[0061] Figure (a) is at 8:00, Figure (b) is at 10:00, and Figure (c) is at 12:00.

[0062] Figure (d) is at 14:00, Figure (e) is at 16:00, and Figure (f) is at 18:00;

[0063] Figure 3 The simulation results of solar radiation, sky radiation and ground radiation in step 1 of this embodiment are shown below:

[0064] Figure 4 This is a schematic diagram of a single-channel signal processing circuit in step three of this embodiment;

[0065] Figure 5 This is the Simulink-PSpice co-simulation model of step 4 in this embodiment;

[0066] Figure 6 This is the simulation visualization of the dynamic intersection scene in step 4 of this embodiment;

[0067] Figure 7 Schematic diagram of the dynamic rendezvous flight posture in step five of this embodiment;

[0068] Figure 8 This is a comparison chart of the simulation data and the measured data in step five of this embodiment;

[0069] Figure (a) shows the simulated data in test 1, and Figure (b) shows the measured data in test 1;

[0070] Figure (c) shows the simulated data in Test 2, and Figure (d) shows the measured data in Test 2;

[0071] Figure (e) is the simulation data in test 3, and Figure (f) is the measured data in test 3. DETAILED DESCRIPTION

[0072] The present invention will be described in detail below with reference to the accompanying drawings and embodiments. The technical problems solved by the technical solution of the present invention and the beneficial effects thereof are also described. It should be noted that the described embodiments are only intended to facilitate understanding of the present invention and do not serve to limit the present invention in any way.

[0073] The present invention discloses a method for rapid simulation of short-range ground target linear array infrared detection signals, which is applicable to ground target detection application scenarios of dynamic platforms without rolling flight attitude, such as cruise missiles and drones. This embodiment is described using cruise missiles as an example.

[0074] like Figure 1As shown, this embodiment discloses a method for rapid simulation of infrared detection signals of a short-range ground target linear array, and the specific implementation steps are as follows:

[0075] Step 1: Establish an infrared radiation model that covers the target's spontaneous radiation, solar radiation, sky radiation, and ground radiation, and calculate the total infrared radiation per unit area of ​​the target;

[0076] The target's own radiation is a function of temperature. Based on multi-physics field finite element analysis, boundary conditions are set to simulate the target and environmental temperature fields to obtain temperature distribution data. A three-dimensional model covering the terrain and target is constructed, taking into account the target's geographical location, posture, atmospheric state and time, and boundary conditions such as target material, surface physical parameters, and grid are set. The temperature distribution at different time nodes is simulated through transient analysis. Take the parameters of a certain measured experiment as an example: the simulated geographical location is 34°57'N, 110°09'E, the time zone is East 8, the time is July 12, the daily ambient temperature range is 24℃~34℃, 8:00~18:00 is selected as the observation time point, and the interval time is 2 hours. The temperature distribution simulation results are as follows: Figure 2 The temperature data is exported in a standard file format. At the same time, the ambient radiation is calculated based on the input parameters, and the obtained solar radiation, sky radiation and ground radiation change curves are shown in Figure 3 The total infrared radiation of a target unit surface element is the sum of its own radiation and the ambient radiation.

[0077] Step 2: Construct a geometric measurement model of the linear array infrared detection system. Combined with the infrared radiation model in step 1, the external optical channel response model of the linear array infrared detection system is obtained to quantify the pixel-level entrance pupil infrared radiation of the linear array infrared detection system.

[0078] The linear array infrared detection system is coaxially mounted on the dynamic platform, with an attack angle of 60°. Based on the parameters of the linear array infrared detection system, the normalized direction vector determined by each pixel and the detection field of view are determined. The target unit surface infrared radiation calculated in step 1 is combined to establish the external optical channel response model of the linear array infrared detection system. The pixel-level entrance pupil infrared radiation of the linear array infrared detection system is the sum of the radiation of all target surface elements within the detection field of view. The parameters of a typical linear array infrared detection system are shown in Table 1.

[0079] Table 1 Parameters of linear array infrared detection system

[0080]

[0081] Step 3: Establish an internal electrical signal response model of the linear array infrared detection system, which covers the receiving optical system, linear array infrared detectors, and signal processing circuits. Combined with the external optical channel response model in step 2, establish a full-link physical response model of the linear array infrared detection system.

[0082] The infrared radiation entering the pupil is converged onto the photosensitive surface of the detector through the receiving optical system. The radiation flux is calculated according to the parameters of the linear array infrared detection system in Table 1, and the photocurrent generated by the photoelectric effect is calculated. The photocurrent signal is converted into a voltage signal through a bias circuit. Within a certain range, the bias current will increase the voltage response rate and noise of the detector. For specific detectors, there is an optimal working bias current to achieve the best signal-to-noise ratio, which is determined based on hardware debugging. The converted voltage signal is amplified and filtered by the signal processing circuit. The circuit model is pre-built in PSpice. Its single-channel circuit schematic is shown in the figure. Figure 4 Combined with the external optical channel response model in step 2, a full-link physical response model of the linear array infrared detection system is established.

[0083] Step 4: Build a cross-platform co-simulation application to simulate dynamic intersection scenarios in a 3D virtual environment. Drive the full-link physical response model through parallel ray tracing and multi-domain synchronous computing methods to output simulation signals for the linear array infrared detection system.

[0084] Establish a Simulink-PSpice joint simulation application to build a 3D virtual environment covering terrain, lighting, targets, and linear array infrared detection systems. Configure parameters and organize input data through a graphical user interface. Simulate the dynamic intersection process in the 3D virtual environment, configure ray tracing parameters according to the geometric measurement model, and calculate the pixel-level infrared radiation value of the linear array infrared detection system in combination with the infrared radiation model. Establish a cross-domain synchronous simulation channel through the Simulink-PSpice interactive module, and output the time-series electrical signal data of the multi-channel of the linear array infrared detection system in real time. Use visualization components for signal tracking, such as Figure 6 shown.

[0085] Step 5: Establish evaluation indicators, verify the simulation data on the measured data, and obtain the simulation model.

[0086] Three experiments were conducted with different rendezvous postures. The simulation data were compared with the measured data channel by channel to evaluate the effectiveness of the simulation model. The simulation parameters were configured according to the actual measured conditions. Taking the parameters of a certain measured experiment as an example (the same as in step 1), the dynamic platform's flight speed was 10m / s, the flight time was 3s, and the flight posture was as follows: Figure 7 As shown in Figure 2. The comparison between simulation data and measured data is shown in Figure 2. Figure 8The performance evaluation is shown in Table 2. The output voltage amplitude range is 0–10 V. The RMSE of each overall signal during the test is no greater than 0.76, resulting in a simulated signal error of no more than 7.6%. The PCC of the overall signal is no less than 0.86, and the simulated signal has a strong positive correlation with the measured signal. The simulation times for the three tests were 8.53, 10.15, and 13.41 seconds, respectively, demonstrating the effectiveness of the simulation model in terms of accuracy and speed. Finally, the simulation model was packaged and exported for subsequent engineering applications.

[0087] Table 2 Results of evaluation indicators for each channel

[0088]

[0089] In summary, the present embodiment discloses a method for rapid simulation of infrared detection signals of short-range ground targets. It simulates the omnidirectional attitude dynamic rendezvous process for typical short-range ground target infrared detection application scenarios, and rapidly generates high-fidelity linear array infrared detection system simulation signal data, which can provide an effective data source for the application of short-range ground target infrared detection technology.

[0090] The above specific description further illustrates the purpose, technical solutions and beneficial effects of the invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for rapid simulation of infrared detection signals of a short-range ground target linear array, characterized by: The following steps are included: Step 1: Establish an infrared radiation model that covers the target's spontaneous radiation, solar radiation, sky radiation, and ground radiation, and calculate the total infrared radiation per unit area of ​​the target; Step 2: Construct a geometric measurement model of the linear array infrared detection system. Combined with the infrared radiation model in step 1, the external optical channel response model of the linear array infrared detection system is obtained to quantify the pixel-level entrance pupil infrared radiation of the linear array infrared detection system. Step 3: Establish an internal electrical signal response model of the linear array infrared detection system, which covers the receiving optical system, linear array infrared detectors, and signal processing circuits. Combined with the external optical channel response model in step 2, establish a full-link physical response model of the linear array infrared detection system. Step 4. Establish a cross-platform joint simulation application, simulate dynamic intersection scenarios based on a three-dimensional virtual environment, construct scene elements covering terrain, lighting, targets, and linear array infrared detection systems, drive the full-link physical response model through parallel ray tracing and multi-domain synchronous calculation methods, output the linear array infrared detection system simulation signal, and realize rapid simulation of the linear array infrared detection system output signal.

2. The method for rapid simulation of infrared detection signals of a short-range ground target linear array according to claim 1, characterized in that: The implementation method of step one is: The infrared radiation model is used to characterize the zero-line-of-sight infrared radiation of ground targets. The modeling of each radiation component is as follows: Step 1.1, spontaneous radiation; the target's own radiation is considered isotropic, and the equivalent blackbody radiation generated by any object with an absolute temperature above 0 degrees is calculated as follows: Where T is the temperature, λ1 and λ2 represent the infrared band range, c1 is the first radiation constant, and c2 is the second radiation constant; Step 1.2: Solar radiation; infrared radiation E reaching the upper boundary of the atmosphere sun The calculation is as follows: Where, E const represents the solar constant; σ is the Stefan-Boltzmann constant; T sum is the average temperature of the sun's equivalent black body; the irradiance E of the solar radiation per unit area d The calculation is as follows: AND d =And sun C s p m cosθ (3) Where C s represents the correction factor caused by the change in the distance between the sun and the earth, p m represents atmospheric attenuation, p is atmospheric transparency, m is atmospheric mass coefficient, and θ is the solar incidence angle; Step 1.3, sky radiation; Sky radiation is composed of solar scattered radiation and atmospheric radiation, which is affected by atmospheric conditions. The radiation generated by solar scattered radiation E s1 The calculation is as follows: Where, α s is the solar altitude angle; considering weather factors, a full-day atmospheric infrared radiation model related to clear sky radiation and cloud coefficient is established, and the calculation is as follows: Where C d represents cloud factor, RH represents relative humidity, E cs represents the radiation under clear sky conditions, ε cs Clear sky radiation emissivity; Considering the target surface element inclination angle β, sky radiation E s It is the superposition of two parts and is calculated as follows: Step 1.4: Ground radiation; ground radiation includes self-radiation and reflection of solar and sky radiation. The ground’s self-radiation E g0 By calculating the equivalent blackbody radiation, combining equations (3) and (6), we can get the ground radiation E g The calculation is as follows: Where, ε g is the ground emissivity, ρ g is the ground reflectivity, and ε is defined o is the target unit surface emissivity, ρ t is the reflectivity of the target unit surface element, the total radiation E of the target unit surface element is calculated as follows: And=ε o AND o +ρ t (AND d +E s +E g ) (8) Equations (1), (6), (7) and (8) constitute the infrared radiation model.

3. The method for rapid simulation of infrared detection signals of a short-range ground target linear array according to claim 2, characterized in that: In step 2, The linear array infrared detection system adopts a push-broom detection system. When the dynamic platform is flying, the linear array infrared detection system can only respond to infrared radiation within a certain field of view. The optical center of the linear array infrared detection system is defined as the coordinate origin, the direction of movement is the positive direction of the x-axis, and the positive direction of the z-axis is upward. The single-pixel detection field of view is equivalent to a rectangular area. The normalized direction vector from the origin to the center of the rectangle is calculated as follows: Where ψ represents the angle of attack, is the angle between the detection direction of the i-th pixel and the x-axis direction. The length l and width w of the single pixel detection field of view are calculated as follows: Where r represents the detection distance, s l Represents the length of a single pixel of the array detector, s w Represents the width of a single pixel, and F represents the focal length of the optical system; Equations (8) and (9) constitute the geometric measurement model; the radiation characteristics of the target surface conform to the Lambertian surface, and the infrared radiation E of a single pixel reaching the entrance pupil of the optical system is simplified. in The calculation is as follows: Where n represents the number of surface elements covered in the l×w detection field of view determined by a single pixel, τ atm Represents the atmospheric transmittance between the target and the infrared detection system, A opt and A i are the optical lens cross section and target surface area, ζ i1 and ζ i2 Represent the normal line of the optical lens cross section surface element and the target surface element normal and r i Angle; Equations (8) and (11) constitute the external optical channel response model of the linear array infrared detection system.

4. The method for rapid simulation of infrared detection signals of a short-range ground target linear array according to claim 3, characterized in that: In step three, The infrared radiation entering the pupil is focused onto the photosensitive surface of the detector through the receiving optical system. Its radiation flux is calculated from the optical system parameters as follows: Where, τ opt Represents the transmittance of the optical lens, A d is the area of ​​the detector's photosensitive surface, D is the diameter of the optical system's entrance pupil; the photocurrent generated by the photoelectric effect is calculated by the following formula: Where η represents quantum efficiency; q is the basic charge; h is Planck's constant; c is the speed of light; Equations (12) and (13) constitute the photoelectric effect model. The weak photocurrent generated by the incident pupil infrared radiation is converted into a voltage signal through a bias circuit. The working bias current that achieves the best signal-to-noise ratio is determined through calibration testing. The converted voltage signal is then amplified by a two-stage operational amplifier circuit in series, and a high-pass filter is configured to avoid amplifying noise signals. The output of the amplifier circuit is the internal electrical signal response of the linear array infrared detection system. The external optical channel response model and the internal electrical signal response model of the linear array infrared detection system are combined to form a full-link physical response model of the linear array infrared detection system.

5. The method for rapid simulation of infrared detection signals of a short-range ground target linear array according to claim 4, characterized in that: The implementation method of step 4 is: A Simulink-PSpice co-simulation application was constructed. According to the actual application scenario, scene elements covering terrain, lighting, targets and linear array infrared detection systems were established to simulate the dynamic intersection process in a three-dimensional virtual environment. Parallel ray tracing was used to deploy the geometric measurement model. The infrared radiation of the linear array infrared detection system at the entrance pupil was numerically calculated pixel by pixel according to the infrared radiation model to realize the drive of the external optical channel response model. PSpice was used to establish the simulation circuit of the linear array infrared detection system to drive the internal electrical signal response model. The co-simulation application was used to realize the mixed synchronous simulation of numerical calculation and analog circuit, and the simulation signal of the linear array infrared detection system was obtained, realizing the rapid simulation of the output signal of the linear array infrared detection system.

6. The method for rapid simulation of infrared detection signals of a short-range ground target linear array according to claim 5, characterized in that: It also includes step five, establishing evaluation indicators, verifying the simulation data based on the evaluation indicators and measured data, and screening out simulation models that meet the preset accuracy.

7. The method for rapid simulation of infrared detection signals of a short-range ground target linear array according to claim 6, characterized in that: The implementation method of step five is: The root mean square error (RMSE) and the Pearson correlation coefficient (PCC) are used to evaluate the similarity between the simulated output signal and the measured signal. Given two sets of time series signals, the root mean square error is calculated as follows: Where n represents the number of sequence sampling points; x i represents the simulation value; y i It represents the actual measured value. The RMSE value of the overall signal is valid if it is lower than the preset threshold within the range. The Pearson correlation coefficient is calculated as follows: Where μx and μy represent the average values ​​of the simulated value and the measured value, respectively. The PCC range is -1 to 1. Approaching 1 represents a linear positive correlation, and approaching -1 represents a linear negative correlation. The PCC value of the overall signal is valid if it is greater than the preset threshold. When both RMSE and PCC meet the validity requirements, the simulation model is exported and packaged for subsequent engineering applications.

8. A method for rapid simulation of infrared detection signals of a short-range ground target linear array according to claim 6 or 7, characterized in that: It also includes step six, using the simulation model in step five to simulate various dynamic intersection scenarios by setting different parameters, and obtaining rapid simulation data of the linear array infrared detection signal of short-range ground targets through simulation prediction, establishing a simulation data set of the linear array infrared detection signal of short-range ground targets, and applying it to the linear array infrared detection system module optimization and control algorithm verification.

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