A method and system for rapid evaluation of imaging performance of optoelectronic system based on precalculation

Abstract

The present application proposes a method and system for rapid evaluation of the imaging performance of an optoelectronic system based on pre-calculation. Belonging to the field of optoelectronic imaging performance evaluation, the method includes pre-establishing an optoelectronic system pre-calculation library, pre-calculating multiple data, storing the pre-calculation results for call, and continuously updating the pre-calculation results. When in use, the pre-calculation results are brought into the optoelectronic system imaging performance evaluation model, so as to quickly obtain and output the optoelectronic system imaging performance data. The system includes an optoelectronic system pre-calculation library module, a target radiation data inversion pre-calculation module, a system spatial transfer characteristic data pre-calculation module, a system noise characteristic data pre-calculation module, a system contrast threshold function pre-calculation module, a path curve fitting module, an update optoelectronic system pre-calculation library module, and an optoelectronic imaging performance data rapid output module; it reduces the performance evaluation time of the optoelectronic system and can effectively support the real-time deduction task of the optoelectronic system in complex scenarios.

Description

Technical Field

[0001] The present application relates to the technical field of photoelectric imaging performance evaluation, and in particular to a method for rapid evaluation of the imaging performance of a photoelectric system based on pre-calculation. Background Art

[0002] During scenario simulations, the environment and targets change rapidly. The speed of evaluating the imaging performance of optoelectronic systems is an important indicator of whether the simulation is real-time. Developing a rapid evaluation method for the imaging performance of optoelectronic systems is of great significance for integrated scenario simulations. Current methods for evaluating the imaging performance of optoelectronic systems are primarily based on the Johnson criterion or the TTP (targeting task performance) criterion proposed by the U.S. Army Night Vision Sensor Agency. This method involves a large amount of theoretical calculations, resulting in a long evaluation time and a high demand for computing resources. This makes it difficult to meet the rapid response requirements when real-time simulations are required. Summary of the Invention

[0003] The purpose of this application is to provide a method for quickly evaluating the imaging performance of an optoelectronic system based on pre-calculation, which can reduce the time required for evaluating the performance of the optoelectronic system.

[0004] This application is implemented as follows:

[0005] In a first aspect, the present application provides a method for rapid evaluation of the imaging performance of an optoelectronic system based on pre-calculation, comprising the following steps: pre-establishing an optoelectronic system pre-calculation library, including marking data that takes longer than a preset time during the simulation of an optoelectronic system performance evaluation model, and establishing a corresponding database table, wherein the database table includes a target radiation characteristic data table, a system spatial transfer characteristic data table, a system noise characteristic data table, and a contrast threshold function table;

[0006] Target radiation data inversion pre-calculation, including using existing photoelectric imaging system data to invert the target radiation distribution, combining radiation correlation factors to obtain target radiation characteristic data, and storing it in the corresponding position of the database table waiting for call;

[0007] Pre-calculation of system spatial transfer characteristic data, including obtaining the comprehensive modulation transfer function M(f x ,f y ), the modulation transfer function of the detector array D(f x ,f y ) and the signal processing circuit modulation transfer function S(f x ,f y ), cascade and multiply the three to obtain the system space transfer characteristic data, and store it in the corresponding position of the database table waiting for call;

[0008] Pre-calculation of system noise characteristic data, including establishing a three-dimensional noise component characterization model N based on the detector noise equivalent temperature difference measurement data and combined with the non-uniformity measurement data s ; Obtain system NETD, noise equivalent bandwidth, noise signal variance, and combine with the three-dimensional noise model N s Obtain system noise characteristic data and store it in the corresponding location of the database table waiting for call;

[0009] Pre-calculation of the system contrast threshold function, including using the TTP criterion to evaluate the imaging performance of the optoelectronic system to obtain the system contrast threshold function CTF sys The calculated value is stored in the corresponding position of the database table and waits for calling;

[0010] Path curve fitting, including polynomial fitting for different target ranges, obtaining fitting functions of atmospheric transmittance, atmospheric radiation and target distance, and fitting functions of optoelectronic system detection probability and target distance;

[0011] Update the optoelectronic system pre-calculation library, including continuously updating the target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function CTF in the optoelectronic system pre-calculation library through measured data and test data in different application scenarios sys The calculated value of

[0012] Rapid output of optoelectronic imaging performance data, including rapid retrieval of corresponding target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function (CTF) from the optoelectronic system pre-calculation database according to optoelectronic system parameters, operating range and application scenarios using database foreign key indexing. sys The calculated value is brought into the optoelectronic system imaging performance evaluation model to quickly obtain and output the optoelectronic system imaging performance data.

[0013] In a second aspect, the present application provides a system for rapid evaluation of the imaging performance of an optoelectronic system based on pre-calculation, comprising: an optoelectronic system pre-calculation library module for marking data that takes longer than a preset time during the simulation of an optoelectronic system performance evaluation model, and establishing a corresponding database table, wherein the database table includes a target radiation characteristic data table, a system spatial transfer characteristic data table, a system noise characteristic data table, and a contrast threshold function table;

[0014] The target radiation data inversion pre-calculation module is used to use the existing photoelectric imaging system data to invert the target radiation distribution, combine the radiation correlation factors to obtain the target radiation characteristic data, and store it in the corresponding position of the database table waiting for call;

[0015] The system spatial transfer characteristic data pre-calculation module is used to obtain the comprehensive modulation transfer function M(f x ,fy ), the modulation transfer function of the detector array D(f x ,f y ) and the signal processing circuit modulation transfer function S(f x ,f y ), cascade and multiply the three to obtain the system space transfer characteristic data, and store it in the corresponding position of the database table waiting for call;

[0016] The system noise characteristic data pre-calculation module is used to establish a three-dimensional noise component characterization model N based on the detector noise equivalent temperature difference measurement data and the non-uniformity measurement data. s ; Obtain system NETD, noise equivalent bandwidth, noise signal variance, and combine with the three-dimensional noise model N s Obtain system noise characteristic data and store it in the corresponding location of the database table waiting for call;

[0017] System contrast threshold function pre-calculation module, used to evaluate the imaging performance of the optoelectronic system using the TTP criterion to obtain the system contrast threshold function CTF sys The calculated value is stored in the corresponding position of the database table and waits for calling;

[0018] The path curve fitting module is used to use polynomial fitting for different target ranges to obtain the fitting function of atmospheric transmittance, atmospheric radiation and target distance, and the fitting function of optoelectronic system detection probability and target distance;

[0019] Update the optoelectronic system pre-calculation library module, which is used to continuously update the target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function CTF in the optoelectronic system pre-calculation library through measured data and test data in different application scenarios sys The calculated value of

[0020] The optoelectronic imaging performance data fast output module is used to quickly retrieve the corresponding target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function (CTF) from the optoelectronic system pre-calculation library according to the optoelectronic system parameters, operating range and application scenario by using the database foreign key index. sys The calculated value is brought into the optoelectronic system imaging performance evaluation model to quickly obtain and output the optoelectronic system imaging performance data.

[0021] In a third aspect, the present application provides an electronic device, comprising:

[0022] a memory for storing one or more programs;

[0023] processor;

[0024] When one or more programs are executed by a processor, the above method is implemented.

[0025] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned method when executed by a processor.

[0026] Compared with the prior art, this application has at least the following advantages or beneficial effects:

[0027] By pre-establishing a pre-calculation library for the optoelectronic system, we record the time-consuming data during the simulation of the optoelectronic system performance evaluation model and establish a corresponding database table. We continuously update the target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function (CTF) in the pre-calculation library for the optoelectronic system through measured data and experimental data in different application scenarios. sys During use, the system quickly retrieves the corresponding target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data, and the calculated value of the contrast threshold function CTFsys from the pre-calculated optoelectronic system database using a database foreign key index based on the optoelectronic system parameters, operating range, and application scenario. These data are then fed into the optoelectronic system imaging performance evaluation model, allowing for rapid output of the optoelectronic system imaging performance data. This significantly improves the speed of the optoelectronic system imaging performance evaluation model, achieving millimeter-level response and effectively supporting real-time simulation tasks of optoelectronic systems in complex scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 This is a flowchart of an embodiment of a method for rapid evaluation of imaging performance of an optoelectronic system based on pre-calculation in this application;

[0030] Figure 2 This is a structural block diagram of an embodiment of a system for rapid evaluation of imaging performance of an optoelectronic system based on pre-calculation according to the present application;

[0031] Figure 3 This is a structural block diagram of an embodiment of an electronic device of the present application.

[0032] Icons: 101, optoelectronic system pre-calculation library module; 102, target radiation data inversion pre-calculation module; 103, system spatial transfer characteristic data pre-calculation module; 104, system noise characteristic data pre-calculation module; 105, system contrast threshold function pre-calculation module; 106, path curve fitting module; 107, update optoelectronic system pre-calculation library module; 108, optoelectronic imaging performance data rapid output module; 201, processor; 202, memory; 203, communication interface; DETAILED DESCRIPTION

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0034] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features thereof may be combined with each other.

[0035] Example

[0036] The embodiment of the present application provides a method for quickly evaluating the imaging performance of an optoelectronic system based on pre-calculation, which can reduce the time required for evaluating the performance of the optoelectronic system.

[0037] Please refer to Figure 1 A method for rapidly evaluating the imaging performance of an optoelectronic system based on precalculation comprises the following steps:

[0038] S101: Pre-establishing an optoelectronic system pre-calculation library, including marking data that takes longer than a preset time during the optoelectronic system performance evaluation model simulation process, and establishing corresponding database tables, wherein the database tables include a target radiation characteristic data table, a system spatial transfer characteristic data table, a system noise characteristic data table, and a contrast threshold function table;

[0039] In this step, the optoelectronic system pre-calculation library uses a SQLite database. Data that takes a long time to calculate, including target radiation characteristics, system spatial transfer characteristics, system noise characteristics, and the calculated value of the contrast threshold function, are marked and corresponding database tables are created for them. This allows complex data that would otherwise require real-time calculation to be stored in the database during the pre-calculation phase, allowing for quick access when needed, thus saving computation time.

[0040] S102: Target radiation data inversion pre-calculation, including using existing optoelectronic imaging system data to invert the target radiation distribution, combining radiation correlation factors to obtain target radiation characteristic data, and storing it in the corresponding location of the database table for waiting for retrieval;

[0041] In this step, the radiation brightness received by the system is measured using the existing photoelectric system and expressed as:

[0042] L opt (λ)=L t (T,λ)τ atm (λ)+L atm (λ);

[0043] Where, L t (T,λ) represents the radiant brightness generated by the target surface in the observation direction, τ atm (λ) represents the transmittance of the atmosphere between the target surface and the imaging system, L atm (λ) represents the radiation brightness of the atmosphere between the target surface and the imaging system. At different wavelengths, the radiation of the target can be expressed as:

[0044]

[0045] Where ε(λ) represents the surface emissivity of scene elements; M bb (λ, T) represents the blackbody radiation emittance; C1 represents the first radiation constant, C1=3.74×10 8 (W·μm 4 / m 2 ); C2 represents the second radiation constant, C2 = 1.44 × 10 4(μm·K); where ε(λ) is obtained through experimental testing and historical data. The target radiation distribution is then inverted using radiometric calibration of measured data and atmospheric effect calculations. The specific steps for obtaining target radiation characteristic data by combining radiation-related factors include: based on the target radiation distribution, comprehensively considering the impact of environmental radiation on the radiation characteristics of the target and its background surfaces, and combining the material properties of the target and its background, as well as local meteorological conditions, to obtain target radiation characteristic data. Environmental radiation includes direct solar radiation and atmospheric radiation. Specifically, radiometric calibration: First, radiometric calibration is performed on the imaging data of the target and its background using an existing electro-optical imaging system. This involves determining the correspondence between pixel values ​​and radiation intensities in the imaging data. Detector and atmospheric effect inversion: Next, the impact of detector effects (such as detector sensitivity and noise) and atmospheric effects (such as atmospheric absorption and scattering) on ​​the imaging data is considered, and inversion processing is performed to more accurately interpret the radiation distribution of the target and its background. Environmental radiation impact analysis: Finally, the impact of environmental radiation, including direct solar radiation and atmospheric radiation, on the radiation characteristics of the target and its background surfaces is comprehensively considered. These environmental radiation factors affect the radiation distribution of the target and its background, thereby affecting the imaging performance of the optoelectronic system. Calculation of target surface radiation characteristics: Finally, the target radiation characteristics are obtained by combining the material properties of the target and its background (such as reflectivity, emissivity, etc.) and local meteorological conditions (such as temperature, humidity, wind speed, etc.).

[0046] S103: Pre-calculating the system spatial transfer characteristic data, including obtaining the optical system's comprehensive modulation transfer function M(fx, fy), the detector array modulation transfer function D(fx, fy), and the signal processing circuit modulation transfer function S(fx, fy), cascading and multiplying the three to obtain the system spatial transfer characteristic data, and storing it in the corresponding location of the database table for waiting for retrieval;

[0047] This step pre-calculates the system's spatial transfer characteristics, focusing on estimating the overall performance of the optoelectronic system under specific operating conditions. Using ray tracing theoretical models, the optical system's comprehensive modulation transfer function (M(fx,fy)) can be calculated. This function describes the system's ability to modulate images at different spatial frequencies (fx,fy), specifically, how the system delivers image contrast. This function replaces models that consider optical component aberrations, diffraction, and defocus characteristics separately. It provides a more comprehensive and accurate description of system performance. Combined with the circuit filter function H(fx,fy) provided by the circuit design software, this function describes the impact of the signal processing circuitry on the image signal. By combining H(fx,fy) with other system characteristics, the modulation transfer function (S(fx,fy)) of the signal processing circuitry is constructed. This function describes how the signal processing circuitry further impacts image contrast transfer. The modulation transfer function (D(fx,fy)) of the detector array is then obtained. The overall spatial transfer characteristics of the system are calculated by cascading and multiplying the optical system's combined modulation transfer function (M(fx,fy),) the detector array's modulation transfer function (D(fx,fy)) (which describes how the detector array affects image contrast), and the signal processing circuit's modulation transfer function (S(fx,fy). These three functions, M(fx,fy), D(fx,fy), and S(fx,fy), can be calculated based on the specific parameters of the optoelectronic system (such as the parameters of the optical components, the characteristics of the detector array, and the design of the signal processing circuitry) as well as environmental parameters (such as temperature, humidity, and lighting conditions).

[0048] S104: Pre-calculation of system noise characteristic data, including establishing a three-dimensional noise component characterization model Ns based on the detector noise equivalent temperature difference measurement data and combining the non-uniformity measurement data; obtaining the system NETD, noise equivalent bandwidth, noise signal variance, and combining the three-dimensional noise model N s Obtain system noise characteristic data and store it in the corresponding location of the database table waiting for call;

[0049] For ease of understanding, in this step, the system's NETD (Noise Equivalent Temperature Difference) is an important parameter for measuring thermal imaging system performance. It represents the minimum temperature difference the system can detect. It reflects the system's sensitivity to noise; lower NETD values ​​generally indicate better system performance. The noise equivalent bandwidth (NEB) is the effective frequency range over which a system is sensitive to noise during signal processing. It determines the frequency range of noise signals to which the system can respond and is crucial for understanding the system's noise characteristics. The noise signal variance is a statistical measure of the fluctuation of the noise signal. In signal processing, understanding the noise variance helps assess the impact of noise on signal quality. The three-dimensional noise model (Ns) is a model that considers the distribution characteristics of noise in different dimensions (such as time, space, and frequency). Ns represents the noise characteristics within this model, which may be noise intensity, distribution, or other related parameters. Based on known system parameters (such as NETD, NB, and noise signal variance) and the noise model (Ns), the overall noise characteristics of the system can be predicted or calculated. This is crucial for system design, optimization, and performance evaluation. When calculating system noise characteristics, the noise characteristics derived from NETD, noise equivalent bandwidth, and noise signal variance are combined or superimposed with the predictions from the three-dimensional noise model Ns. This allows for a more comprehensive description of the system's noise characteristics by comprehensively considering the system's noise performance in different dimensions.

[0050] S105: Pre-calculating the system contrast threshold function, including using the TTP criterion to evaluate the imaging performance of the optoelectronic system to obtain the calculated value of the system contrast threshold function CTFsys, and storing it in the corresponding position of the database table for waiting for call;

[0051] In this step, the TTP criterion is a standard used to evaluate the performance of the target task. The TTP criterion is based on factors such as the focal length of the optical system, the center spacing of the detector pixels, the observation distance and the observation angle. It evaluates the image quality interpretation scale by calculating the ground sampling distance, the target background contrast function and the human eye contrast threshold function. This method efficiently combines subjective evaluation with objective evaluation to build a more reliable and realistic evaluation system. The specific steps of pre-calculating the system contrast threshold function include: let the calculation formula of the contrast threshold function of the optoelectronic system be:

[0052]

[0053] Where MTF(ξ) is the total MTF of the optoelectronic system, CTFeye(ξ) is the contrast threshold function of the human eye, which is only related to the system parameter values, and L is the display brightness in cd / m 2α is the correction factor for noise to brightness, which is set to 169.6. σ is the noise power of the imaging system. It should be noted that steps S102-S105 are not sequential; that is, the target radiation data inversion precalculation, system spatial transfer characteristic data precalculation, system noise characteristic data precalculation, and system contrast threshold function precalculation can be performed simultaneously. Alternatively, the system contrast threshold function precalculation can be performed first and then the target radiation data inversion precalculation.

[0054] S106: Path curve fitting, including using polynomial fitting for different target ranges to obtain fitting functions of atmospheric transmittance, atmospheric radiation, and target distance, and fitting functions of optoelectronic system detection probability and target distance;

[0055] In this step, polynomial fitting is used in path curve fitting. Polynomial fitting is a commonly used mathematical tool used to approximate the relationship between data points through polynomial functions. In this embodiment, polynomial fitting is used to describe the variation patterns of various parameters at different target ranges. The range refers to the distance from the target to the photoelectric system and the distance that light propagates in the atmosphere. Through polynomial fitting, a functional relationship can be obtained that describes the variation of atmospheric transmittance and atmospheric radiation with target distance. These functional relationships represent the degree of influence of the atmosphere on light propagation and the variation of atmospheric radiation at different distances. Similarly, through polynomial fitting, a functional relationship that describes the variation of the detection probability of the photoelectric system with target distance can also be obtained. This functional relationship is of great significance for evaluating the detection performance of the photoelectric system at different distances.

[0056] S107: Updating the optoelectronic system pre-calculation library, including continuously updating the target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data, and the calculated value of the contrast threshold function CTFsys in the optoelectronic system pre-calculation library through measured data and test data in different application scenarios;

[0057] In this step, various data sets of typical optoelectronic systems in typical application scenarios can be traversed. This data includes environmental data (such as lighting conditions and atmospheric conditions), target attribute data (such as target brightness and contrast), and atmospheric data (such as atmospheric transmittance and atmospheric radiation). By traversing and analyzing this data, the target radiation data, system spatial transfer characteristic data, system noise characteristic data, and pre-calculated values ​​of the system contrast threshold function can be obtained for the optoelectronic system in different environmental application scenarios.

[0058] S108: Rapid output of optoelectronic imaging performance data, including rapidly retrieving corresponding target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data, and calculated value of contrast threshold function CTFsys from the optoelectronic system pre-calculation library according to optoelectronic system parameters, effective range, and application scenarios using database foreign key indexes, and bringing these data into the optoelectronic system imaging performance evaluation model to rapidly obtain and output optoelectronic system imaging performance data.

[0059] In this step, the required data is determined based on the specific parameters of the optoelectronic system (such as lens focal length and aperture size), the application scenario (such as night reconnaissance and daytime surveillance), and the target's operating range (i.e., the distance between the target and the optoelectronic system). To efficiently obtain the required data, this implementation utilizes a database foreign key index. A foreign key index is a mechanism in a database that allows for the rapid location of other records associated with a specific record. In this scenario, it is used to quickly locate data records that match the given optoelectronic system parameters, application scenario, and operating range. Target radiation data, system spatial transfer characteristics data, system noise characteristics data, and pre-calculated values ​​of the system's contrast threshold function are retrieved from a pre-calculated database. These data represent the target's radiant energy, the optoelectronic system's spatial transfer characteristics, the system's noise characteristics, and the pre-calculated values ​​of the system's contrast threshold function, respectively. These data are key inputs for evaluating optoelectronic system performance. By inputting this data into the optoelectronic system imaging performance evaluation model and running the evaluation model, the optoelectronic system's performance results can be rapidly derived. These results include key performance indicators such as the system's resolution, signal-to-noise ratio, and contrast sensitivity.

[0060] Please refer to Figure 2 , the present application also provides a system for rapid evaluation of the imaging performance of an optoelectronic system based on pre-calculation, comprising: an optoelectronic system pre-calculation library module 101, for marking data that takes longer than a preset time during the simulation process of an optoelectronic system performance evaluation model, and establishing a corresponding database table, wherein the database table includes a target radiation characteristic data table, a system spatial transfer characteristic data table, a system noise characteristic data table, and a contrast threshold function table;

[0061] The target radiation data inversion pre-calculation module 102 is used to use the existing photoelectric imaging system data to invert the target radiation distribution, combine the radiation correlation factors to obtain the target radiation characteristic data, and store it in the corresponding position of the database table for waiting for call;

[0062] The system spatial transfer characteristic data pre-calculation module 103 is used to obtain the comprehensive modulation transfer function M(f x ,f y ), the modulation transfer function of the detector array D(f x ,f y) and the signal processing circuit modulation transfer function S(f x ,f y ), cascade and multiply the three to obtain the system space transfer characteristic data, and store it in the corresponding position of the database table waiting for call;

[0063] The system noise characteristic data pre-calculation module 104 is used to establish a three-dimensional noise component characterization model N based on the detector noise equivalent temperature difference measurement data and the non-uniformity measurement data. s ; Obtain system NETD, noise equivalent bandwidth, noise signal variance, and combine with the three-dimensional noise model N s Obtain system noise characteristic data and store it in the corresponding location of the database table waiting for call;

[0064] The system contrast threshold function pre-calculation module 105 is used to evaluate the imaging performance of the optoelectronic system using the TTP criterion to obtain the system contrast threshold function CTF. sys The calculated value is stored in the corresponding position of the database table and waits for calling;

[0065] The path curve fitting module 106 is used to use polynomial fitting for different target ranges to obtain fitting functions of atmospheric transmittance, atmospheric radiation and target distance, and fitting functions of optoelectronic system detection probability and target distance;

[0066] Update the optoelectronic system pre-calculation library module 107, which is used to continuously update the target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function CTF in the optoelectronic system pre-calculation library through measured data and test data in different application scenarios sys The calculated value of

[0067] The optoelectronic imaging performance data fast output module 108 is used to quickly retrieve the corresponding target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function (CTF) from the optoelectronic system pre-calculation database according to the optoelectronic system parameters, operating range and application scenario by using the database foreign key index. sys The calculated value is brought into the optoelectronic system imaging performance evaluation model to quickly obtain and output the optoelectronic system imaging performance data.

[0068] In summary, this method overcomes the problems of complex and time-consuming calculations in traditional optoelectronic system imaging performance evaluation, and greatly improves the real-time application of the model.

[0069] For the specific implementation of the system for rapid evaluation of the imaging performance of an optoelectronic system based on pre-calculation, please refer to the embodiment of the method for rapid evaluation of the imaging performance of an optoelectronic system based on pre-calculation, which will not be described in detail here.

[0070] Please refer to Figure 3 The present application also provides an electronic device, including: a memory 202 for storing one or more programs; a processor 201; the processor 201 and the memory 202 transmit data to each other through a communication interface, and when one or more programs are executed by the processor 201, the above-mentioned method for quickly evaluating the imaging performance of an optoelectronic system based on pre-calculation is implemented.

[0071] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for rapidly evaluating the imaging performance of an optoelectronic system based on precalculation.

[0072] It will be apparent to those skilled in the art that the present application is not limited to the details of the exemplary embodiments described above and that the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the present application is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A method for rapid evaluation of imaging performance of an optoelectronic system based on precalculation, characterized in that: The following steps are involved: Pre-establishing an optoelectronic system pre-calculation library, including marking data that takes longer than a preset time during the simulation of the optoelectronic system performance evaluation model, and establishing corresponding database tables, wherein the database tables include a target radiation characteristic data table, a system spatial transfer characteristic data table, a system noise characteristic data table, and a contrast threshold function table; Target radiation data inversion pre-calculation, including using existing photoelectric imaging system data to invert the target radiation distribution, combining radiation correlation factors to obtain target radiation characteristic data, and storing it in the corresponding position of the database table waiting for call; Pre-calculation of system spatial transfer characteristic data, including obtaining the comprehensive modulation transfer function M(f x ,f y ), the modulation transfer function of the detector array D(f x ,f y ) and the signal processing circuit modulation transfer function S(f x ,f y ), cascade and multiply the three to obtain the system space transfer characteristic data, and store it in the corresponding position of the database table waiting for call; Pre-calculation of system noise characteristic data, including establishing a three-dimensional noise component characterization model N based on the detector noise equivalent temperature difference measurement data and combined with the non-uniformity measurement data s ; Obtain system NETD, noise equivalent bandwidth, noise signal variance, and combine with the three-dimensional noise model N s Obtain system noise characteristic data and store it in the corresponding location of the database table waiting for call; Pre-calculation of the system contrast threshold function, including using the TTP criterion to evaluate the imaging performance of the optoelectronic system to obtain the system contrast threshold function CTF sys The calculated value is stored in the corresponding position of the database table and waits for calling; Path curve fitting, including polynomial fitting for different target ranges, obtaining fitting functions of atmospheric transmittance, atmospheric radiation and target distance, and fitting functions of optoelectronic system detection probability and target distance; Update the optoelectronic system pre-calculation library, including continuously updating the target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function CTF in the optoelectronic system pre-calculation library through measured data and test data in different application scenarios sys The calculated value of Rapid output of optoelectronic imaging performance data, including rapid retrieval of corresponding target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function (CTF) from the optoelectronic system pre-calculation database according to optoelectronic system parameters, operating range and application scenarios using database foreign key indexing. sys The calculated value is brought into the optoelectronic system imaging performance evaluation model to quickly obtain and output the optoelectronic system imaging performance data.

2. The method for rapid evaluation of imaging performance of an optoelectronic system based on precalculation according to claim 1, characterized in that: The specific steps of pre-establishing the optoelectronic system pre-calculation library include: The optoelectronic system pre-calculation library is designed using the SQLite database.

3. The method for rapid evaluation of imaging performance of an optoelectronic system based on precalculation according to claim 1, characterized in that: The specific steps of using the existing optoelectronic imaging system data to invert the target radiation distribution include: The radiation brightness received by the system measured using the existing photoelectric system is expressed as: L opt (λ)=L t (T,λ)τ atm (λ)+L atm (l) Where, L t (T,λ) represents the radiant brightness generated by the target surface in the observation direction, τ atm (λ) represents the transmittance of the atmosphere between the target surface and the imaging system, L atm (λ) represents the radiation brightness of the atmosphere between the target surface and the imaging system. At different wavelengths, the radiation of the target can be expressed as: Where ε(λ) represents the surface emissivity of scene elements; M bb (λ, T) represents the blackbody radiation emittance; C1 represents the first radiation constant, C1=3.74×10 8 (W·μm 4 / m 2 ); C2 represents the second radiation constant, C2 = 1.44 × 10 4 (μm·K); where ε(λ) is obtained through experimental tests and historical data. The target radiation distribution is obtained by inverting the calculated target radiation through radiation calibration of measured data and calculation of atmospheric effects.

4. The method for rapid evaluation of imaging performance of an optoelectronic system based on precalculation according to claim 3, characterized in that: The specific steps of obtaining target radiation characteristic data by combining radiation-related factors include: Based on the target radiation distribution, the impact of environmental radiation on the radiation characteristics of the target and its background surface is comprehensively considered, and the target radiation characteristic data is obtained in combination with the material properties of the target and its background and local meteorological conditions; wherein, the environmental radiation includes direct solar radiation and atmospheric radiation.

5. The method for rapid evaluation of imaging performance of an optoelectronic system based on precalculation according to claim 1, characterized in that: The specific steps of precalculating the system spatial transfer characteristic data include: According to the changes in optical component parameters under working conditions, the comprehensive modulation transfer function M(f x ,f y ) to replace the aberration, diffraction and defocus characteristic models of the optical components; obtain the modulation transfer function D(f x ,f y ); and according to the circuit filter function H(f x ,f y ) Establish the signal processing circuit modulation transfer function S(f x ,f y ).

6. The method for rapid evaluation of imaging performance of an optoelectronic system based on precalculation according to claim 3, characterized in that: The specific steps of precalculating the system contrast threshold function include: The contrast threshold function calculation formula of the photoelectric system is: Where MTF(ξ) is the total MTF of the optoelectronic system, CTFeye(ξ) is the contrast threshold function of the human eye, which is only related to the system parameter values, and L is the display brightness in cd / m 2 ,α is the correction factor of noise to brightness, and 169.6 is taken, σ is the noise power of the imaging system.

7. The method for rapid evaluation of imaging performance of an optoelectronic system based on precalculation according to claim 6, characterized in that: The specific steps of updating the optoelectronic system pre-calculation library include: Traverse the environmental data, target attribute data, and atmospheric data of typical optoelectronic systems in typical application scenarios, and obtain the target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data, and contrast threshold function (CTF) of optoelectronic systems in different application scenarios. sys The calculated value is updated in the optoelectronic system pre-calculation library.

8. A system for rapid evaluation of imaging performance of an optoelectronic system based on pre-calculation, characterized in that: include: The optoelectronic system pre-calculation library module is used to mark data that takes longer than a preset time during the simulation of the optoelectronic system performance evaluation model and establish a corresponding database table, wherein the database table includes a target radiation characteristic data table, a system spatial transfer characteristic data table, a system noise characteristic data table, and a contrast threshold function table; The target radiation data inversion pre-calculation module is used to use the existing photoelectric imaging system data to invert the target radiation distribution, combine the radiation correlation factors to obtain the target radiation characteristic data, and store it in the corresponding position of the database table waiting for call; The system spatial transfer characteristic data pre-calculation module is used to obtain the comprehensive modulation transfer function M(f x ,f y ), the modulation transfer function of the detector array D(f x ,f y ) and the signal processing circuit modulation transfer function S(f x ,f y ), cascade and multiply the three to obtain the system space transfer characteristic data, and store it in the corresponding position of the database table waiting for call; The system noise characteristic data pre-calculation module is used to establish a three-dimensional noise component characterization model N based on the detector noise equivalent temperature difference measurement data and the non-uniformity measurement data. s ; Obtain system NETD, noise equivalent bandwidth, noise signal variance, and combine with the three-dimensional noise model N s Obtain system noise characteristic data and store it in the corresponding location of the database table waiting for call; System contrast threshold function pre-calculation module, used to evaluate the imaging performance of the optoelectronic system using the TTP criterion to obtain the system contrast threshold function CTF sys The calculated value is stored in the corresponding position of the database table and waits for calling; The path curve fitting module is used to use polynomial fitting for different target ranges to obtain the fitting function of atmospheric transmittance, atmospheric radiation and target distance, and the fitting function of optoelectronic system detection probability and target distance; Update the optoelectronic system pre-calculation library module, which is used to continuously update the target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function CTF in the optoelectronic system pre-calculation library through measured data and test data in different application scenarios sys The calculated value of The optoelectronic imaging performance data fast output module is used to quickly retrieve the corresponding target radiation characteristic data, system spatial transfer characteristic data, system noise characteristic data and contrast threshold function (CTF) from the optoelectronic system pre-calculation library according to the optoelectronic system parameters, operating range and application scenario by using the database foreign key index. sys The calculated value is brought into the optoelectronic system imaging performance evaluation model to quickly obtain and output the optoelectronic system imaging performance data.

9. An electronic device, characterized in that: include: a memory for storing one or more programs; processor; When the one or more programs are executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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