Method and device for generating atmospheric transmission data in predetermined format of air moving target

Abstract

The invention relates to a method and device for generating atmospheric transmission data in a predetermined format with target height change, and the method comprises the steps: determining first atmospheric transmission characteristic data calculated by a sensor under the observation geometric parameters of first atmospheric transmission; inputting a distance geometric parameter in the observation geometric parameters of the first atmospheric transmission into the transformation model to obtain an observation geometric parameter of second atmospheric transmission; and generating a first three-dimensional atmosphere transmission data three-dimensional distribution diagram in a predetermined format according to observation geometric parameters of second atmosphere transmission and the first atmosphere transmission characteristic data. According to the technical scheme, due to the fact that the transformation model is adopted, nonlinear transformation of pre-sensitization and post-saturation can be carried out on the first target altitude and the first detection distance, and compatibility of atmospheric transmission data formats before and after target height change is achieved.

Description

Technical Field

[0001] This invention relates to the field of atmospheric transport characteristic data technology, and more particularly to a method and apparatus for generating atmospheric transport data of a predetermined format for aerial moving targets. Background Technology

[0002] In related technologies, the observation geometry parameters of atmospheric transmission have the following drawbacks: when the observation angle is close to horizontal, although the altitude of the target changes very little, the corresponding detection distance will also change greatly, and the atmospheric transmission characteristic data will show huge differences. There will be obvious unreasonable atmospheric coupling effects in the simulation image. The drastic change in detection distance will cause the atmospheric transmission characteristic data before and after the change in target altitude to have format incompatibility problems, which will affect the subsequent integration and analysis of data. Summary of the Invention

[0003] The technical problem to be solved by this invention is the incompatibility of atmospheric transmission characteristic data formats between two consecutive atmospheric transmission data due to changes in target altitude. In view of the defects in the prior art, this invention provides a method and apparatus for generating atmospheric transmission data of a predetermined format for aerial moving targets.

[0004] To address the aforementioned technical problems, this invention provides a method for generating atmospheric transmission data in a predetermined format for aerial moving targets, comprising: Determine the first atmospheric transport characteristic data calculated by the sensor under the observed geometric parameters of the first atmospheric transport; The distance geometric parameters from the first atmospheric transmission observation geometric parameters are input into the transformation model to obtain the second atmospheric transmission observation geometric parameters. The transformation model is used to achieve a nonlinear transformation of pre-sensitization followed by saturation. Based on the observed geometric parameters of the second atmospheric transport and the first atmospheric transport characteristic data, a first three-dimensional atmospheric transport data three-dimensional distribution map in a predetermined format is generated. The observation geometric parameters of the first atmospheric transmission include: the altitude of the first target, the observation zenith angle, and the first detection distance; The distance geometric parameters in the first atmospheric transmission observation geometric parameters include: the altitude of the first target and the first detection distance; The observation geometric parameters of the second atmospheric transmission include: the altitude of the second target, the observation zenith angle, and the second detection distance; Wherein, the second target altitude is obtained by transforming the first target altitude using the transformation model; The second detection distance is obtained by transforming the first detection distance using the transformation model; The dimensions of the first three-dimensional atmospheric transport data distribution map in the predetermined format include at least the altitude of the second target and the second detection distance.

[0005] Secondly, this application also proposes an apparatus for generating atmospheric transmission data in a predetermined format with varying altitudes, comprising: The first determining module is used to determine the first atmospheric transmission characteristic data calculated by the sensor under the observation geometric parameters of the first atmospheric transmission; The conversion module is used to input the distance geometric parameters from the observation geometric parameters of the first atmospheric transmission into the transformation model to obtain the observation geometric parameters of the second atmospheric transmission. The transformation model is used to achieve a nonlinear transformation of pre-sensitization followed by saturation. The image module is used to generate a first three-dimensional atmospheric transport data three-dimensional distribution map in a predetermined format based on the observed geometric parameters of the second atmospheric transport and the first atmospheric transport characteristic data. The observation geometric parameters of the first atmospheric transmission include: the altitude of the first target, the observation zenith angle, and the first detection distance; The distance geometric parameters in the first atmospheric transmission observation geometric parameters include: the altitude of the first target and the first detection distance; The observation geometric parameters of the second atmospheric transmission include: the altitude of the second target, the observation zenith angle, and the second detection distance; Wherein, the second target altitude is obtained by transforming the first target altitude using the transformation model; The second detection distance is obtained by transforming the first detection distance using the transformation model; The dimensions of the first three-dimensional atmospheric transport data distribution map in the predetermined format include at least the altitude of the second target and the second detection distance.

[0006] Thirdly, this application also proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements a method for generating atmospheric transport data in a predetermined format with varying altitudes as described in any of the preceding claims.

[0007] Fourthly, this application also proposes a computer-readable storage medium storing computer program instructions that, when executed by a processor, implement the steps of the atmospheric transport data generation method of a predetermined format for altitude variation as described in any of the preceding claims.

[0008] Implementing this invention has the following beneficial effects: The technical solution of this application, by employing a transformation model, can perform a nonlinear transformation of the first target altitude and the first detection distance, which is pre-sensitized and then saturated, to generate atmospheric transport data in a predetermined format. The atmospheric transport data in the predetermined format is a three-dimensional distribution map, and the dimensions include at least the transformed target altitude and detection distance. This data format is conducive to achieving compatibility of atmospheric transport characteristic data formats before and after the target altitude change. Attached Figure Description

[0009] Figure 1 This is a flowchart of a method for generating atmospheric transmission data in a predetermined format based on target altitude changes, provided by an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating the change in detection distance before and after a change in target height, provided by an embodiment of the present invention. Figure 3 This is a flowchart of a method for generating atmospheric transport characteristic data in a predetermined format according to an embodiment of the present invention; Figure 4 This is a schematic diagram of an atmospheric transmission data generation device with a predetermined format for target altitude variation provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0010] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0011] Current infrared scene simulation systems have high real-time requirements for infrared image simulation capabilities (no less than 50Hz), and typically employ GPU-based graphics rendering engines (OSG, UE, etc.) to achieve high-performance infrared image simulation. Due to limitations in data transfer bandwidth between the CPU and GPU, texture mapping techniques are often used to transfer datasets involved in the simulation process.

[0012] In infrared scene simulation systems, atmospheric transport characteristics are a key factor to consider. Since atmospheric transport characteristics require significant computation time, they need to be pre-calculated, and the results input into the shader for infrared characteristic calculations. For each vertex in the scene, the atmospheric transport characteristic parameters (path radiation, transmittance) differ depending on the light transmission path. Therefore, infrared scene simulation requires real-time acquisition of atmospheric transport characteristic data under different conditions. To ensure data transmission and extraction performance, atmospheric transport characteristic parameters under different conditions are often transferred from CPU memory to the GPU cache in the form of a 2D texture.

[0013] Currently, atmospheric transport texture data is mainly organized around the sensor, storing atmospheric transport parameters in two dimensions: different sensing pitch angles and sensor height. While this can meet the real-time extraction requirements of atmospheric transport parameters in infrared scene simulation, it also has many limitations, mainly in two aspects: 1) When the observation angle is close to horizontal, even a small change in sensor height will result in a large change in the corresponding detection distance, leading to significant differences in atmospheric transport characteristics and obvious unreasonable atmospheric coupling effects in the simulation image; 2) The current atmospheric transport texture uses a linear storage method for sensor height. If the range of sensor heights stored is too large, it cannot meet the accuracy requirements of small-scene infrared simulation data. If the height range used is too small, it cannot cover the sensor height range in large scenes, making atmospheric transport textures used in large scenes incompatible with those used in small scenes.

[0014] The incompatibility between small and large scenes is essentially due to the observation geometry parameters, such as sensor height and detection distance. Minor adjustments to these parameters cause nonlinear abrupt changes in the detection range, target proportion, and atmospheric transmission path length, exceeding the parameter adaptation range of the original scene and thus leading to data consistency failure.

[0015] The incompatibility of observation geometry between small and large scenes stems from minute adjustments to the sensor height, such as increasing it by 1 meter. If the target height and sensor position are on the same order of magnitude, this will cause a significant non-linear increase in detection distance, leading to core parameters such as atmospheric transmission path length and observation angle exceeding the design thresholds of the original scene. The atmospheric transmission model, sensor calibration coefficients, and data processing algorithms in the original scene were all optimized based on specific geometric conditions. After a sudden change in parameters, the model's adaptability fails, and data consistency and measurement accuracy cannot be guaranteed, resulting in incompatibility between the two scenes. Scene design thresholds are pre-set allowable ranges / critical values ​​for core parameters such as detection distance, sensor height, and observation angle to ensure measurement accuracy, algorithm adaptability, and data validity in a specific scene.

[0016] Small scenes and large scenes each correspond to an independent set of design thresholds, and the threshold ranges of the two differ significantly. When the parameters cross from the threshold range of one scene to the threshold range of another scene, the original scene's model and algorithm will become ineffective, resulting in incompatibility between the two scenes. For example, regarding detection distance, the design threshold for small scenes is 5-50 meters for close-range detection. The design threshold for large scenes is 50-500 meters for medium- to long-range detection. An example of an incompatible trigger point is as follows: when the target height increases by 1 meter, the detection distance increases from 40 meters to 70 meters, exceeding the critical value of 50 meters.

[0017] To solve the above technical problems, see Appendix Figure 1 This application proposes a method for generating atmospheric transport data in a predetermined format with highly variable altitude, comprising: In step S102, the sensor determines the first atmospheric transport characteristic data calculated under the observation geometric parameters of the first atmospheric transport.

[0018] In this embodiment, the object is a target with changing altitude, such as a drone. Sensors are used to calculate atmospheric transmission for the drone in the air. The drone's altitude changes, causing the calculated atmospheric transmission results to also change. The change in drone altitude is for more comprehensive multipath measurement of the atmosphere. After the drone's altitude changes, the detection distance between the sensor and the drone will change significantly.

[0019] See appendix Figure 2 As shown, when the relative position between the sensor and the drone is horizontal, the detection distance is L1. When the drone's altitude increases, the detection distance becomes L2. L2 is obviously greater than L1, especially when the horizontal distance between the sensor and the drone is large, the difference between L2 and L1 will be very large.

[0020] Similarly, when a drone is stationary, but the sensor changes its position in the altitude direction, the detection range will also change significantly before and after the change.

[0021] In step S104, the distance geometric parameters in the observation geometric parameters of the first atmospheric transmission are input into the transformation model to obtain the observation geometric parameters of the second atmospheric transmission.

[0022] The observation geometric parameters of the first atmospheric transmission include: the altitude of the first target, the observation zenith angle, and the first detection distance.

[0023] In this embodiment, the first target altitude The values ​​are selected using an exponential distribution, one of which is... The unit is km. =0,1, 2,,,,,11, a total of 12 values, but not limited to this value selection method.

[0024] The first observation zenith angle is defined as the angle between the vector from the observation point to the sensor and the vector from the Earth's center to the observation point. One way to determine the observation zenith angle is to range from 0° to 180° with 10° intervals, but this method is not limited to this one.

[0025] First detection range L The slant distance from the observation point to the sensor is determined using an exponential distribution. One way to determine the detection distance is as follows: The unit is km. =0,1, 2,,,,,17, a total of 18 values, but not limited to this value selection method.

[0026] The distance geometry parameters include: the altitude of the first target and the first detection distance.

[0027] The transformation model is used to achieve a nonlinear transformation of pre-sensitization followed by saturation.

[0028] In this embodiment, the transformation model can be implemented using a logarithmic function, an arctangent function, or another method. The function implementation, where k is less than 1.

[0029] In step S106, a three-dimensional distribution map of first three-dimensional atmospheric transport data in a predetermined format is generated based on the observed geometric parameters of the second atmospheric transport and the first atmospheric transport characteristic data.

[0030] The distance geometric parameters in the first atmospheric transmission observation geometric parameters include: the altitude of the first target and the first detection distance; The observation geometric parameters of the second atmospheric transmission include: the altitude of the second target, the observation zenith angle, and the second detection distance; Wherein, the second target altitude is obtained by transforming the first target altitude using the transformation model; The second detection distance is obtained by transforming the first detection distance using the transformation model; The dimensions of the first three-dimensional atmospheric transport data distribution map in the predetermined format include at least the altitude of the second target and the second detection distance.

[0031] In this embodiment, a first three-dimensional atmospheric transmission data distribution map in a predetermined format can be generated based on the observed geometric parameters of the second atmospheric transmission and the first atmospheric transmission characteristic data. In the aforementioned first three-dimensional atmospheric transmission data distribution map in the predetermined format, the first dimension is the altitude of the second target, the second dimension is the zenith angle, and the third dimension is the second detection distance.

[0032] The technical solution described above in this application employs a transformation model to achieve a nonlinear transformation that is sensitized before saturation. This allows for the nonlinear transformation of distance geometric parameters, such as the altitude of the first target and the first detection distance, to be sensitized before saturation. The advantage of this transformation is that when the values ​​of the altitude of the first target and the first detection distance are relatively large, the transformed values ​​become relatively small. In particular, when the values ​​change, the transformed value tends to saturate, which is beneficial for achieving compatibility between atmospheric transport characteristic data calculated in large-scale scenarios and atmospheric transport characteristic data measured in small-scale scenarios.

[0033] In some embodiments, the transformation model includes: a logarithmic function, an arctangent function, or a power function; wherein the exponent of the power function is greater than zero and less than one.

[0034] In this embodiment, preferably, a logarithmic function is used, and the logarithmic function is: = .

[0035] When choosing a power function, the form of the power function is Y= Where K is a number greater than zero and less than 1.

[0036] Similar to the logarithmic and power functions mentioned above, the arctangent function also exhibits the characteristic that as the value of the x-coordinate increases, the value of the y-coordinate tends to stabilize, approaching saturation. This saturation characteristic is very suitable for the scenario requirements of this application.

[0037] For example, when a sensor changes position and its altitude increases, the detection distance obtained in the next detection will be significantly different from that of the previous detection. However, after processing with a transformation model, this variation will be reduced. This facilitates compatibility with atmospheric transmission data formats.

[0038] In some embodiments, the transformation model includes: a first transformation sub-model and a second transformation sub-model; The first transformation sub-model is used to transform the altitude of the first target to generate the altitude of the second target.

[0039] The second transformation sub-model is used to transform the first detection distance to generate the second detection distance.

[0040] In some embodiments, see Appendix Figure 3 After determining the first atmospheric transport characteristic data, the method may further include the following steps: In step S202, the first atmospheric transport characteristic data is subjected to differential expansion processing to obtain the second atmospheric transport characteristic data, and the observation geometric parameters of the third atmospheric transport are obtained.

[0041] In this embodiment, the acquisition of atmospheric transport characteristic data, such as transmittance, extinction coefficient, and radiance, is limited by issues such as the accuracy of observation equipment, observation costs, and insufficient spatiotemporal coverage. The raw data often exhibits sparsity or discontinuity. The core purpose of interpolation extension is to fill in the missing data based on existing sparse data using mathematical methods, forming a complete and continuous dataset to meet the needs of subsequent applications.

[0042] Atmospheric transmittance was measured at only 5 stations in a certain area. By interpolation, transmittance data for each 1km×1km grid in the area can be obtained, achieving full spatial coverage.

[0043] In this embodiment, the number of the observed geometric parameters of the third atmospheric transport is an integer power of 2.

[0044] In this embodiment, along with the differential expansion processing of the first atmospheric transport characteristic data, the number of observed geometric parameters of the second atmospheric transport is also differentially expanded to obtain the observed geometric parameters of the third atmospheric transport.

[0045] The number of observation geometric parameters for the third atmospheric transmission is an integer power of 2, in order to improve the efficiency of subsequent data processing and adapt to algorithms and hardware architecture.

[0046] In computers, integer powers of 2 can be quickly divided using binary shift operations, avoiding complex multiplication and division operations and significantly improving processing speed.

[0047] Frequency domain analysis of atmospheric transmission data, such as noise removal and feature extraction, often employs the Fast Fourier Transform (FFT). The FFT algorithm has the lowest computational complexity and can significantly reduce computation time when the input data length is an integer power of 2.

[0048] In step S204, a three-dimensional distribution map of second three-dimensional atmospheric transport data in a predetermined format is generated based on the second atmospheric transport characteristic data and the observation geometric parameters of the third atmospheric transport.

[0049] The three dimensions in the three-dimensional distribution map of the second three-dimensional atmospheric transmission data in the predetermined format are: the altitude of the second target after differential expansion processing, the zenith angle after differential expansion processing, and the second detection distance after differential expansion processing.

[0050] In some embodiments, step S102, determining the first atmospheric transport characteristic data calculated by the sensor under the observation geometric parameters of the first atmospheric transport, may specifically include the following steps: The sensor height and sensor zenith angle are determined based on the first target altitude, the observation zenith angle, and the first detection distance.

[0051] The aforementioned first atmospheric transmission characteristic data are determined based on the sensor height and sensor zenith angle. The first atmospheric transmission characteristic data includes transmittance and path radiation.

[0052] In this embodiment, the actual path of light through the atmosphere can be calculated using the sensor zenith angle and sensor height. The larger the zenith angle, the longer the path of light. The sensor height is used to determine the atmospheric density; the higher the altitude, the thinner the atmosphere, and the less absorption and scattering of light. With the sensor zenith angle and sensor height, combined with wavelength and atmospheric composition parameters, the transmittance is calculated. , ; Where T is the transmittance; n is the atmospheric molecular density, which is affected by the sensor height and the height of the target being measured. k is the proportionality constant of the atmospheric extinction coefficient; m is the total path of light propagation, which is affected by the detection distance and the observation zenith angle.

[0053] The path radiation is calculated based on the transmittance mentioned above.

[0054] In some embodiments, determining the sensor height based on the first target altitude, the observed zenith angle, and the first detection distance includes: ; in, For sensor height; The first target altitude; To observe the zenith angle; This is the first detection range.

[0055] In some embodiments, determining the sensor zenith angle based on the target altitude and the sensor height includes: ; in, The zenith angle of the sensor; The target altitude; For sensor height; L represents the first detection distance.

[0056] In some embodiments, when the transformation model is a logarithmic function, the target altitude from the observed geometric parameters of the first atmospheric transport is input into the transformation model to obtain the target altitude of the second atmospheric transport, including: = ; in, The altitude of the target is the observation geometric parameters for the first atmospheric transport. The altitude is the target elevation in the observed geometric parameters of the second atmospheric transport after transformation.

[0057] In some embodiments, when the transformation model is a logarithmic function, the detection range in the observation geometry parameters of the first atmospheric transmission is input into the transformation model to obtain the detection range of the second atmospheric transmission, including: = ; Where L is the first detection distance; This is the second detection range.

[0058] The following section details another method for processing background atmospheric transmission characteristics data suitable for real-time simulation of infrared scenes. The specific scheme is as follows: The first step is to determine the target altitude for the texture data. (Unit: km), Observed zenith angle (Unit: °) and detection distance L (Unit: km) Take the value and calculate the corresponding sensor height. (Unit: km) and sensor zenith angle (Unit: °).

[0059] Among them, the target altitude The values ​​are selected using an exponential distribution, one of which is... km, =0,1, 2,,,,,11, a total of 12 values, but not limited to this value selection method; Observation zenith angle Defined as the angle between the vector from the observation point to the sensor and the vector from the Earth's center to the observation point. One possible way to take this value is in the range of 0°-180° with 10° intervals, but it is not limited to this method. Detection range L The slope distance from the observation point to the sensor is taken using an exponential distribution, one possible method of taking the value is... km, =0,1, 2,,,,,17, a total of 18 values, but not limited to this value selection method.

[0060] Using sensor height in calculations for: ; Sensor zenith angle for: ; The second step is based on the sensor height. and sensor zenith angle Calculate the atmospheric transmission characteristics (transmittance, path radiation) of the sensor under different target altitudes, different observation zenith angles, and different detection distances in the scene coordinate system.

[0061] The third step is to adjust the target altitudes accordingly. Detection range L Convert to logarithms of height and distance , One of the conversion methods is, = , = However, it is not limited to this value selection method.

[0062] Step 4: For atmospheric transmission characteristic data, including transmittance and path radiation, the data is interpolated in three dimensions: logarithm of altitude, zenith angle of detection, and logarithm of detection distance, so that the number of logarithms of altitude, zenith angle of detection, and logarithm of detection distance after the interpolation are all integer powers of 2.

[0063] The fifth step involves converting the differentiated atmospheric transmission characteristic data into a three-dimensional image, using the logarithm of altitude, the detected zenith angle, and the logarithm of detection distance as dimensions. The A channel of each image pixel stores atmospheric transmittance, and the RGB channels store atmospheric path radiance data, with a path radiance storage precision of 0.001 W / (m²). 2 .Sr).

[0064] Atmospheric transport characteristic data are stored as binary files in array rows, with each array element consisting of four bytes. The first three bytes store the path radiation, with a storage precision of 0.001 W / (m²). 2 The fourth byte of the array (.Sr) stores the transmittance. The array elements are arranged in the order of logarithm of altitude, zenith angle of detection, and logarithm of detection distance. The innermost loop contains the logarithm of detection distance, and the outermost loop contains the logarithm of altitude.

[0065] The technical solution of this application provides a new atmospheric transmission image format and generation method suitable for simulating the infrared characteristics of aerial targets in infrared scenes. By redesigning the organization of atmospheric transmission data, it solves the problem of incompatibility in data accuracy between large-scale and small-scale local scenes in existing technologies. This image, combined with a graphics rendering engine, effectively solves the problem of atmospheric transmission coupling simulation accuracy in large-scale and local fine-scale scene simulations. This application can provide a high-precision atmospheric transmission coupling scheme for aerial targets in real-time simulation of comprehensive scene infrared characteristics based on a graphics rendering engine.

[0066] Centered on the target, atmospheric transmission characteristic parameters are stored in a 3D image using the logarithm of the target's altitude and the logarithm of the sensor's zenith angle and distance in the scene as dimensions. This supports the simulation of the infrared characteristics of aerial targets in the scene and solves the problems of drastic changes in atmospheric transmission parameters with detector altitude under horizontal viewpoint and incompatibility between atmospheric transmission images of aerial targets in large scenes and local small scenes.

[0067] Secondly, this application proposes an atmospheric transmission data generation device with a predetermined format for target altitude changes, see appendix. Figure 4 ,include: The first determining module 21 is used to determine the first atmospheric transmission characteristic data calculated by the sensor under the observation geometric parameters of the first atmospheric transmission; The conversion module 22 is used to input the distance geometric parameters in the observation geometric parameters of the first atmospheric transmission into the transformation model to obtain the observation geometric parameters of the second atmospheric transmission. The transformation model is used to achieve a nonlinear transformation of pre-sensitization followed by saturation. Image module 23 is used to generate a first three-dimensional atmospheric transmission data three-dimensional distribution map in a predetermined format based on the observed geometric parameters of the second atmospheric transmission and the first atmospheric transmission characteristic data. The observation geometric parameters of the first atmospheric transmission include: the altitude of the first target, the observation zenith angle, and the first detection distance; The distance geometric parameters in the first atmospheric transmission observation geometric parameters include: the altitude of the first target and the first detection distance; The observation geometric parameters of the second atmospheric transmission include: the altitude of the second target, the observation zenith angle, and the second detection distance; Wherein, the second target altitude is obtained by transforming the first target altitude using the transformation model; The second detection distance is obtained by transforming the first detection distance using the transformation model; The dimensions of the first three-dimensional atmospheric transport data distribution map in the predetermined format include at least the altitude of the second target and the second detection distance.

[0068] In some embodiments, a difference processing module is further included, which, after the first determining module 21 determines the first atmospheric transport characteristic data, performs difference expansion processing on the first atmospheric transport characteristic data to obtain the second atmospheric transport characteristic data and obtain the observed geometric parameters of the third atmospheric transport. The number of the observed geometric parameters of the third atmospheric transmission are all integer powers of 2; A second three-dimensional atmospheric transport data three-dimensional distribution map in a predetermined format is generated based on the second atmospheric transport characteristic data and the observation geometric parameters of the third atmospheric transport. The three dimensions in the three-dimensional distribution map of the second three-dimensional atmospheric transmission data in the predetermined format are: the altitude of the second target after differential expansion processing, the zenith angle after differential expansion processing, and the second detection distance after differential expansion processing.

[0069] In some embodiments, the first determining module 21 is further configured to determine the sensor height and the sensor zenith angle based on the first target altitude, the observed zenith angle, and the first detection distance; The first atmospheric transport characteristic data is determined based on the sensor height and the sensor zenith angle.

[0070] The first determining module 21 is also used to calculate using the following formula: ; in, For sensor height; The first target altitude; To observe the zenith angle; This is the first detection range; ; in, The zenith angle of the sensor; The target altitude; For sensor height; L represents the first detection distance.

[0071] The conversion module 22 is also used to input the target altitude from the observation geometric parameters of the first atmospheric transmission into the conversion model when the transformation model is a logarithmic function, to obtain the target altitude of the second atmospheric transmission, including: = ; in, The altitude of the target is the observation geometric parameters for the first atmospheric transport. The altitude is the target elevation in the observed geometric parameters of the second atmospheric transport after transformation.

[0072] In some embodiments, the conversion module 22 is further configured to, when the transformation model is a logarithmic function, input the detection range in the observation geometric parameters of the first atmospheric transmission into the transformation model to obtain the detection range of the second atmospheric transmission, including: = ; Where L is the first detection distance; This is the second detection range.

[0073] Thirdly, see appendix. Figure 5 This application proposes an electronic device including a memory 32, a processor 31, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described above.

[0074] The aforementioned electronic devices can be computing devices such as desktop computers, laptops, handheld computers, and cloud servers. These electronic devices may include, but are not limited to, processors and memory. Those skilled in the art will understand that the figures are merely examples of electronic devices and do not constitute a limitation on the electronic devices. They may include more or fewer components than illustrated, or combine certain components, or different components. For example, the aforementioned electronic devices may also include input / output devices, network access devices, buses, etc.

[0075] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0076] Fourthly, this application proposes a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the steps of any of the above methods.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating atmospheric transmission data of a predetermined format for an aerial moving target, characterized in that, include: Determine the first atmospheric transport characteristic data calculated by the sensor under the observed geometric parameters of the first atmospheric transport; The distance geometric parameters from the first atmospheric transmission observation geometric parameters are input into the transformation model to obtain the second atmospheric transmission observation geometric parameters. The transformation model is used to achieve a nonlinear transformation of pre-sensitization followed by saturation. Based on the observed geometric parameters of the second atmospheric transport and the first atmospheric transport characteristic data, a first three-dimensional atmospheric transport data three-dimensional distribution map in a predetermined format is generated. The observation geometric parameters of the first atmospheric transmission include: the altitude of the first target, the observation zenith angle, and the first detection distance; The distance geometric parameters in the first atmospheric transmission observation geometric parameters include: the altitude of the first target and the first detection distance; The observation geometric parameters of the second atmospheric transmission include: the altitude of the second target, the observation zenith angle, and the second detection distance; Wherein, the second target altitude is obtained by transforming the first target altitude using the transformation model; The second detection distance is obtained by transforming the first detection distance using the transformation model; The dimensions of the first three-dimensional atmospheric transport data distribution map in the predetermined format include at least the altitude of the second target and the second detection distance.

2. The method for generating atmospheric transmission data of a predetermined format for an aerial moving target according to claim 1, characterized in that, The transformation model includes: a logarithmic function, an arctangent function, or a power function; Wherein, the exponent of the power function is greater than zero and less than one.

3. The method for generating atmospheric transmission data of a predetermined format for an aerial moving target according to claim 1, characterized in that, The transformation model includes: a first transformation sub-model and a second transformation sub-model; The first transformation sub-model is used to transform the altitude of the first target to generate the altitude of the second target; The second transformation sub-model is used to transform the first detection distance to generate the second detection distance.

4. The method for generating atmospheric transmission data in a predetermined format for aerial moving targets according to claim 1, characterized in that, After determining the first atmospheric transport characteristic data calculated by the sensor under the observed geometric parameters of the first atmospheric transport, the method further includes: The first atmospheric transport characteristic data is subjected to interpolation expansion processing to obtain the second atmospheric transport characteristic data, and the observation geometric parameters of the third atmospheric transport are obtained. A second three-dimensional atmospheric transport data three-dimensional distribution map in a predetermined format is generated based on the second atmospheric transport characteristic data and the observation geometric parameters of the third atmospheric transport. The three dimensions in the three-dimensional distribution map of the second three-dimensional atmospheric transmission data in the predetermined format are: the altitude of the second target after differential expansion processing, the zenith angle after differential expansion processing, and the second detection distance after differential expansion processing.

5. The method for generating atmospheric transmission data of a predetermined format for an aerial moving target according to claim 4, characterized in that, in, The number of the observed geometric parameters for the third atmospheric transport is an integer power of 2.

6. The method for generating atmospheric transmission data of a predetermined format for an aerial moving target according to claim 1, characterized in that, Determine the first atmospheric transport characteristic data calculated by the sensor under the observed geometric parameters of first atmospheric transport, including: The sensor height and sensor zenith angle are determined based on the first target altitude, the observed zenith angle, and the first detection distance. The first atmospheric transport characteristic data is determined based on the sensor height and the sensor zenith angle.

7. The method for generating atmospheric transmission data of a predetermined format for an aerial moving target according to claim 6, characterized in that, Determining the sensor height and sensor zenith angle based on the first target altitude, the observed zenith angle, and the first detection distance includes: ； in, For sensor height; The first target altitude; To observe the zenith angle; ； in, The zenith angle of the sensor; The target altitude; For sensor height; L represents the first detection distance.

8. The method for generating atmospheric transmission data of a predetermined format for an aerial moving target according to claim 2, characterized in that, When the transformation model is a logarithmic function, the target altitude from the observed geometric parameters of the first atmospheric transport is input into the transformation model to obtain the target altitude of the second atmospheric transport, including: = ； in, The altitude of the target is the observation geometric parameters for the first atmospheric transport. The altitude is the target elevation in the observed geometric parameters of the second atmospheric transport after transformation.

9. The method for generating atmospheric transmission data of a predetermined format for an aerial moving target according to claim 1, characterized in that: When the transformation model is a logarithmic function, the detection range from the observation geometry parameters of the first atmospheric transmission is input into the transformation model to obtain the detection range of the second atmospheric transmission, including: = ； Where L is the first detection distance; This is the second detection range.

10. An apparatus for generating atmospheric transmission data in a predetermined format for aerial moving targets, characterized in that, include: The first determining module is used to determine the first atmospheric transmission characteristic data calculated by the sensor under the observation geometric parameters of the first atmospheric transmission; The conversion module is used to input the distance geometric parameters from the observation geometric parameters of the first atmospheric transmission into the transformation model to obtain the observation geometric parameters of the second atmospheric transmission. The transformation model is used to achieve a nonlinear transformation of pre-sensitization followed by saturation. The image module is used to generate a first three-dimensional atmospheric transport data three-dimensional distribution map in a predetermined format based on the observed geometric parameters of the second atmospheric transport and the first atmospheric transport characteristic data. The observation geometric parameters of the first atmospheric transmission include: the altitude of the first target, the observation zenith angle, and the first detection distance; The distance geometric parameters in the first atmospheric transmission observation geometric parameters include: the altitude of the first target and the first detection distance; The observation geometric parameters of the second atmospheric transmission include: the altitude of the second target, the observation zenith angle, and the second detection distance; Wherein, the second target altitude is obtained by transforming the first target altitude using the transformation model; The second detection distance is obtained by transforming the first detection distance using the transformation model; The dimensions of the first three-dimensional atmospheric transport data distribution map in the predetermined format include at least the altitude of the second target and the second detection distance.

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