Geogas light scattering distribution characteristic simulation method based on spatial non-uniform parameter driving

Abstract

The invention discloses a geogas light scattering distribution characteristic simulation method based on spatial non-uniform parameter driving, and belongs to the technical field of scattering characteristic simulation. According to the method, firstly, the conversion relation between a global uniform longitude and latitude grid model and a detector local coordinate system is established, and accurate dispersion and coordinate unification of detection light vectors are achieved; then calculating the spatial relationship between the detection light and the earth surface, and judging a limb or non-limb detection mode; non-uniform parameters such as earth surface albedo, aerosol optical thickness and cloud optical thickness of corresponding positions are rapidly extracted based on a grid index mechanism; and finally, radiance values are calculated by adopting corresponding parameterized models according to different detection modes, and a complete radiance distribution image is synthesized, so that the authenticity and the precision of geogas light scattering distribution characteristic simulation are remarkably improved.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of scattering characteristic simulation, in particular to a ground-to-air light scattering distribution characteristic simulation method based on spatial non-uniform parameter driving. BACKGROUND

[0002] At present, the ground-to-air light is mainly estimated by atmospheric radiation transmission calculation software, such as the popular MODTRAN software in the industry. However, the interaction between the cloud-aerosol-atmosphere-ground-radiation is described roughly by the software, and the one-dimensional radiation transmission model is generally used in the complex ground-to-air background, that is, the horizontal isotropy is maintained in each atmospheric layer, and the influence of the non-uniformity of the ground, cloud and aerosol in the horizontal direction is not considered. This method can only calculate the ground-to-air light scattering radiance in a single direction and a unit field of view, resulting in low simulation precision of the ground-to-air light scattering distribution characteristic.

[0003] Therefore, it is necessary to provide a ground-to-air light scattering distribution characteristic simulation method based on spatial non-uniform parameter driving. SUMMARY

[0004] In order to solve the problem that the traditional simulation method does not consider the influence of the non-uniformity of the ground, cloud and aerosol in the horizontal direction, resulting in low simulation precision, the embodiment of the present application provides a ground-to-air light scattering distribution characteristic simulation method based on spatial non-uniform parameter driving. The technical scheme is as follows: On the one hand, the present application provides a ground-to-air light scattering distribution characteristic simulation method based on spatial non-uniform parameter driving, characterized in that the method comprises: obtaining spatial non-uniform distribution data corresponding to a ground surface latitude and longitude grid; the spatial non-uniform distribution data at least includes ground surface albedo distribution data, aerosol optical thickness distribution data and cloud optical thickness distribution data; establishing a local coordinate system based on the position of a detector, and discretizing the light rays of the detector based on the detection direction to convert to obtain a plurality of detection light ray vectors in the earth-fixed coordinate system; respectively calculating the spatial relationship between each detection light ray vector and the earth surface and determining the detection mode, and extracting the parameter data of the target position from the spatial non-uniform distribution data based on the detection mode; the parameter data includes the ground surface albedo, the aerosol type, the aerosol optical thickness and the cloud optical thickness; the detection mode includes the edge detection mode and the non-edge detection mode; For each detection light ray vector, the parameter data of the target position is input into the parameterized model under the detection mode corresponding to the current detection light ray vector to calculate the radiance value, and the radiance values corresponding to all detection light ray vectors are synthesized to generate the ground-to-air light scattering distribution characteristic simulation result in the field of view of the detector.

[0005] On the other hand, the present invention provides a simulation device for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters, characterized in that the device comprises: The data preparation module is used to acquire spatially non-uniformly distributed data corresponding to the latitude and longitude grid of the Earth's surface; the spatially non-uniformly distributed data includes at least surface albedo distribution data, aerosol optical thickness distribution data, and cloud optical thickness distribution data; The light discretization module is used to establish a local coordinate system based on the detector position and discretize the detector light rays based on the detection direction to obtain several detector light ray vectors in the Earth-fixed coordinate system. The data extraction module is used to calculate the spatial relationship between each of the probe ray vectors and the Earth's surface and determine the detection mode. Based on the detection mode, it extracts parameter data of the target location from the spatially non-uniformly distributed data. The parameter data includes surface albedo, aerosol type, aerosol optical thickness, and cloud optical thickness. The detection modes include limb detection mode and non-limb detection mode. The radiance calculation module is used to input the parameter data of the target position into the parameterized model of the detection mode corresponding to the current detection ray vector for each of the detection ray vectors to calculate the radiance value, and synthesize the radiance values ​​corresponding to all detection ray vectors to generate simulation results of the ground-atmosphere light scattering distribution characteristics within the detector's field of view.

[0006] On the other hand, the present invention provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in any one of the present specification.

[0007] On the other hand, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the method described in any one of the present specification.

[0008] On the other hand, the present invention provides a computer program product, characterized in that it includes a computer program, which, when executed by a processor, implements the steps of any of the methods described in this specification.

[0009] This invention provides a simulation method for the distribution characteristics of Earth-atmosphere light scattering based on spatially non-uniform parameters. This method first establishes a transformation relationship between a global uniform latitude and longitude grid model and the detector's local coordinate system, achieving precise discretization and coordinate unification of the probe ray vector. Then, it calculates the spatial relationship between the probe ray and the Earth's surface, intelligently determining whether the detection mode is near or far from the edge. Next, based on a grid indexing mechanism, it quickly extracts non-uniform parameters such as surface albedo, aerosol optical thickness, and cloud optical thickness at the corresponding locations. Finally, it uses corresponding parametric models to calculate radiance values ​​for different detection modes and synthesizes a complete radiance distribution image, significantly improving the realism and accuracy of the simulation of Earth-atmosphere light scattering distribution characteristics. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart of a simulation method for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters, provided by an example of the present invention. Figure 2 This is a schematic diagram of a detection ray discretization provided by an example of the present invention; Figure 3 This is a schematic diagram of reverse ray tracing provided by an example of the present invention; Figure 4 This is a schematic diagram of an observation geometry provided by an example of the present invention; Figure 5 This is a hardware architecture diagram of an electronic device provided in an embodiment of the present invention; Figure 6 This is a structural diagram of a simulation device for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters, provided in an embodiment of the present invention. Detailed Implementation

[0012] 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 some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0013] The inventive concept of this invention lies in: firstly, establishing the transformation relationship between a global uniform latitude and longitude grid model and the detector's local coordinate system to achieve precise discretization and coordinate unification of the probe ray vector; then, calculating the spatial relationship between the probe ray and the Earth's surface to intelligently determine whether the probe is near or far from the edge; furthermore, rapidly extracting non-uniform parameters such as surface albedo, aerosol optical thickness, and cloud optical thickness at the corresponding location based on a grid indexing mechanism; finally, calculating the radiance value using a corresponding parametric model for different probe modes and synthesizing a complete radiance distribution image, significantly improving the realism and accuracy of the simulation of Earth-atmosphere light scattering distribution characteristics.

[0014] The following describes the specific implementation of the above concept.

[0015] Please refer to Figure 1 This invention provides a simulation method for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters, the method comprising: Step 100: Obtain spatially non-uniformly distributed data corresponding to the latitude and longitude grid of the Earth's surface; the spatially non-uniformly distributed data shall include at least the surface albedo distribution data, aerosol optical thickness distribution data, and cloud optical thickness distribution data; Step 102: Establish a local coordinate system based on the detector position, and discretize the detector rays based on the detection direction to obtain several detector ray vectors in the Earth-fixed coordinate system. Step 104: Calculate the spatial relationship between each probe ray vector and the Earth's surface and determine the detection mode. Based on the detection mode, extract the parameter data of the target location from the spatially non-uniformly distributed data. The parameter data includes surface albedo, aerosol type, aerosol optical thickness, and cloud optical thickness. The detection modes include limb detection mode and non-limb detection mode. Step 106: For each probe ray vector, the parameter data of the target position is input into the parameterized model of the detection mode corresponding to the current probe ray vector to calculate the radiance value. The radiance values ​​corresponding to all probe ray vectors are synthesized to generate the simulation results of the ground-atmosphere light scattering distribution characteristics within the detector's field of view.

[0016] In this invention, the transformation relationship between a global uniform latitude and longitude grid model and the detector's local coordinate system is first established to achieve precise discretization and coordinate unification of the probe ray vector; then, the spatial relationship between the probe ray and the Earth's surface is calculated to intelligently determine whether the probe is near or far from the edge; furthermore, non-uniform parameters such as surface albedo, aerosol optical thickness, and cloud optical thickness at the corresponding location are quickly extracted based on a grid indexing mechanism; finally, radiance values ​​are calculated using corresponding parametric models for different probe modes, and a complete radiance distribution image is synthesized, significantly improving the realism and accuracy of the simulation of Earth-atmosphere light scattering distribution characteristics.

[0017] The following descriptionFigure 1 The execution method of each step is shown.

[0018] First, regarding step 100: Acquire spatially non-uniformly distributed data corresponding to the latitude and longitude grid of the Earth's surface. The spatially non-uniformly distributed data shall include at least the distribution data of surface albedo, aerosol optical thickness, and cloud optical thickness.

[0019] In this invention, non-uniform distribution data of parameters such as surface albedo, aerosol type, aerosol optical thickness, and cloud optical thickness for the same region to be calculated are obtained. The geographical latitude and longitude division of these parameters is kept consistent, and the non-uniformity of the spatial distribution of the surface, atmosphere, and clouds is represented in the form of gridded matrix data. The data structure is in the form of an N×M matrix. Since the surface is expressed by directional reflectance, the surface environment is different at different latitude and longitude locations, the surface albedo is different, and the contribution to the radiance of the detector direction is different.

[0020] Regarding step 102: In this embodiment of the invention, the local coordinate system has the detector position as the origin, the Z-axis pointing to the Earth's center, the X-axis along the latitude line, and the Y-axis determined according to the right-hand coordinate system defined by the X and Z axes; the Earth-fixed coordinate system has the Earth's center as the origin, the X-axis pointing to the intersection of the Prime Meridian and the equator on the equatorial plane, the Z-axis perpendicular to the equatorial plane pointing to the North Pole, and the Y-axis determined according to the right-hand coordinate system defined by the X and Z axes.

[0021] like Figure 2 As shown, in the detector's local coordinate system, based on the set field of view and the number of pixels in the imaging array, the continuous detection field of view is discretized into multiple rays corresponding one-to-one with each pixel. Pixels are numbered using a two-dimensional array (i,j), where the first index i represents the process from small to large in the X-axis direction, and the second index j represents the process from small to large in the Y-axis direction. The rays are uniformly distributed within the field of view, ensuring that each pixel has a corresponding detection ray. When the imaging array has a rotation angle, all discrete rays will be rotated accordingly. The figure shows the ray discretization when the center detection direction is (0,0,1). By rotation, the discrete ray distribution corresponding to any center detection vector can be obtained. After discretizing the detection rays in the local coordinate system, each detection ray is transformed to obtain several detection ray vectors in the Earth-fixed coordinate system.

[0022] Regarding step 104: In some implementations, step 104, "calculating the spatial relationship between each probe ray vector and the Earth's surface and determining the detection mode, and extracting parameter data of the target location from the spatially non-uniformly distributed data based on the detection mode," may include: The discriminant is calculated based on the detector position vector and the direction vector of the detector ray, and the detection mode is determined based on the value of the discriminant. When the discriminant is less than zero, the probe ray has no intersection with the Earth's surface, and it is determined to be an edge detection mode. The coordinates of the tangent point between the probe ray and the Earth's surface are calculated as the target position, so as to extract the parameter data of the target position from the spatially non-uniformly distributed data. When the discriminant is greater than or equal to zero, the probe ray intersects with the Earth's surface, which is determined to be a non-edge detection mode. The coordinates of the intersection point between the probe ray and the Earth's surface are calculated as the target position, so as to extract the parameter data of the target position from the spatially non-uniformly distributed data.

[0023] Specifically, the discriminant is determined by the following formula: in, p Let be the detector position vector. d To detect the direction vector of the light ray, R The radius is the Earth's radius.

[0024] refer to Figure 3 In a preferred embodiment, step 104 calculates the coordinates of the intersection point of the probe ray and the Earth's surface as the target location to extract parameter data of the target location from spatially non-uniformly distributed data, including: Based on the detector's position vector and the direction vector of the probe ray, calculate the distance between the detector and the point where the probe ray intersects the Earth's surface; Based on the detector position vector, the direction vector of the probe ray, and the distance, the coordinates of the intersection point in the Earth-fixed coordinate system are determined. Calculate the zenith angle and azimuth angle of the intersection point based on its coordinates in the Earth-fixed coordinate system. Based on the zenith and azimuth coordinates of the intersection point, and the grid scale of the pre-divided latitude and longitude grid in the longitude and latitude directions, the index coordinates of the intersection point in the latitude and longitude grid are calculated to extract the parameter data of the index coordinates from the spatially non-uniformly distributed data.

[0025] In this embodiment, Figure 3 The description specifically depicts the location of the detector. p Departure, along the direction d The principle of calculating the intersection point of the observed light rays with the Earth's surface.

[0026] Specifically, the distance between the detector and the point where the probe ray intersects the Earth's surface is determined by the following formula: in, t int For detector pAnd to detect the distance between the point where the light rays intersect with the Earth's surface.

[0027] The coordinates of the intersection point in the Earth-fixed coordinate system are determined by the following formula: in, r int The coordinates of the intersection point in the Earth-fixed coordinate system.

[0028] The zenith angle and azimuth angle coordinates of the intersection point are determined by the following formula: in,( x int , y int , z int ) The coordinates of the intersection point in the Earth-fixed coordinate system are: The coordinates of the zenith angle and the coordinates of the azimuth angle of the intersection point.

[0029] Specifically, the index coordinates of the intersection point on the Earth's surface latitude and longitude grid are determined by the following formula: in, The symbol for rounding down is ( m int , n int ) represents the index coordinates of the intersection point on the Earth's surface latitude and longitude grid.

[0030] After converting the index coordinates to the Earth-fixed coordinate system, the parameter data of the index coordinates can be extracted from spatially non-uniformly distributed data.

[0031] Specifically, the grid element index coordinates are converted to coordinates in the Earth-fixed coordinate system as follows: in, These represent the number of grid divisions in the latitude and longitude directions, respectively. These represent the grid scale of the Earth's surface latitude and longitude grid in the longitude and latitude directions, respectively, characterizing the degree of refinement of the grid cells; This indicates the sequential positioning of grid elements along the latitude and longitude directions; x , y , z This indicates the sequential positioning of the grid elements in the Earth-Fixed Coordinate System.

[0032] Regarding step 106: In some implementations, the inputs to the edge detection parameterization model also include a first detection geometry angle; the first detection geometry angle includes the solar zenith angle, the edge cutting height, and the relative azimuth angle; The input to the non-proximal edge detection parameterization model also includes a second detection geometry angle; the second detection geometry angle includes the solar zenith angle, the observation zenith angle, and the relative azimuth angle; In a preferred embodiment, in step 106, the second detection geometry angle is calculated as follows: The solar zenith angle is calculated based on the normal vector at the intersection of the probe ray and the Earth's surface and the solar direction vector. The observed zenith angle is calculated based on the unit vector of the detection direction and the normal vector at the intersection point; The relative azimuth angle is calculated based on the projection vector of the unit vectors of the solar direction vector and the probe direction onto the tangent plane.

[0033] like Figure 4 As shown, the solar zenith angle and the observed zenith angle are calculated using the normal vector *n* at the intersection of the probe ray and the Earth's surface, based on the unit vector *s* of the solar direction and the unit vector *e* of the probe direction. The relative azimuth angle is calculated using the projection vectors *s* of the solar direction and the observed direction onto the tangent plane at their intersection. n and e n Finish.

[0034] Combination Figure 4 The second detection geometry angle is determined by the following formula: in, The zenith angle of the sun. To observe the zenith angle, The relative azimuth angle. e Let be the unit vector in the direction of detection. n To detect the normal vector at the point where the light ray intersects the Earth's surface, s n and e n These are the projection vectors onto the tangent plane of the unit vectors of the solar direction and the probe direction, respectively. s This is the direction vector of the sun.

[0035] In some implementations, the solar direction vector is calculated as follows: The solar declination is calculated based on ordinal days; wherein, the ordinal days are the number of days from January 1 of the current year to the time of the probe. Based on the detection time, time difference correction term, standard meridian longitude and true solar time, the geographical longitude of the subsolar point at the detection time is calculated; The solar direction vector is calculated based on the solar declination and the geographical longitude of the subsolar point.

[0036] Specifically, the solar direction vector is calculated using the following formula: Where n is the ordinal number day, B The intermediate angle variable introduced for calculating the time difference correction term. The solar declination, L To determine the geographical longitude of the subsolar point at a given time, For the detection time, For time zone correction, Standard meridian longitude, True solar time s This is the direction vector of the sun.

[0037] It should be noted that the detection time parameter consists of year, month, and day, used to calculate the ordinal day; the detection time parameter consists of hour, minute, and second, used to determine the sun's position. In addition to the input parameters mentioned above, the number of CPU threads needs to be set to achieve parallel computing optimization, and an angle file requiring the calculation of Earth-atmosphere light scattering can be selectively input to output calculation results according to specific angle requirements. These input parameters together constitute the complete input conditions for calculating the Earth-atmosphere light scattering distribution.

[0038] like Figure 5 , Figure 6 As shown, this embodiment of the invention provides a simulation device for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters. The device can be implemented in software, hardware, or a combination of both. From a hardware perspective, as... Figure 5 The diagram shown is a hardware architecture diagram of a computing device for simulating the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters, as provided in an embodiment of the present invention. Except for... Figure 5 In addition to the processor, memory, network interface, and non-volatile memory shown, the computing device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing packets. Taking software implementation as an example, such as... Figure 6 As shown, a device in a logical sense is formed by the CPU of the computing device in which it is located reading the corresponding computer program from the non-volatile memory into the memory for execution.

[0039] likeFigure 6 As shown, this embodiment of the invention provides a simulation device for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters, comprising: The data preparation module 600 is used to acquire spatially non-uniformly distributed data corresponding to the latitude and longitude grid of the Earth's surface; the spatially non-uniformly distributed data includes at least surface albedo distribution data, aerosol optical thickness distribution data, and cloud optical thickness distribution data; The light discretization module 602 is used to establish a local coordinate system based on the detector position and discretize the detector light rays based on the detection direction to obtain several detector light ray vectors in the Earth-fixed coordinate system. The data extraction module 604 is used to calculate the spatial relationship between each probe ray vector and the Earth's surface and determine the detection mode. Based on the detection mode, it extracts the parameter data of the target location from the spatially non-uniformly distributed data. The parameter data includes surface albedo, aerosol type, aerosol optical thickness, and cloud optical thickness. The detection modes include limb detection mode and non-limb detection mode. The radiance calculation module 606 is used to input the parameter data of the target position into the parameterized model of the detection mode corresponding to the current detection ray vector for each detection ray vector to calculate the radiance value, and synthesize the radiance values ​​corresponding to all detection ray vectors to generate simulation results of the ground-atmosphere light scattering distribution characteristics within the detector's field of view.

[0040] In some specific implementations, the data preparation module 600 can be used to perform the above step 100, the light discretization module 602 can be used to perform the above step 102, the data extraction module 604 can be used to perform the above step 104, and the radiance synthesis 606 can be used to perform the above step 106.

[0041] In some specific implementations, when the detection mode is determined, the data extraction module 604 performs the following operations: The discriminant is calculated based on the detector position vector and the direction vector of the detector ray, and the detection mode is determined based on the value of the discriminant. When the discriminant is less than zero, the probe ray has no intersection with the Earth's surface, and it is determined to be an edge detection mode. The coordinates of the tangent point between the probe ray and the Earth's surface are calculated as the target position, so as to extract the parameter data of the target position from the spatially non-uniformly distributed data. When the discriminant is greater than or equal to zero, the probe ray intersects with the Earth's surface, which is determined to be a non-edge detection mode. The coordinates of the intersection point between the probe ray and the Earth's surface are calculated as the target position, so as to extract the parameter data of the target position from the spatially non-uniformly distributed data.

[0042] In some specific implementations, when the data extraction module 604 extracts parameter data of the target location from spatially non-uniformly distributed data based on the detection mode, it performs the following operations: Based on the detector's position vector and the direction vector of the probe ray, calculate the distance between the detector and the point where the probe ray intersects the Earth's surface; Based on the detector position vector, the direction vector of the probe ray, and the distance, the coordinates of the intersection point in the Earth-fixed coordinate system are determined. Calculate the zenith angle and azimuth angle of the intersection point based on its coordinates in the Earth-fixed coordinate system. Based on the zenith and azimuth coordinates of the intersection point, and the grid scale of the pre-divided latitude and longitude grid in the longitude and latitude directions, the index coordinates of the intersection point in the latitude and longitude grid are calculated to extract the parameter data of the index coordinates from the spatially non-uniformly distributed data.

[0043] In some specific implementations, when the radiance calculation module 606 calculates the radiance value by inputting the parameter data of the target position into the parameterized model of the detection mode corresponding to the current detection ray vector, it performs the following operations: The input to the edge detection parameterization model also includes the first detection geometry angle; the first detection geometry angle includes the solar zenith angle, the edge cutting height, and the relative azimuth angle; The input to the non-proximal edge detection parameterization model also includes a second detection geometry angle; the second detection geometry angle includes the solar zenith angle, the observation zenith angle, and the relative azimuth angle.

[0044] In some specific implementations, the radiance calculation module 606 is also used to perform the following operations: The second detection geometry angle is calculated as follows: The solar zenith angle is calculated based on the normal vector at the intersection of the probe ray and the Earth's surface and the solar direction vector. The observed zenith angle is calculated based on the unit vector of the detection direction and the normal vector at the intersection point; The relative azimuth angle is calculated based on the projection vector of the unit vectors of the solar direction vector and the probe direction onto the tangent plane.

[0045] In some specific implementations, the radiance calculation module 606 is also used to perform the following operations: The solar direction vector is calculated as follows: The solar declination is calculated based on ordinal days; where the ordinal day is the number of days from January 1 of the current year to the time of the probe. Based on the detection time, time difference correction term, standard meridian longitude and true solar time, the geographical longitude of the subsolar point at the detection time is calculated; The solar direction vector is calculated based on the solar declination and the geographical longitude of the subsolar point.

[0046] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on a simulation device for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters. In other embodiments of the present invention, a simulation device for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters may include more or fewer components than illustrated, or combine some components, split some components, or arrange different components. The components illustrated may be implemented in hardware, software, or a combination of software and hardware.

[0047] The information interaction and execution process between the modules in the above-mentioned device are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description of the method embodiment of the present invention, and will not be repeated here.

[0048] This invention also provides a computing device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a simulation method for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters, according to any embodiment of this invention.

[0049] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program causes the processor to perform a simulation method for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters, according to any embodiment of this invention.

[0050] Embodiments of this application also provide a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium and executes the computer program, causing the computer device to perform a simulation method for the distribution characteristics of ground-atmosphere light scattering based on spatially non-uniform parameters as described in any of the above embodiments.

[0051] Specifically, an apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the embodiments described above is stored, and the computer (or CPU or MPU) of the apparatus may read and execute the program code stored in the storage medium.

[0052] In this case, the program code read from the storage medium can itself implement the function of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute part of the present invention.

[0053] Storage media embodiments for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0054] Furthermore, it should be clear that not only can the program code read by the computer be executed, but also the operating devices on the computer can be instructed based on the program code to perform some or all of the actual operations, thereby realizing the function of any of the above embodiments.

[0055] Furthermore, it is understood that the program code read from the storage medium is written to the memory set in the expansion board inserted into the computer or to the memory set in the expansion module connected to the computer. Then, based on the instructions of the program code, the CPU or other components installed on the expansion board or expansion module execute some and all of the actual operations, thereby realizing the function of any of the above embodiments.

[0056] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0057] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0058] 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 simulating the distribution characteristics of the light scattering between the atmosphere and the ground based on spatial non-uniform parameters, characterized in that, The method comprises: acquiring spatial non-uniform distribution data corresponding to a terrestrial latitude-longitude grid; the spatial non-uniform distribution data at least includes surface albedo distribution data, aerosol optical depth distribution data and cloud optical depth distribution data; establishing a local coordinate system based on a detector position, and discretizing a detector light ray based on a detection direction to convert to obtain a plurality of detection light ray vectors in a geostationary coordinate system; calculating the spatial relationship of each detection light ray vector with the earth's surface and determining a detection mode, and extracting parameter data of a target position from the spatial non-uniform distribution data based on the detection mode; the parameter data includes surface albedo, aerosol type, aerosol optical depth and cloud optical depth; the detection mode includes a limb detection mode and a non-limb detection mode; for each detection light ray vector, inputting the parameter data of the target position into a parameterized model under the detection mode corresponding to the current detection light ray vector to calculate a radiance value, and synthesizing the radiance values corresponding to all detection light ray vectors to generate a simulation result of the atmospheric light scattering distribution characteristics within the field of view of the detector.

2. The method of claim 1, wherein, The calculation of the spatial relationship of each detection light ray vector with the earth's surface and the determination of the detection mode, and the extraction of the parameter data of the target position from the spatial non-uniform distribution data based on the detection mode, comprises: calculating a discriminant based on the detector position vector and the direction vector of the detection light ray, and determining the detection mode according to the value of the discriminant; when the discriminant is less than zero, the detection light ray has no intersection with the earth's surface, and the detection mode is determined as a limb detection mode, the tangent point coordinates of the detection light ray and the earth's surface are calculated as the target position to extract the parameter data of the target position from the spatial non-uniform distribution data; when the discriminant is greater than or equal to zero, the detection light ray intersects with the earth's surface, and the detection mode is determined as a non-limb detection mode, the intersection point coordinates of the detection light ray and the earth's surface are calculated as the target position to extract the parameter data of the target position from the spatial non-uniform distribution data.

3. The method of claim 2, wherein, The calculation of the intersection point coordinates of the detection light ray and the earth's surface as the target position to extract the parameter data of the target position from the spatial non-uniform distribution data comprises: calculating the distance between the detector and the intersection point of the detection light ray and the earth's surface based on the detector position vector and the direction vector of the detection light ray; determining the coordinates of the intersection point in the geostationary coordinate system based on the detector position vector, the direction vector of the detection light ray and the distance; calculating the zenith angle coordinates and the azimuth angle coordinates of the intersection point based on the coordinates of the intersection point in the geostationary coordinate system; calculating the index coordinates of the intersection point in the terrestrial latitude-longitude grid based on the zenith angle coordinates and the azimuth angle coordinates of the intersection point, and the grid scales in the longitude and latitude directions of the pre-divided terrestrial latitude-longitude grid, to extract the parameter data of the index coordinates from the spatial non-uniform distribution data.

4. The method of claim 1, wherein, The input of the limb detection parameterized model further includes a first detection geometric angle; the first detection geometric angle includes a solar zenith angle, a limb tangent height and a relative azimuth angle; The input of the non-edge detection parameterized model further includes a second detection geometric angle; the second detection geometric angle includes a solar zenith angle, an observation zenith angle and a relative azimuth angle.

5. The method of claim 4, wherein, The second detection geometric angle is calculated by the following method: a solar zenith angle is calculated based on a normal vector at the intersection point of the detection light ray and the earth surface and a solar direction vector; an observation zenith angle is calculated based on a unit vector of the detection direction and the normal vector at the intersection point; a relative azimuth angle is calculated based on a projection vector of the solar direction vector and the unit vector of the detection direction on a tangent plane.

6. The method of claim 5, wherein, The solar direction vector is calculated by the following method: a solar declination is calculated based on a ordinal day; wherein the ordinal day is the number of days from January 1 of the current year to the detection time; a geographic longitude of a solar direct point at the detection time is calculated based on the detection time, a time difference correction term, a standard meridian longitude and a true solar time; a solar direction vector is calculated based on the solar declination and the geographic longitude of the direct point.

7. An apparatus for simulating the distribution characteristics of spatially non-uniform parameter-driven atmospheric light scattering, comprising: The device comprises: a data preparation module for obtaining spatial non-uniform distribution data corresponding to a ground surface latitude and longitude grid; the spatial non-uniform distribution data at least includes ground surface albedo distribution data, aerosol optical thickness distribution data and cloud optical thickness distribution data; a light ray discretization module for establishing a local coordinate system based on a detector position and discretizing detector light rays based on a detection direction to convert to obtain a plurality of detection light ray vectors in a ground-fixed coordinate system; a data extraction module for calculating the spatial relationship between each detection light ray vector and the earth surface and determining a detection mode, and extracting parameter data of a target position from the spatial non-uniform distribution data based on the detection mode; the parameter data includes ground surface albedo, aerosol type, aerosol optical thickness and cloud optical thickness; the detection mode includes an edge detection mode and a non-edge detection mode; a radiance calculation module for inputting the parameter data of the target position into a parameterized model under the detection mode corresponding to the current detection light ray vector for each detection light ray vector to calculate a radiance value, and synthesizing the radiance values corresponding to all detection light ray vectors to generate a ground-atmosphere light scattering distribution characteristic simulation result within the field of view of the detector.

8. A computer device, comprising: The computer device comprises a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program stored on the memory to realize the steps of the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the method of any one of claims 1-6.

10. A computer program product, characterised in that, The computer program is executed by the processor to realize the steps of the method of any one of claims 1-6.

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