Data lossless fusion and aerodynamic optical effect calculation method based on flow field characteristics

Abstract

The invention discloses a data lossless fusion and aero-optical effect calculation method based on flow field characteristics, and belongs to the technical field of aero-optical effect calculation, and the method comprises the steps: constructing a coordinate system based on an optical window and optical calculation parameters; constructing a first layer of optical grid based on a window plane; coordinate transformation of a flow field and a first layer of optical grids; generating optical calculation grid points based on a linear equation and a plane equation; performing interpolation conversion on the flow field data to an optical computational grid; and completing ray tracing and optical function calculation. According to the method, the optical computational grid and data interpolation extraction can be quickly generated with high precision, so that the pneumatic optical effect can be calculated with high precision.

Description

Technical Field

[0001] The present invention belongs to the technical field of aero-optical effect calculation, and in particular to a method for lossless data fusion and aero-optical effect calculation based on flow field characteristics. Background Art

[0002] Aircraft with optical guidance / navigation rely on optical detectors to capture the target's optical signal to identify and track the target and achieve precise guidance. However, during high-speed flight, if the flight speed is high (reaching Mach 5 or above), the air will be strongly compressed, and a gas layer with non-uniform density will be formed in the shock layer, which can be up to ten times higher than the natural atmospheric density (incoming flow), and the temperature in the shock layer can reach hundreds or even thousands of degrees. For optical window glass, the heat flow generated by air friction is conducted inward to form a structural temperature field with non-uniform temperature. The non-uniform density of the shock layer gas and the non-uniform temperature of the window glass will lead to non-uniform changes in the refractive index. When the optical signal passes through these media with non-uniform changes in refractive index, refraction will cause a series of imaging problems. The high-temperature gas in the shock layer and the window glass also generate radiation to form radiation noise. These phenomena are aero-optical effects, including imaging offset, image blur, and reduced signal-to-noise ratio, which make the optical detector unable to see the target clearly, and thus cannot effectively detect and track.

[0003] The aero-optical effect was first discovered in optical measurements of low-speed flows. Aero-optical calculations require the generation of optical calculation grids. Due to the low-speed aero-optical problem, the gas flow is slow and the density gradient changes little. Generally, a grid with a unit of 1mm×1mm×1mm can be generated. For example, 64×64×n is common in the literature, where n is the number of normal grids, which is determined according to the actual thickness of the flow field.

[0004] However, for high-speed or even ultra-high-speed flows, the shock layer is strongly compressed and the density varies greatly, which may differ by several times within 1 mm. In particular, the density between the shock wave front and the incoming flow is strongly discontinuous, that is, the density before and after the wave front differs by several to dozens of times. Obviously, generating an optical calculation grid with a grid scale of 1 mm in the shock layer and extracting density data will cause relatively large errors, which is unacceptable for aerodynamic optical calculations measured in microns. Summary of the invention

[0005] The purpose of the present invention is to overcome the defects of the prior art and provide a method for lossless data fusion and aero-optical effect calculation based on flow field characteristics.

[0006] The object of the present invention is achieved through the following technical solutions: A method for lossless data fusion and aero-optical effect calculation based on flow field characteristics, the method comprising: In response to the read flow field data and the optical window data of the optical system, a coordinate system based on the optical window and optical calculation parameters is constructed; Constructing a first layer of optical grid based on a plane of the optical window, wherein the first layer of optical grid covers the field of view of the optical system; The coordinates of the flow field grid and the first layer of optical grid are transformed so that the incident signal light coincides with the Y axis of the coordinate system and has the opposite direction; In the grid unit surface of the flow field grid and the optical window, search for the nearest grid unit surface, establish the plane equation of the grid unit surface, substitute the intersection point of the signal incident light and the grid unit surface into the plane equation, and obtain the calculation grid point of the second layer optical grid; The flow field data is interpolated and converted to the calculation grid points of the second layer of optical grid until the outermost layer of the flow field grid ends, thus completing the generation of the second layer of optical grid and data interpolation; Ray tracing is done based on the second layer optical grid and data interpolation.

[0007] Furthermore, the method also includes calculating optical functions based on the ray tracing results, and the optical functions include wave phase difference function, pupil function, amplitude distribution function and point spread function.

[0008] Furthermore, a coordinate system based on the optical window and optical calculation parameters takes the lens center point of the optical window as the origin and the normal of the optical window as the Y-axis.

[0009] Furthermore, the micro-element of the first layer of optical grid is 1 mm×1 mm.

[0010] Furthermore, the flow field data is converted to the calculation grid point interpolation of the second layer optical grid specifically including: The inverse distance weighted method is used to interpolate the data and obtain the physical parameters of the intersection point.

[0011] Furthermore, searching for a nearest grid cell surface in the grid cell surface of the flow field grid and the optical window specifically includes: Use vector containers to initialize and store geometric data of flow field grid point sets; Generate a balanced binary tree retrieval structure in recursive mode; The distance from the grid unit surface relative to the optical window to the flow field grid point set is recursively calculated and the nearest point is located.

[0012] The beneficial effects of the present invention are: (1) The present invention transforms the coordinates so that the incident light is in the vertical direction, making it faster to solve the straight line and plane focus according to the analytical geometry equation.

[0013] (2) The optical computational grid generated by the present invention is almost identical to the CFD (Computational Fluid Dynamics) grid in the normal direction, and the distance weighted method is used for interpolation, which well maintains the flow field structure characteristics and data accuracy, and has high interpolation efficiency.

[0014] (3) The flow field data of the present invention determines the optical calculation results. Based on the lossless data fusion of the flow field grid and the optical calculation grid, high-precision aerodynamic-optical correlation function calculation results can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flowchart of a method for lossless data fusion and aero-optical effect calculation based on flow field characteristics according to an embodiment of the present invention; Figure 2 This is an aerodynamic layout diagram of the boss side flat window seeker according to an embodiment of the present invention; Figure 3 Schematic diagram of main technical parameters of the boss side flat window guide head according to an embodiment of the present invention; Figure 4 This is a flow control principle diagram of the boss side flat window guide head according to an embodiment of the present invention; Figure 5 It is a schematic diagram of the traditional method to generate optical calculation grid and interpolation results; Figure 6 It is a schematic diagram of generating an optical calculation grid and interpolation results by the lossless fusion of data based on flow field characteristics and the calculation method of aero-optical effects of the present invention; Figure 7 It is a schematic diagram comparing the center line density of incident light.

[0016] Figure numerals: 1 - ball head structure, 2 - first cone structure, 3 - boss structure, 4 - optical glass mounting mechanism, 5 - optical glass window, 6 - second cone structure. DETAILED DESCRIPTION

[0017] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0018] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0019] For high-speed or even ultra-high-speed flows, the shock layer is strongly compressed and the density varies greatly, which may differ by several times within 1 mm. In particular, the density between the shock wave front and the incoming flow is strongly discontinuous, that is, the density before and after the wave front differs by several to dozens of times. Generating an optical computational grid with a grid scale of 1 mm in the shock layer and extracting density data will cause relatively large errors.

[0020] In order to solve the above technical problems, the following embodiments of the present invention are proposed for lossless data fusion based on flow field characteristics and aero-optical effect calculation methods.

[0021] Example 1 Reference Figure 1 ,like Figure 1 The figure is a flowchart of the method for lossless data fusion and aero-optical effect calculation based on flow field characteristics in this embodiment, which mainly includes the following steps: Step 1: Flow field coordinate transformation.

[0022] The origin of the grid coordinate system used in CFD simulation is generally at the top of the aircraft head. Optical calculations generally treat the optical system as a convex lens imaging system. Therefore, the optical calculation grid of the detector field of view needs to be generated with the center of the lens as the origin (incident center) in the optical window and the normal of the optical window as the symmetry axis to generate an axisymmetric grid. In order to quickly generate the optical calculation grid, the origin of the coordinate system must first be moved to the center of the optical window lens, and the CFD grid must be translated and rotated with the normal of the optical window as the Y axis.

[0023] This step requires inputting the lens center point position parameters and the optical window tilt angle (to find the normal direction).

[0024] Step 2: Generate the first layer of optical computational grid.

[0025] Based on the center point of the optical window plane, a square grid with n×n microelements is generated. n is generally 1mm by default, but it can also be customized. The purpose of generating an optical calculation grid is optical calculation. The grid must cover the field of view of the optical system. Therefore, the total number of grids is determined according to the equivalent parameters of the optical system.

[0026] Due to the axial symmetry or plane symmetry of high-speed aircraft, the high-speed flow shock wave compression flow field has special structural characteristics, that is, the density, temperature, pressure, etc. of the flow field have a large gradient distribution in the normal direction of the aircraft wall, while the gradient is small or even zero along the circumferential direction. Therefore, when generating the optical calculation grid, the first layer of grid scale that coincides with the optical window can meet the requirements when it is 1mm, and it can also be customized as needed. The particularity of the optical calculation grid generation in this patent is mainly for the normal grid.

[0027] Step 3: Coordinate transformation of flow field and first layer optical grid.

[0028] In order to facilitate the rapid generation of the optical grid, the flow field grid needs to be transformed again and rotated according to the incident angle θ of the incident light so that the signal incident light coincides with the Y axis and is in the opposite direction. The first layer of optical calculation grid also performs this step to keep it parallel to the window.

[0029] Step 4: Generate the next layer of optical calculation grid points.

[0030] First, select any grid point P0 of the first layer of optical calculation grid, the coordinates of P0 are x0=a, y0=b, z0=c. Since the normal grid of the grid to be generated is in the vertical direction, its straight line equation is x=a, z=c, and y is a variable; then, adopt a recursive calculation method of the distance from a spatial point to a given point set or a non-recursive calculation method of the distance from a spatial point to a given point set, and quickly search for the nearest grid unit surface S in the grid unit surface relative to the flow field grid and the optical window, take three coordinate data of the four points of the grid unit S, and establish the plane equation; finally, it can be known from the processing of step 3 that the intersection point P2 of the incident light and the S plane equation is x2=a, z2=c, and substitute it into the plane equation to solve y2, so as to complete the point coordinates of the second layer of grid, x2=a, y2=b, z2=c.

[0031] Among them, a recursive calculation method for the distance from a spatial point to a given point set specifically includes the following steps: Step A: Use a vector container to initialize and store the geometric data of a given point set. In the initial stage, assume that The given point set of point elements is , define a A vector container ( ), sequential storage Points The address value is recorded as , where the class describing the point element information contains two basic data: ① The spatial coordinates of the point element, in the form of a double-precision floating-point array The logo, its length and spatial dimension Same;②Point elements in The initial sequence number in the signed integer variable Identification; at a given point set In the example, any two different point elements have different value.

[0032] Step B: Generate a balanced binary tree retrieval structure in a recursive mode. In the current step, you need to All elements in are divided into multiple finite point subsets for storage, and each finite point subset forms a one-to-one mapping relationship with the relevant nodes on the balanced binary tree; among them, the finite point subset contained in each non-terminal node is the union of the finite point subsets contained in its left child and right child nodes, and the finite point subsets contained in the same-level brother nodes do not intersect with each other.

[0033] Furthermore, step B can be divided into the following three sub-steps: Step B1: Set a finite point subset length threshold for a balanced binary tree and use a signed integer member variable If the current node contains a finite number of point subset elements Satisfy the conditions , then the current node is identified as a non-terminal node and needs to continue to perform recursive decomposition; otherwise, the current node is identified as a terminal node. In the embodiment of the present invention, based on the comprehensive consideration of the binary tree height control factor and the local nearest point fast search factor, the setting The value of is 24.

[0034] Step B2: Declare a binary tree recursive generation function without a return type and its parameter list. The binary tree recursive generation function is named , its input parameters are: ① subtree root node (reference pointer transfer);② The node contains the point subset elements in The starting subscript in (Signed integer value transfer); ③ The node contains the point subset elements in The end subscript in (Signed integer value is passed). Therefore, the form of the binary tree recursive generation function is .

[0035] Step B3: Global root node pointer for a balanced binary tree Construct an instantiated object. In the binary tree constructor, the global root node pointer The initial value is the empty address . In the current step, Passed by reference to The first parameter of , at the same time, let and The values ​​are 0 and ( for After executing the related steps B31 to B34, if the condition Established, then Return immediately, otherwise continue to execute step B35 and then return.

[0036] Step B31: Open up dynamic memory to implement the current Object instantiation, and through the node type The assignment operation inside the constructor uses Private member variables of an object , The values ​​of the current binary tree recursive generation function Of , Be consistent.

[0037] Step B32: Follow The current coordinate axis directions are calculated separately The point elements contained in the object (Continuous subscript The range is ) and use signed integer register variables Record the direction number corresponding to the maximum variance.

[0038] Step B33: Along the direction of maximum variance, according to the coordinate components of the point elements The rules from small to large are currently The point element address value contained in the object (Continuous subscript The range is ) to sort. The present invention directly calls the C++ standard template library The generic algorithm completes this sorting process to achieve the optimal combination of quick sort, heap sort and insertion sort, thereby reducing the time cost of recursive construction of a balanced binary tree.

[0039] Step B34: Calculate the root node of the current subtree The upper and lower bounds of the bounding box of the space. coordinate axis directions, respectively calculate the current The point elements contained in the object (Continuous subscript The range is ) The infimum of Supremum , (subscript The range is ). The present invention directly calls the C++ standard template library and The generic algorithm completes this calculation process.

[0040] Step B35: construct subtrees at all levels of the balanced binary tree. In steps B31 to B34, and Identifies the current subtree at a given point sequence The starting and ending range of the point subset involved in . Since in step B33, along the sequence number The maximum variance direction of the subscript The range is The point elements are reordered, so the signed integer register variable is defined For use in sequence Mark the median element on the top. According to step B3, if the condition Established, then call Complete the generation of the next level left subtree and right subtree in sequence, otherwise jump out of the current one directly For the generation of the left subtree, the binary tree recursive generation function The first parameter value is set to the current root node The left child pointer , the second parameter is set to , the third parameter is set to For the generation of the right subtree, the binary tree recursive generation function The first parameter value is set to the current root node The right child pointer , the second parameter is set to , the third parameter is set to .

[0041] Step C: Recursively calculate the distance from the spatial point to the given point set and locate the nearest point. Any point in dimensional space The coordinates of , To a given set of points The square value of the distance uses a double-precision floating-point register variable Storage, whose initial value is a sufficiently large floating-point constant (In the embodiment of the present invention, ). Declare a recursive search function with no return type and its parameter list as , where the double-precision floating-point parameter for The first address of the point coordinate array (constant pointer transfer), The root node address of the current subtree (pointer transfer), double-precision floating-point parameter That is To a given set of points The square value of the distance (reference transfer). In particular, at the initial moment, the global root node pointer of the balanced binary tree is used initialization The second parameter of the function When the parameter transfer is completed, the distance from the spatial point to the given point set can be calculated according to steps B1 to B3 and the nearest point can be located.

[0042] Step C1: If the root node of the current subtree is a non-terminal node, that is The left child pointer of the object and the right child pointer Both exist, then define and initialize two local node pointers as follows: , .

[0043] Calculate separately Point to the nearest node pointer (To a known point The node pointer variable to which the nearer subtree bounding box belongs) and the far node pointer (To a known point The node pointer variable to which the bounding box of the farther subtree belongs) is the square value of the distance between the bounding boxes of the two subtrees of the root node and . Set the near node pointer The corresponding bounding box infra and supremum parameters are and ,at the same time Point at dimension( ) Defined as: If ,So ;if ,So ;if ,So . Further, .Pick The corresponding bounding box infra and supremum parameters of the node, by analogy The calculation process can be obtained If , then exchange and Values ​​and swap and If , then call the recursive function , its three parameters are Point coordinates first address , near node pointer With reference variables .if , then call the recursive function , its three parameters are Point coordinates first address , far node pointer With reference variables .

[0044] Step C2: If the root node of the current subtree is a terminal node, that is The left child pointer of the object and the right child pointer All point to empty address values , then extract the current The object contains the starting and ending range parameters of the given point subset, and stores their values ​​in signed integer register variables and Next, traverse A fragment of a sequence, where the subscript The range is , calculate successively Point to point elements The square of the distance ,if , then The value of is updated to Simultaneously balance the nearest point pointer of a binary tree Point to the current point element The address of.

[0045] Step C3: Return The square root of As a point To a given point set sequence The distance, at this time the nearest point pointer of the balanced binary tree Pointing Distance point in sequence The first address of the most recent element, which can be accessed through the interface function It is noted that, in the implementation of step C1 to step C2 of this embodiment, only the square value of the relevant distance parameter is stored to avoid the influence of frequent square root operations on the computing performance.

[0046] Step D: When the query process is completed, release the dynamic memory opened by the internal members of the balanced binary tree, which are: ① Given point set sequence ② The heap space occupied by each element of the tree is released according to the sequential traversal process of the vector. ② The heap space occupied by each layer of nodes in the balanced binary tree is released according to the pre-order traversal process of the fork tree structure.

[0047] A non-recursive method for calculating the distance from a spatial point to a given point set comprises the following specific steps: For the flow field grid element S, take three point coordinates (x01, x02, x03), (y01, y02, y03), (z01, z02, z03), and calculate the intersection of the plane equation and the straight line as follows: m=(y02-y01)*(z03-z01)-(z02-z01)*(y03-y01); n=(z02-z01)*(x03-x01)-(x02-x01)*(z03-z01); e=(x02-x01)*(y03-y01)-(y02-y01)*(x03-x01); f=-a*x01-b*y01-c*z01; y2=-(m*a+e*c+f) / n.

[0048] Step 5: Perform data interpolation on the generated grid points.

[0049] According to step 4, the coordinates of point P2, the coordinates of the four vertices of the flow field grid surface S and the flow field data are obtained. The inverse distance weighted method is used for data interpolation to obtain the density, temperature, pressure, component mass fraction and other physical parameters of point P2. In order to avoid program errors when 0 is generated in the denominator, ε is introduced, which is generally less than 10 -15 The number of can satisfy: ; By analogy, repeat steps 4 and 5 to generate the second layer according to the optical calculation grid point data of the first layer, until the outermost layer of the CFD grid is reached, completing the generation of the optical calculation grid and data interpolation.

[0050] Step 6: Ray tracing and optical function calculation.

[0051] According to the optical calculation grid and density parameters and component mass fractions obtained in step 5, refractive index field calculation, ray tracing and optical function calculation are performed.

[0052] Calculation model of gas medium refractive index: , K iGD is the refractive index of different gases, ρ i is the gas component density, which is determined by the total gas density and the component mass fraction.

[0053] Ray tracing uses geometric optics or the Runge-Kutta method, the main purpose of which is to calculate the optical path difference OPD: .

[0054] After calculating the optical path difference, the optical function calculation can be performed: Wave phase difference function: ; Pupil function: ; Amplitude distribution function: ; Point spread function: .

[0055] Example 2 This embodiment takes a flat window guide head structure on the side of a boss and an aircraft shape as an example to illustrate the application effect of the present invention. Figure 2-4 , Figure 2 This is the aerodynamic layout diagram of the boss side flat window guide head in this embodiment. In order to ensure the internal installation space of the guide head, a ball head double-cone basic shape is adopted, and the side cutting plane is adopted. In order to ensure the field of view of the detector, a boss structure is designed on the side to increase the window width. The boss side flat window guide head consists of a ball head structure 1, a first cone structure 2, a boss structure 3, an optical glass mounting mechanism 4, an optical glass window 5 and a second cone structure 6. Figure 3 This is a schematic diagram of the main technical parameters of the flat window guide head on the side of the boss in this embodiment. The ball head radius R=22mm, the first cone angle θ1=18°, the first cone length L1=150mm; the second cone angle θ2=12°, the second cone length L2=190mm; the window plane inclination angle θ3=15°, and the second cone end diameter D=210mm. The width of the light-transmitting part of the window is H2=60mm, the overall width of the window is H1=76mm, the window brightness is semicircular, the radius of the light-transmitting part is R2=30mm, the overall radius is R1=38mm, and the middle length of the window is L3=145mm. The coordinates of the incident light of the optical signal take the window plane as the horizontal direction and the window normal as the normal direction. The incident angle θ is the angle between the incident ray of the optical signal and the normal direction. The inclination angle of the guide head outer window is 15°, the forward incident angle limit is 75°, and the effective use is about 30-60°. The optical window glass is sapphire, and the window material is sapphire. Its parameters are: density, 3980kg / m 3 ; Thermal conductivity: 40W / m·k at 25℃; 10W / m·k at 1000℃; Heat capacity: 750J / Kg·k at 25℃; 1256.1 J / Kg·k at 1000℃. Figure 4This is the flow control principle diagram of the flat window guide head on the side of the boss in this embodiment. The high-speed incoming flow forms a shock wave at the head and flows backward. In the horizontal direction, the high-speed airflow is first guided to both sides at the cutting plane boss, and the front edge of the boss of the optical window mounting mechanism can guide the high-speed airflow to both sides for the second time; in the vertical direction, expansion separation occurs at the first cone cutting plane, and the secondary expansion separation and diversion occurs at the front edge of the optical glass mounting mechanism, so that a relatively low local pressure, density, and temperature area is formed above the optical window, and the window is also kept away from the high-temperature area of ​​the shock wave layer. The internal optical system can be equivalent to a convex lens focusing system. According to the optical calculation of the present invention, the radius of the equivalent convex lens is 30 mm and the focal length is 120 mm.

[0056] The calculation altitude of this embodiment is 40 km, the flight Mach number is 10, and the calculation adopts a 7-component chemical reaction model and a laminar flow field.

[0057] The conventional method generates a grid, the incident angle of the light is 0 degrees (i.e. perpendicular to the window), and the grid of the flow field calculation near the wall is denser in order to better capture the flow characteristics. From the normal to the outside, the closer to the atmosphere, the lower the flow velocity, and the sparser the grid can meet the simulation requirements. The normal grid is 61, and the optical calculation grid generated by the conventional method has a grid point number of 65×65×101 (the actual size is 64mm×64mm×100mm). Near the wall, a grid spans several layers of flow field grids, and in order to cover the flow field range, the grid points are taken as 101. Using traversal search to determine the grid point position, serial calculation interpolation takes about 68 hours.

[0058] The method provided in the aforementioned embodiment generates an optical calculation grid with a light incident angle of 0 degrees. The generated grid completely coincides with the flow field grid normal, and the number of grid points is 65×65×61 (the normal is consistent with the flow field grid number). In addition, the grid point positions are determined when the grid is generated, and interpolation is performed directly in less than 40 seconds.

[0059] Reference Figure 5 ,like Figure 5 The figure shows a schematic diagram of the traditional method for generating optical computing grids and interpolation results. The figure gives the interpolation results of the traditional optical computing grid generation. The thin solid lines are the optical computing grid density contour lines, and the thick dotted lines are the flow field density contour lines. It can be seen that there are obvious differences in some areas.

[0060] Reference Figure 6 ,like Figure 6 The figure shows a schematic diagram of generating an optical calculation grid and interpolation results based on lossless data fusion of flow field characteristics and aero-optical effect calculation method. The thin solid lines are optical calculation grid density contour lines, and the thick dotted lines are flow field density contour lines. It can be seen that the density interpolation results completely coincide with the flow field.

[0061] Reference Figure 7 ,like Figure 7 The figure shows a schematic diagram of the comparison of the centerline density of the incident light. CFD is the flow field data. It can be seen that the density interpolation result of the new method provided in the above embodiment completely coincides with the flow field data, with almost no loss of accuracy, while the traditional method has obvious differences near the wall and other positions in the shock layer. At the wall L=0.5mm, (the value obtained by the drawing software) the flow field calculation density is: 0.027766636763219603, the interpolation result of the above embodiment method is: 0.027766636359310693, and the result of the traditional method is: 0.056364779498153411. After taking eight significant digits, the interpolation result of the above embodiment method is: 0.02776664, and the traditional method is 0.05636478.

[0062] In aero-optical calculations, the basic data for calculating optical functions are flow field parameters, that is, the flow field data determine the results of optical calculations. If there are large errors in data interpolation conversion, errors will also be caused in optical calculations, resulting in inaccurate and unreliable aero-optical calculations.

[0063] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for lossless data fusion and aero-optical effect calculation based on flow field characteristics, characterized in that: The method comprises: In response to the read flow field data and the optical window data of the optical system, a coordinate system based on the optical window and optical calculation parameters is constructed; Constructing a first layer of optical grid based on a plane of the optical window, wherein the first layer of optical grid covers the field of view of the optical system; The coordinates of the flow field grid and the first layer of optical grid are transformed so that the incident signal light coincides with the Y axis of the coordinate system and has the opposite direction; In the grid unit surface of the flow field grid opposite to the optical window, search for the nearest grid unit surface, establish the plane equation of the grid unit surface, substitute the intersection point of the signal incident light and the grid unit surface into the plane equation, and obtain the calculation grid point of the second layer optical grid; The flow field data is interpolated and converted to the calculation grid points of the second layer of optical grid until the outermost layer of the flow field grid ends, thus completing the generation of the second layer of optical grid and data interpolation; Ray tracing is done based on the second layer optical grid and data interpolation.

2. The method for lossless data fusion and aero-optical effect calculation based on flow field characteristics according to claim 1, characterized in that: The method also includes calculating optical functions according to the ray tracing results, and the optical functions include wave phase difference function, pupil function, amplitude distribution function and point spread function.

3. The method for lossless data fusion and aero-optical effect calculation based on flow field characteristics according to claim 1, characterized in that: The coordinate system based on the optical window and optical calculation parameters takes the lens center point of the optical window as the origin and the normal line of the optical window as the Y-axis.

4. The method for lossless data fusion and aero-optical effect calculation based on flow field characteristics according to claim 1, characterized in that: The microelement of the first layer of optical grid is 1mm×1mm.

5. The method for lossless data fusion and aero-optical effect calculation based on flow field characteristics according to claim 1, characterized in that: The interpolation conversion of flow field data to the computational grid points of the second layer optical grid specifically includes: The inverse distance weighted method is used to interpolate the data and obtain the physical parameters of the intersection point.

6. The method for lossless data fusion and aero-optical effect calculation based on flow field characteristics according to claim 1, characterized in that: In the mesh cell surface of the flow field mesh and the optical window, searching for the nearest mesh cell surface specifically includes: Use vector containers to initialize and store geometric data of flow field grid point sets; Generate a balanced binary tree retrieval structure in recursive mode; The distance from the grid unit surface relative to the optical window to the flow field grid point set is recursively calculated and the nearest point is located.

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