A method and apparatus for analyzing flutter imaging in space cameras

Abstract

This invention discloses a method and apparatus for analyzing flutter imaging in space cameras. The method includes: acquiring lens parameters, three-dimensional model information, and material property information of a space optical camera; performing finite element modeling on the three-dimensional model information and material property information of the space optical camera to obtain a structural finite element model of the space optical camera; the structural finite element model includes node positions, node structures, and inter-node connection relationships; performing flutter imaging analysis on the structural finite element model to obtain space camera flutter imaging analysis results; the space camera flutter imaging analysis results are used to characterize the impact of flutter on the image sharpness of the space camera. This invention comprehensively considers multiple professional fields such as optics, mechanics, and information in the space camera flutter imaging analysis process, and compared with single-professional analysis, it can obtain more accurate flutter impact analysis results.

Description

Technical Field

[0001] This invention relates to the field of space remote sensing imaging simulation, and specifically to a method and apparatus for analyzing space camera flutter imaging. Background Technology

[0002] During its operation in orbit, a space camera is affected by the wide-bandwidth, low-amplitude reciprocating motion generated by other components. This high-frequency flutter is characterized by its minute size, inherent nature, and difficulty in control. Its minute size refers to the low energy of the flutter, which does not damage the structure; its inherent nature is determined by the flutter excitation source and design parameters; and its difficulty in control refers to the small amplitude, wide bandwidth, and multiple mode overlap of the flutter, making it difficult to measure in orbit. As the performance requirements for high-resolution Earth observation, such as MTF and resolution, become increasingly stringent, it is necessary to simulate and analyze the impact of flutter on the imaging quality of the space camera, thereby guiding camera design and ground image processing.

[0003] Classical optomechanical integration analysis typically employs frequency response analysis, starting with structural model stress analysis to transfer dizziness to optics, analyzing optical axis pointing stability (LOS), and then calculating the MTF of the optical system to analyze the impact of dizziness on camera imaging. This approach does not consider the impact of dizziness on the detector and the final image, making it impossible to predict and evaluate image quality. Therefore, it is necessary to research and implement a simulation method that considers the entire dizziness transmission chain from the excitation source to the image, enabling integrated optomechanical information analysis of dizziness. Summary of the Invention

[0004] This invention primarily addresses the problem that existing technologies have not achieved end-to-end simulation of the impact of flutter on the imaging quality of space cameras, and provides a method and apparatus for analyzing space camera flutter imaging.

[0005] In a first aspect, this application discloses a method for analyzing flutter imaging in a space camera, comprising:

[0006] S1, acquire the lens parameters, 3D model information, and material property information of the space optical camera; the 3D model information of the space optical camera includes the position and connection relationship of each module of the space optical camera; the space optical camera includes a fixed bracket, a lens, and a focal plane; the fixed bracket is used to fix and install the lens and the focal plane; the lens includes several mirror surfaces;

[0007] S2, perform finite element modeling on the three-dimensional model information and material property information of the space optical camera to obtain the structural finite element model of the space optical camera; the structural finite element model includes node positions, node structures and connection relationships between nodes; the nodes are extracted from each module of the space optical camera;

[0008] S3, perform flutter imaging analysis on the finite element model of the structure to obtain the flutter imaging analysis results of the space camera; the flutter imaging analysis results of the space camera are used to characterize the impact of flutter on the image sharpness of the space camera.

[0009] The flutter imaging analysis of the finite element model of the structure yields flutter imaging analysis results from the space camera, including:

[0010] S31, Obtain excitation source information; the excitation source information is a time-domain function of the force that perturbs the space optical camera.

[0011] S32, using the excitation source information, perform mechanical perturbation processing on the structural finite element model to obtain the three-dimensional displacement of all nodes of the structural finite element model;

[0012] S33, perform image principal point image displacement calculation on the three-dimensional displacement of all nodes of the finite element model of the structure to obtain the image principal point image displacement time domain curve information;

[0013] S34, perform flutter imaging calculation processing on the image shift time-domain curve information of the principal point to obtain the flutter imaging analysis result information of the space camera.

[0014] The process of calculating the image displacement of principal points on the three-dimensional displacement of all nodes in the finite element model of the structure to obtain the time-domain curve information of the image displacement of principal points includes:

[0015] S331, compare the three-dimensional displacements of all nodes in the finite element model of the structure with the node positions of the finite element model of the structure to obtain the surface shape change information of the mirror.

[0016] S332, Perform standard Zenik polynomial fitting on the surface shape change information of the mirror and the lens parameters of the space optical camera to obtain standard Zenik polynomial coefficients; use the standard Zenik polynomial coefficients to construct a standard Zenik polynomial;

[0017] S333, perform ray tracing processing on the standard Zenik polynomial and the lens parameters of the space optical camera to obtain the image shift of the principal point; the principal point is the intersection of the optical axis of the space optical camera and the focal plane;

[0018] S334, Repeat steps S331 to S333 at all sampling times within the duration of the excitation source information to obtain the image shift value of the principal point at all sampling times;

[0019] S335: For all sampling times of the principal point, the image shift values ​​are merged according to the order of their sampling times to obtain the image shift time-domain curve information of the principal point.

[0020] The flutter imaging calculation processing of the image principal point image shift time-domain curve information to obtain space camera flutter imaging analysis results includes:

[0021] S341, The duration of the excitation source information is evenly divided to obtain several integration time periods;

[0022] S342, within each integration time period, the first diffusion model is used to calculate and process the image shift time-domain curve information of the principal image point to obtain the image shift point diffusion function value of the integration time period;

[0023] S343, within each integration time period, the second diffusion model is used to calculate and process the image shift time-domain curve information of the principal image point to obtain the image integration point diffusion function value of the integration time period;

[0024] S344, within each integration time period, the third diffusion model is used to calculate and process the image principal point image shift point diffusion function value and the image integration point diffusion function value of the integration time period to obtain the flutter point diffusion function value of the integration time period.

[0025] S345, the average value of all flutter point spread function values ​​in each integration time period is accumulated to obtain the total point spread function value of the integration time period;

[0026] S346 performs frequency domain transformation on the total point spread function values ​​for all integration time periods to obtain the flutter imaging analysis results of the space camera.

[0027] The first diffusion model is calculated as follows:

[0028]

[0029]

[0030] Where a and c are preset calculation factors, PSF si (x, y) represents the image shift point spread function value of the image point with coordinates (x, y) at the i-th sampling time within a certain integration time interval, (dx i ,dy i ) represents the value of the image shift time-domain curve information of the principal point at the i-th sampling time within the integration period.

[0031] The second diffusion model is calculated as follows:

[0032]

[0033]

[0034]

[0035] Among them, PSF ti (x, y) represents the image integration point spread function value of the image point with coordinates (x, y) at the i-th sampling time within a certain integration time interval, (dx) i ,dy i ) represents the value of the image shift time-domain curve information of the principal point at the i-th sampling time within the integration period. Let be the absolute value of the image shift of the principal point at the i-th sampling time, and rect() be the rectangle function.

[0036] The calculation expression for the third diffusion model is as follows:

[0037] PSF fi (x,y)=PSF si (x,y)*PSF ti (x,y),

[0038] Where * represents convolution operation, PSF fi (x,y) represents the flutter point spread function value of the image point with coordinates (x,y) at the i-th sampling time within a certain integration time interval.

[0039] In a second aspect of this embodiment, a space camera flutter imaging analysis device is disclosed, the device comprising:

[0040] Memory containing executable program code;

[0041] A processor coupled to the memory;

[0042] The processor calls the executable program code stored in the memory to execute the space camera flutter imaging analysis method.

[0043] In a third aspect of this embodiment, a computer-storable medium is disclosed, wherein the computer-storable medium stores computer instructions, and when the computer instructions are invoked, they are used to execute the space camera flutter imaging analysis method.

[0044] In a fourth aspect of this application, an information data processing terminal is disclosed, which is used to implement the space camera flutter imaging analysis method.

[0045] The beneficial effects of this invention are as follows:

[0046] The flutter imaging analysis process of space cameras in this invention comprehensively considers multiple professional fields such as optics, mechanics and information. Compared with analysis of individual professional fields, it can take into account the coupling factors between multiple professional fields and obtain more accurate flutter effect analysis results.

[0047] Compared with previous flutter frequency response analysis, this invention extends to the field of image processing, realizing end-to-end flutter imaging analysis from excitation source to image;

[0048] The flutter point spread function value of the image calculated by this invention can be used to directly analyze the impact of flutter imaging on image quality, predict the flutter imaging quality of space optical cameras, and serve as a basis for evaluating the flutter suppression and image stabilization control of space optical cameras. Attached Figure Description

[0049] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention. Detailed Implementation

[0050] To better understand the content of this invention, an embodiment is provided here.

[0051] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention.

[0052] In a first aspect, this application discloses a method for analyzing flutter imaging in a space camera, comprising:

[0053] S1, acquire the lens parameters, 3D model information, and material property information of the space optical camera; the 3D model information of the space optical camera includes the position and connection relationship of each module of the space optical camera; the space optical camera includes a fixed bracket, a lens, and a focal plane; the fixed bracket is used to fix and install the lens and the focal plane; the lens includes several mirror surfaces;

[0054] The three-dimensional model of the space optical camera information is obtained by performing a three-dimensional description of the space optical camera information, which can be obtained using CAD.

[0055] S2, finite element modeling is performed on the 3D model information and material property information of the space optical camera to obtain the structural finite element model of the space optical camera; the structural finite element model includes node positions, node structures, and connection relationships between nodes; the node structure includes the size and positional relationships of the hexahedrons or tetrahedrons contained in the module corresponding to the node. The nodes are obtained by extracting each module of the space optical camera. The extraction involves using the geometric center or centroid of the module as the node.

[0056] S3, perform flutter imaging analysis on the finite element model of the structure to obtain the flutter imaging analysis results of the space camera; the flutter imaging analysis results of the space camera are used to characterize the impact of flutter on the image sharpness of the space camera.

[0057] The S3 includes:

[0058] S31, Obtain excitation source information; the excitation source information is a time-domain function of the force that perturbs the space optical camera.

[0059] S32, using the excitation source information, perform mechanical perturbation processing on the structural finite element model to obtain the three-dimensional displacement of all nodes of the structural finite element model;

[0060] S33, perform image principal point image displacement calculation on the three-dimensional displacement of all nodes of the finite element model of the structure to obtain the image principal point image displacement time domain curve information;

[0061] S34, perform flutter imaging calculation processing on the image shift time-domain curve information of the principal point to obtain the flutter imaging analysis result information of the space camera.

[0062] The process of calculating the image displacement of principal points on the three-dimensional displacement of all nodes in the finite element model of the structure to obtain the time-domain curve information of the image displacement of principal points includes:

[0063] S331, compare the three-dimensional displacements of all nodes in the finite element model of the structure with the node positions of the finite element model of the structure to obtain the surface shape change information of the mirror.

[0064] The mechanical perturbation process is performed on the finite element model of the structure to obtain the three-dimensional displacements of all nodes of the finite element model of the structure. This can be obtained by collecting the three-dimensional displacements of the nodes after applying excitation source information to the simulation of the finite element model of the structure in MSC.Patran software.

[0065] The surface shape change information of the mirror is obtained by comparing the three-dimensional displacements of all nodes in the finite element model of the structure with the node positions of the finite element model of the structure. This can be done using Sigfit software.

[0066] S332, Perform standard Zenik polynomial fitting on the surface shape change information of the mirror and the lens parameters of the space optical camera to obtain standard Zenik polynomial coefficients; use the standard Zenik polynomial coefficients to construct a standard Zenik polynomial;

[0067] S333, perform ray tracing processing on the standard Zenik polynomial and the lens parameters of the space optical camera to obtain the image shift of the principal point; the principal point is the point on the focal plane of the optical axis of the space optical camera.

[0068] S334, Repeat steps S331 to S333 at all sampling times within the duration of the excitation source information to obtain the image shift value of the principal point at all times;

[0069] S335: The image shift values ​​of the principal point at all times are merged according to the order of time to obtain the image shift time-domain curve information of the principal point.

[0070] All sampling moments within the duration of the excitation source information can be: the duration of the excitation source information includes several sampling moments, and steps S331 to S333 are repeated for all the included sampling moments; for example, if the duration of the excitation source information is [0,10] s and the sampling interval is 1 s, then the sampling moments include 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10.

[0071] The image shift time-domain curve information of the principal point includes the sampling time and the image shift value of the principal point at that time;

[0072] The lens parameters of the space optical camera include focal length, aperture number, relative aperture, outer diameter, length, material, spherical aberration, distortion, and transmittance.

[0073] The ray tracing process is implemented using a ray tracing algorithm;

[0074] The ray tracing algorithm includes:

[0075] Light is generated by obtaining the line of sight and its origin based on the camera's position and the lens parameters of the spatial optical camera.

[0076] When light rays intersect, find the nearest object that intersects with the camera's line of sight, and determine the point of intersection of the line of sight corresponding to the nearest object on the focal plane;

[0077] The object is colored by calculating the grayscale of the intersection of the lines of sight using the standard Zenik polynomial.

[0078] The surface shape change information of the mirror can be obtained through the three-dimensional displacement of all nodes of the structural finite element model and the Euclidean distance between the node positions of the structural finite element model.

[0079] The surface shape change information of the mirror is used as wave phase difference and is subjected to standard Zener polynomial fitting with the lens parameters of the space optical camera to obtain the parameters of the Zener polynomial.

[0080] The standard Zeniko polynomial fitting process can be implemented using the least squares Zeniko coefficient fitting algorithm.

[0081] The flutter imaging calculation processing of the image principal point image shift time-domain curve information to obtain space camera flutter imaging analysis results includes:

[0082] S341, The duration of the excitation source information is evenly divided to obtain several integration time periods;

[0083] S342, within each integration time period, the first diffusion model is used to calculate and process the image shift time-domain curve information of the principal image point to obtain the image shift point diffusion function value of the integration time period;

[0084] S343, within each integration time period, the second diffusion model is used to calculate and process the image shift time-domain curve information of the principal image point to obtain the image integration point diffusion function value of the integration time period;

[0085] S344, within each integration time period, the third diffusion model is used to calculate and process the image principal point image shift point diffusion function value and the image integration point diffusion function value of the integration time period to obtain the flutter point diffusion function value of the integration time period.

[0086] S345, the average value of all flutter point spread function values ​​in each integration time period is accumulated to obtain the total point spread function value of the integration time period;

[0087] S346 performs frequency domain transformation on the total point spread function values ​​for all integration time periods to obtain the flutter imaging analysis results of the space camera.

[0088] The first diffusion model is calculated as follows:

[0089]

[0090]

[0091] Where a and c are preset calculation factors, PSF si (x, y) represents the image shift point spread function value of the image point with coordinates (x, y) at the i-th sampling time within a certain integration time interval, (dx i ,dy i ) represents the value of the image shift time-domain curve information of the principal point at the i-th sampling time within the integration period.

[0092] The coordinates (x, y) are the coordinates of the image point on the image plane in the two-dimensional coordinate system on the focal plane.

[0093] The second diffusion model is calculated as follows:

[0094]

[0095]

[0096]

[0097] Among them, PSF ti(x, y) represents the image integration point spread function value of the image point with coordinates (x, y) at the i-th sampling time within a certain integration time interval, (dx) i ,dy i ) represents the value of the image shift time-domain curve information of the principal point at the i-th sampling time within the integration period. Let be the absolute value of the image shift of the principal point at the i-th sampling time, and rect() be the rectangle function.

[0098] The calculation expression for the third diffusion model is as follows:

[0099] PSF fi (x,y)=PSF si (x,y)*PSF ti (x,y),

[0100] Where * represents convolution operation, PSF fi (x,y) represents the flutter point spread function value of the image point with coordinates (x,y) at the i-th sampling time within a certain integration time interval.

[0101] The process of accumulating and averaging all flutter point spread function values ​​for each integration time period to obtain the total point spread function value for that integration time period includes:

[0102]

[0103] Among them, PSF n (x,y) represents the total point spread function value of the image point with coordinates (x,y) in the nth integration time interval, where N is the total number of sampling times contained in an integration time interval.

[0104] The frequency domain transformation of the total point spread function values ​​for all integration time periods yields the space camera flutter imaging analysis results, including:

[0105] For the total point spread function value at each integration time interval, a two-dimensional Fourier transform is performed to obtain the image frequency domain spread function value. This image frequency domain spread function value is determined as the space camera flutter imaging analysis result information for that integration time interval. The space camera flutter imaging analysis result information for all integration time intervals is merged to obtain the space camera flutter imaging analysis result information. Here, the image frequency domain flutter imaging analysis result is used to characterize the space camera flutter imaging analysis result information.

[0106] The frequency domain transformation of the total point spread function values ​​for all integration time periods yields the space camera flutter imaging analysis results, including:

[0107] For the total point spread function value of each integration time period, a two-dimensional Fourier transform is performed to obtain the image frequency domain spread function value. The image frequency domain spread function value is determined as the spatial camera flutter imaging analysis result information for the integration time period.

[0108] Feature fusion processing is performed on the space camera flutter imaging analysis results for each integration time period to obtain the space camera flutter imaging analysis results.

[0109] The space camera flutter imaging analysis results for each integration time period are subjected to feature fusion processing to obtain the space camera flutter imaging analysis results, including:

[0110] S3461, perform cross-correlation calculation on the space camera flutter imaging analysis results for each integration time period to obtain the cross-correlation matrix R for the integration time period; i，j Let r represent the element in the i-th row and j-th position of the cross-correlation matrix R. i，j The calculation expression is:

[0111] r i，j =E(e i e j ),

[0112] Where E() represents the mean, e i e represents the spatial camera flutter imaging analysis result information at the i-th sampling time of a certain integration period. j This represents the spatial camera flutter imaging analysis result information at the j-th sampling time of a certain integration period;

[0113] S3462, For each integration time interval, the cross-correlation value is normalized to obtain a normalized correlation value sequence for each integration time interval; the expression for the normalization calculation of the cross-correlation value is:

[0114]

[0115] in, This represents the j-th value of the normalized correlation value sequence at the i-th and j-th sampling times within a certain integration time interval;

[0116] S3463, perform logarithmic summation on the normalized correlation value sequence for each integration time period to obtain the uncertainty value for each integration time period;

[0117] The calculation expression for the logarithmic summation process is as follows:

[0118]

[0119] Among them, H i Let be the uncertainty value at the i-th sampling time within a certain integration period;

[0120] S3464, the uncertainty value of each integration time period is normalized by angle to obtain the characteristic value of each integration time period;

[0121] The calculation expression for the angle normalization process is:

[0122]

[0123] in, The feature value of the i-th sampling time within a certain integration time period;

[0124] S3465: Using the characteristic values ​​of the integration time interval, the space camera flutter imaging analysis results of each integration time interval are weighted and summed to obtain the space camera flutter imaging analysis results.

[0125] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for analyzing flutter imaging in a space camera, characterized in that, include: S1, acquire the lens parameters, 3D model information and material property information of the space optical camera; The three-dimensional model information of the space optical camera includes the position and connection relationship of each module of the space optical camera; the space optical camera includes a fixed bracket, a lens and a focal plane; the fixed bracket is used to fix and install the lens and the focal plane; the lens includes several mirror surfaces; S2, perform finite element modeling on the three-dimensional model information and material property information of the space optical camera to obtain the structural finite element model of the space optical camera; the structural finite element model includes node positions, node structures and connection relationships between nodes; the nodes are extracted from each module of the space optical camera; S3, perform flutter imaging analysis on the finite element model of the structure to obtain the flutter imaging analysis results of the space camera, including: S31, Obtain excitation source information; the excitation source information is a time-domain function of the force that perturbs the space optical camera. S32, using the excitation source information, perform mechanical perturbation processing on the structural finite element model to obtain the three-dimensional displacement of all nodes of the structural finite element model; S33, perform image principal point image displacement calculation on the three-dimensional displacement of all nodes in the finite element model of the structure to obtain the image principal point image displacement time-domain curve information, including: S331, compare the three-dimensional displacements of all nodes in the finite element model of the structure with the node positions of the finite element model of the structure to obtain the surface shape change information of the mirror. S332, Perform standard Zenik polynomial fitting on the surface shape change information of the mirror and the lens parameters of the space optical camera to obtain standard Zenik polynomial coefficients; use the standard Zenik polynomial coefficients to construct a standard Zenik polynomial; S333, perform ray tracing processing on the standard Zenik polynomial and the lens parameters of the space optical camera to obtain the image shift of the principal point; the principal point is the intersection of the optical axis of the space optical camera and the focal plane; S334, Repeat steps S331 to S333 at all sampling times within the duration of the excitation source information to obtain the image shift value of the principal point at all sampling times; S335, the image shift values ​​of all sampling times of the principal point are merged according to the order of their sampling times to obtain the image shift time domain curve information of the principal point; S34, perform flutter imaging calculation processing on the image shift time-domain curve information of the principal point to obtain the flutter imaging analysis result information of the space camera; The flutter imaging analysis results of the space camera are used to characterize the impact of flutter on the image sharpness of the space camera.

2. The space camera flutter imaging analysis method as described in claim 1, characterized in that, The flutter imaging calculation processing of the image principal point image shift time-domain curve information to obtain space camera flutter imaging analysis results includes: S341, The duration of the excitation source information is evenly divided to obtain several integration time periods; S342, within each integration time period, the first diffusion model is used to calculate and process the image shift time-domain curve information of the principal image point to obtain the image shift point diffusion function value of the integration time period; S343, within each integration time period, the second diffusion model is used to calculate and process the image shift time-domain curve information of the principal image point to obtain the image integration point diffusion function value of the integration time period; S344, within each integration time period, the third diffusion model is used to calculate and process the image principal point image shift point diffusion function value and the image integration point diffusion function value of the integration time period to obtain the flutter point diffusion function value of the integration time period. S345, the average value of all flutter point spread function values ​​in each integration time period is accumulated to obtain the total point spread function value of the integration time period; S346 performs frequency domain transformation on the total point spread function values ​​for all integration time periods to obtain the flutter imaging analysis results of the space camera.

3. The space camera flutter imaging analysis method as described in claim 2, characterized in that, The first diffusion model is calculated as follows: Where a and c are preset calculation factors, PSF si (x, y) represents the image shift point spread function value of the image point with coordinates (x, y) at the i-th sampling time within a certain integration time interval, (dx i ,dy i ) represents the value of the image shift time-domain curve information of the principal point at the i-th sampling time within the integration period.

4. The space camera flutter imaging analysis method as described in claim 2, characterized in that, The second diffusion model is calculated as follows: Among them, PSF ti (x, y) represents the image integration point spread function value of the image point with coordinates (x, y) at the i-th sampling time within a certain integration time interval, (dx) i ,dy i ) represents the value of the image shift time-domain curve information of the principal point at the i-th sampling time within the integration period. Let be the absolute value of the image shift of the principal point at the i-th sampling time, and rect() be the rectangle function.

5. The space camera flutter imaging analysis method as described in claim 2, characterized in that, The calculation expression for the third diffusion model is as follows: PSF fi (x,y)=PSF si (x,y)*PSF ti (x,y), Where * represents convolution operation, PSF fi (x,y) represents the flutter point spread function value of the image point with coordinates (x,y) at the i-th sampling time within a certain integration time interval.

6. A space camera flutter imaging analysis device, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the space camera flutter imaging analysis method as described in any one of claims 1 to 5.

7. A computer-storable medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the space camera flutter imaging analysis method as described in any one of claims 1 to 5.

8. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the space camera flutter imaging analysis method as described in any one of claims 1 to 5.

Images