Based on the Karman’s equation for circular thin plate and Qian’s theory of membrane, the membrane mirror forming theory model is established. The effect of the high order disturbance for the shape of the membrane mirror is reduced by the way of variable thickness, so that the shape of the membrane is parabolic. The finite element method is used to verify the theory of the membrane mirror forming model. But the analysis results are not easy to convergence due to the flexibility characteristics of the membrane. So the reasonable solution parameters are necessary to ensure the correction of the finite element analysis result. The results show that the deviation between the finite element analysis and the theoretical results is small. The uniform thickness deviation is 0.73%, and the variable thickness deviation is 1.30%, thus the validity of the theoretical model is guaranteed. Then the membrane mirror design and optimization method is established on the basis of the theoretical model. Compare the theoretical surface and the optical design surface, and set the minimum root mean square error between the theoretical and the optical design surface as the optimization goal. The original shape and the surface shape control parameters of the membrane are optimized by using genetic algorithm. Finally, get the optimization model which can be used to optimize membrane mirror with any diameter. The genetic algorithm was used to optimize the thickness, boundary condition and the uniform loads. The result of membrane mirror accuracy is λ/4(λ=10um), which indicates that this membrane mirror can be applied in the infrared wavelength range for imaging. The main optimizing parameters are the variable thickness of the membrane, the boundary conditions and the surface loads. Finally, the optimization result of the membrane is the RMS<λ/4(λ=10μm), which indicates that the membrane can be used to long-wave infrared optical system. Based on the theory of mechanics of materials, this paper establishes a theoretical model and analyzes the relationship between the inflatable membrane mirror and the boundary conditions as well as the gas load. And the optimization design method is carried out for space-based optical applications. The model and method established in this paper is of great significance for the design and application of large optical payload based on the membrane mirror.
A model as well as the methodology is proposed to analyze the cryogenic performance of space infrared optical payload. And the model is established from two aspects: imaging quality and background radiation. On the basis of finite element analysis, the deformation of optical surface in cryogenic environment is characterized by Zernike polynomials, and then, the varying pattern of MTF of space cryogenic optical payload could be concluded accordingly. Then from the theory of thermal radiative transfer, the temperature distribution and the deformation of the optical payload under the action of inertial load and thermal load are analyzed based on the finite element method, and the spontaneous radiation and scattering properties of the optical surface and shielding factors between the opto-mechanical structure are considered to establish the radiation calculation model. Furthermore, the cryogenic radiation characteristics of the space infrared optical payload are obtained by the radiation calculation model. Finally, experiments are conducted using an actual off-axis TMA space infrared optical payload. And the results indicate that the background radiation of the space infrared optical payload is decreased by 79% while 33% for MTF at the thermal control temperature of 240K. In this circumstance, the system background radiation is effectively suppressed and the detection sensitivity of the optical payload is improved as well, while the imaging quality is acceptable. The model proposed in this paper can be applied to the analyzing cryogenic properties of space infrared optical payload, and providing theoretical guidance for the design and application of the space cryogenic optical payload.
We propose an in-orbit modulation transfer function (MTF) statistical estimation algorithm based on natural scene, called SeMTF. The algorithm can estimate the in-orbit MTF of a sensor from an image without specialized targets. First, the power spectrum of a satellite image is analyzed, then a two-dimensional (2-D) fractal Brownian motion model is adopted to represent the natural scene. The in-orbit MTF is modeled by a parametric exponential function. Subsequently, the statistical model of satellite imaging is established. Second, the model is solved by the improved profile-likelihood function method. In order to handle the nuisance parameter in the profile-likelihood function, we divided the estimation problem into two minimization problems for the parameters of the MTF model and nuisance parameters, respectively. By alternating the two iterative minimizations, the result will converge to the optimal MTF parameters. Then the SeMTF algorithm is proposed. Finally, the algorithm is tested using real satellite images. Experimental results indicate that the estimation of MTF is highly accurate.
In order to meet the requirements of identification of satellite local targets, a new method based on combined feature
metrics is proposed. Firstly, the geometric features of satellite local targets including body, solar panel and antenna are
analyzed respectively, and then the cluster of each component are constructed based on the combined feature metrics of
mathematical morphology. Then the corresponding fractal clustering criterions are given. A cluster model is established,
which determines the component classification according to weighted combination of the fractal geometric features. On
this basis, the identified targets in the satellite image can be recognized by computing the matching probabilities between
the identified targets and the clustered ones, which are weighted combinations of the component fractal feature metrics
defined in the model. Moreover, the weights are iteratively selected through particle swarm optimization to promote
recognition accuracy. Finally, the performance of the identification algorithm is analyzed and verified. Experimental
results indicate that the algorithm is able to identify the satellite body, solar panel and antenna accurately with
identification probability up to 95%, and has high computing efficiency. The proposed method can be applied to identify
on-orbit satellite local targets and possesses potential application prospects on spatial target detection and identification.
A new method is proposed to solve the problem of image restoration of high resolution TDICCD camera due to satellite
vibrations, which considers image blur and irregular sampling geometric quality degradation simultaneously. Firstly, the
image quality degradation process is analyzed according to imaging characteristics of TDICCD camera, owing to image
motions during TDICCD integration time induced by satellite vibrations. In addition, the vibration simulation model is
established, and the irregular sampling degradation process of geometric quality is mathematically modeled using
bicubic Hermite interpolation. Subsequently, a full image degradation model is developed combined with blurred and
noisy degradation process. On this basis, a new method of image restoration is presented, which can implement not only
deblurring but also irregular to regular sampling. Finally, the method is verified using real remote sensing images, and
compared with the recent restoration methods. Experimental results indicate that the proposed method performs well,
and the Structural Similarity between the restored and ideal images are greater than 0.9 in the case of seriously blurred,
irregularly sampled and noisy images. The proposed method can be applied to restore high resolution on-orbit satellite
With the aperture of telescope becoming larger, the mass of primary mirror and other relevant structures will become
heavier as well. Therefore, lighting weight for large space-based telescope is necessary. This paper purposed a method
based on Neural Network aims to build a math model for primary mirror of large space-based telescope, which can
reduce weight of the telescope and smaller mirror deformation caused by gravity release effectively. In the meantime, it
can also improve stiffness of structure and reduce thermal strain caused by on orbit temperature variation effectively. The
model describes the relationship between the structure of primary mirror of large space-based telescope and
corresponding deformation, and describes the optical performance of mirror by using Zernike Polynomial. To optimize
the structure of primary mirror lightweight, we take the deformation of mirror and its optical performance into
consideration. To apply the structures parameters and its corresponding deformations to Neural Network training, we use
the combination samples of different mirror lightweight structure parameters and corresponding deformation which
caused by gravity release and thermal condition. Finally, by taking advantage of the Neural Network model to optimize
the primary mirror lightweight of 1-meter rectangle space-based telescope, which can make the RMS 0.024λ
(λ=632.8nm)and areal density under 15kg/m2. This method combines existing results and numerical simulation to
establish numerical model based on Neural Network method. Research results can be applied to same processes of
designing, analyzing, and processing of large space-based telescope directly.