With the development of aerospace technology, more and more high-precision star sensors are needed in the aerospace field for star map recognition and aircraft attitude control. However, the performance of star sensors is directly affected by the accuracy of star simulators. In order to improve the performance of the ground system of the satellite simulator, this article introduces a satellite simulation technology based on a high-precision jitter compensation system, and conducts optical design, simulation analysis, and experimental research on the system. Through research and analysis, this system can achieve the vibration compensation function of the ground satellite simulation system, providing a solution for subsequent systems that require highly stable target sources.
The main tasks include:
1) A star simulation technology with jitter compensation function has been proposed. The system provides jitter compensation beacon light through a laser light source, combines multiple target star maps using a large aperture beam splitter prism, and uses a large aperture high-precision piezoelectric deflection mirror to provide real-time feedback compensation for stable star light. In conjunction with a long focal length parallel light tube, it provides a highly stable star target source for high-precision star sensors.
2) Two key components of the star simulation optical path have been designed: the star collimating mirror group and the star focusing mirror group. Through the high-precision development of the starlight collimating mirror group and the starlight convergence mirror group, high-quality star map simulation function has been achieved.
The star maps collected by the star sensor during actual in orbit flight are sourced from stars. To provide a ground calibration environment that is the same as the in orbit flight environment of the star sensor, the light source of the star simulator is an integrating sphere wide spectral light source. Different wavelengths have different refractive indices, and dispersion occurs when propagating in the medium. The broad-spectrum beam passes through the transmission optical system of the star simulator, ultimately forming multiple colored light spots on the detection focal plane, causing the positioning deviation of the system’s star point centroid. Therefore, in the optical system design process of star simulators, it is necessary to consider the spectral characteristics of stars, design a wide spectral range, and improve the accuracy of centroid positioning.
In astronomy, the spectral types of seven stars are represented by the letters 0-M based on their temperature levels. Each spectral type can be further divided into 0-9 subtypes, such as G2 representing the sun. The energy distribution of stars follows the blackbody radiation law with respect to their spectra
To improve the working performance of the star simulator, non thermal design is considered for its optical system. When the temperature environment changes, general imaging optical systems can cause a decrease in image quality. The changes in aberration characteristics of optical systems, such as coma and chromatic aberration, can affect the positioning accuracy of star point centroids, thereby affecting the ground calibration effect of star sensors. Therefore, considering achromatism before constructing the primary structure of an optical system is an important step in optical system design. According to the theory of passive thermal dissipation in optical mechanical systems, the positional chromatic aberration and magnification chromatic aberration of thin lens optical systems are related to factors such as the thermal expansion coefficient and refractive index temperature coefficient of optical and mechanical materials under the action of steady-state temperature fields. Choosing appropriate optical and mechanical materials is the key to achieving non thermal design in transmission optical systems.
The star simulator system can provide simulation conditions of dark stars ranging from 0 to 10 for star sensors, and its performance is affected by stray light in the system.
In imaging optical systems, due to uneven coating of optical lenses, unreasonable positions of mechanical and other structural components in the optical path, and the presence of off-axis field of view light sources, there are not only normal beams participating in imaging on the image plane, but also beams transmitted through non designed optical paths. These beams undergo multiple reflections or scattering in the optical system, thereby reducing the imaging quality of the optical system. By conducting stray light analysis on the optical system, the generation of stray light in the system can be obtained, providing guidance for the subsequent setting of shading structures. Stray light is manifested in the following three categories:
1) Ghost image: Multiple reflections of the imaging beam in the field of view on the optical surface converge to the focal plane of the detector, resulting in ghost images. It is generally believed that the energy carried by the beam will decay to a negligible level after four reflections on the lens surface. Therefore, in the design process of the optical system, a reasonable design of the structure can avoid ghost images.
2) Stray light caused by direct incident light: When the central obstruction of the optical system is too large, the light will directly incident on the focal plane of the detection system to form stray light. Due to the opening in the center of the primary mirror, reflective optical systems may directly pass through the secondary mirror and incident light from the opening in the primary mirror to the image plane. Therefore, it is necessary to design noise suppression mechanisms such as light shields and light blocking rings for such systems.
3) One/multiple scattering of light: The light generated by the light source will scatter on the surface of the object, forming stray light when incident on the image surface. The surface of the structure can be sprayed with matte paint or matte structure to suppress the propagation of scattered light. For high-precision optical systems, the thermal radiation generated by external heat sources can also cause stray light and reduce system performance.
When the pixel size of the detector is fixed, in order to improve the accuracy of star point centroid positioning, the star point target should occupy 2-3 pixel sizes on the imaging surface of the detector. The intensity of star point dispersion spots is Gaussian distributed on the focal plane of the detector, and the closer the star point is to the center of mass, the greater the grayscale value of the star pixel. By using a centroid algorithm weighted by grayscale values, the accuracy of star point centroid positioning can be improved to the sub pixel level.
(1) Traditional centroid method
The traditional centroid method involves graying out the star spot image on the focal plane of the detector, and then adding a weighted calculation to its grayscale value. The weighted weight is the grayscale value of the pixel. Under normal circumstances, the closer the energy distribution of the star spot is to the center of mass, the greater its energy value, which means that the grayscale value of the pixel is higher. The traditional centroid method can be used to obtain the centroid coordinates of star point images.
(2) Weighted centroid method
Excellent imaging optical system design results in sharp star points, allowing the Gaussian distribution of star point grayscale values to grow faster as they approach the center. The square weighted centroid method can be used to increase the contribution of pixels near the center point to the final centroid coordinate calculation by using the square of the grayscale values as weights.
(3) Weighted centroid method with threshold
The actual star map collected by the camera focal plane will have background noise, and using the centroid method with threshold can reduce the interference of background noise and improve the accuracy of star point centroid positioning. This method subtracts the pre-set threshold S from the grayscale values of all pixels, and then calculates the centroid through the weighting method. This method is currently the most widely used.
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