Astrometry is an important branch of astronomy. The long-period and multi-epoch astrometric observations of solar system objects have a great promotion effect on many disciplines. For example, they include the development of ephemerides for observed objects, the enhancement of the early warning and defense capabilities on near-Earth objects (NEOs), the study of planetary physics, the study of the Solar System Formation and Evolution, the deep-space exploration, the understanding of large planets and the determination on the systematic effect of star catalogue, etc. This thesis mainly focuses on the research of NEOs, which is an important part of the solar system objects. The high-precision astrometric observation of NEOs is an important observational topic in the astrometric discipline to have great practical and scientific significance for the relevant research on technique and method. The thesis puts forward the following related technical methods, and carries out the observational experiments and verifications to set up the foundation for the follow-up research of NEO targets.The characteristics of small NEOs such as faintness and fast moving speed restrict the accuracy and precision of their astrometric observations. In this thesis, in order to reduce the impact of these factors, the image fusion technique is proposed. The images of background stars and moving objects in the obtained observation data set were segmented into two independent data sets, and then the “shift-and-stack” method was used for the background stars and moving objects, respectively. We performed image fusion for the superimposed image sets according to the observation time. A high-quality image set can be obtained, which contains many background stars and moving objects with high signal-to-noise ratios (S/Ns), and the saturation of brighter background stars can be avoided. We can reduce the influence of telescope tracking and NEO ephemeris errors on astrometric observations by using this technique. Besides, we performed astrometric reduction on the image data of NEO observed by 1 m optical telescope of Yunnan Observatories. The results showed that this new method can significantly improve the accuracy and precision of astrometry.In order to further improve the observation efficiency of telescope, the role of image fusion technique in follow-up observations of NEOs for obtaining high-precision positions. By considering the effect of streaked image, that caused when the relative velocity between stars and moving objects with respect to exposure time is too fast. On the basis of the method for estimating observable limiting apparent magnitude of stars, we further develop a method for estimating observable limiting apparent magnitude of moving objects. This method is used to obtain better observational iamges and facilitate subsequent precision astrometric measurements.Based on the requirement of image fusion technique for avoiding streaked images, a image for detection is obtained by directly superimposing the time-continuous sequence of images that containing moving objects and background stars. Using the difference information of streaked images between the moving object and the background stars, a method is proposed to identify the moving object in the image for detection by using the different slope angles of the streaked images that formed by different targets. We further propose the specific implementation method of object extraction and segmentation. The identification, extraction and segmentation of moving object were carried out for the NEA image sequence that obtained by 1 m optical telescope of Yunnan Observatories, and the effectiveness of the proposed method was verified. As a key step in image fusion technique, this method can play an important role in the subsequent development of data processing pipeline and greatly improve data processing efficiency.A brief summary and outlook are provided in the end of thesis.
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