| Star sensor is a kind of high-precision attitude measuring instrument, which refers to stars on the celestial sphere. Compared with traditional attitude measuring instruments such as horizon sensor, sun sensor and magnetometer, star sensor has many advantages, which include better autonomy, stronger anti-interference ability and higher precision. Star sensor has become the key instrument of the spacecraft attitude measuring system. For the space optical remote sensing satellites, accurate direction of the boresight is an assurance of the high-precision direction-fixed mapping and space target surveillance mission. With the rapid development of high-resolution optical remote sensing satellite technology of our country, the development of the star sensor technology can not catch up with that pace. This project is the sub-project of a remote sensing camera project, of which the mission asks for a type of star sensor which can be used on the high-resolution optical remote sensing satellites. In the view of the trend of high-precision, low power consumption and miniaturization, the key technology points of star sensor processing link are studied in this dissertation.Taking STAR1000 as the core imaging device, the design of the imaging circuit is accomplished. The image data is output in LVDS format. Four-gain control and sixteen-grade exposure time control have been realized. The circuit can communicate with other devices through a serial port. High quality of the star camera has been confirmed by the night sky test.The star targets detection algorithms are studied in the dissertation, and a dynamic threshold image dividing algorithm which gets the dynamic threshold from the edge background is put forward. The star image which has been dealt with by the Gauss filter is divided by this algorithm. The algorithm can avoid targets missing and star centroid precision decreasing. The star targets are labeled by four connected domain analysis algorithm, and then the star targets coordinates are obtained by the centroid algorithm with threshold. The sources of the centroid error have been analyzed. The star centroid systematic error is analyzed by the improved analysis method in two-dimension frequency domain. The theoretical expression of the star centroid systematic error has been obtained, of which the PSF is a parameter. A simulation experiment on the star centroid systematic error is carried out based on the PSF data from CODE V. The result of the simulation experiment is in accordance with the frequency analysis, which can explain the experiment phenomenon that the amplitude of the S curve changes in the image plane. Through the star centroid systematic error measurement and compensation experiment, the result of the frequency analysis and the effect of the error compensation equation have been validated. The effect of the error compensation equation is better than the traditional sinusoidal curve compensation method, and after the compensation the star sub-pixel centroid accuracy reaches about 1/40 pixel.With data from the Smithsonian observatory catalog(SAO) under epoch J2000, the establishment of the guide star catalog has been accomplished. Firstly, based on the limit magnitude guide stars are selected from about 250,000 stars of the SAO, and then the conversion of star apparent position is carried out by astronomical correction algorithm. For the problem of celestial sphere division, this dissertation proposes a uniform celestial sphere division method based on the space solid angle. The method solves the problem of uneven division which the traditional methods have encountered. Based on the celestial sphere division of this dissertation, a quasi-uniform treatment to the guide stars is carried out, and 4096 guide stars are obtained finally. The guide star catalog is established with an improved storage structure, including four tables which are star angular distance information table, star pair table, star angular distance lookup table and the celestial sphere division table. These four tables cooperate with each other and improve the efficiency of information retrieval. The four tables cooperate well with the following algorithms. The analysis of star coordinates transformation from the celestial coordinate system to the image plane coordinate system is carried out. And the projection transformation and nonlinear imaging model are also discussed in this dissertation. After the gray conversion the simulation star map is generated. Finally under the framework of MFC the design of star map simulation software is completed using Open CV vision database, establishing a software testing environment which is necessary for the simulation experiments for following algorithms.In this dissertation, a star map identifying algorithm based on star vector matrix SVD quasi-optimal matching is proposed. The algorithm uses the three elements of the feature vector obtained by the singular value decomposition of the star vector matrix to construct the loss function, and keep the last N candidate star groups which generate the N smallest loss function values. The algorithm solves the redundancy problem encountered by the sub-graph isomorphism algorithms, improving the identification rate of the algorithm. For the identification of the celestial regions which get few stars, an identification method is proposed based on the "empty region" guide star lookup table, which is an alternative branch of the identification algorithm.On the aspect of attitude algorithm, a kind of improved SVD attitude algorithm is proposed. The algorithm solves the problem that the traditional SVD algorithm may output two attitudes for one frame. The improved SVD attitude algorithm uses the data generated by the identification algorithm, which reduces time consumption. Through the simulation software of star map, the contrasting experiment of the improved SVD algorithm, QUEST algorithm and TRIAD algorithm is carried out in the dissertation. The result shows that the improved SVD algorithm is as precise as QUEST algorithm, whose accuracy is significantly higher than that of TRIAD algorithm.On the aspect of star tracking, an algorithm based on fast star image mapping is used. The algorithm uses the attitude information among frames to generate digital reference star image by star image mapping method. Taking the star coordinates in the reference star image as the centers of tracking windows, the star tracking is carried out. If one star is not the only one in a tracking window, the angular distance matching mechanism will help to identify that star, which enhances the tracking ability of the algorithm. A threshold is set to ensure the reliability of the star tracking algorithm. The threshold also ensures the reasonable switching between the star tracking mode and the celestial identification mode. The result of the simulation experiment indicates that the tracking algorithm has the ability to track stars steadily under a large angular speed condition. |
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