Attitude fluctuation of satellite platform is a crucial error source that influences the performance of the satellite
surveying and mapping and extensively existed in all spacecrafts. Verification and detection of fluctuation frequency of
the high spatial resolution remote sensing satellite plays a key role in farther optimizing the geo-location accuracy when
the geometric accuracy of satellite reaches a fairly high precision. In this paper, an approximate sampling theorem is
designed to verify and detect the attitude fluctuation frequency of satellite, and this novel method is based on Nyquist-
Shannon sampling theorem, which applies ingeniously attitude acquisition time interval. The sampling interval of this
approach will be appropriately altered by proposed sampling model while the satellite attitude acquisition frequency is
not proportional to the fluctuation frequency. A simulative triangular wave and a strip attitude data of ZY-3 obtained
while satellite was early on-orbit are experimented, and these results demonstrate the following findings: 1)the method
proposed is effective and can filter irrelevant wave partially; 2)the fluctuation components obtained contain a distinct
frequency of around 0.67Hz meets the inherent frequency of ZY-3 detected by other methods.
In this paper, a guide star selection algorithm based on angular grids is presented, which can be used to minimize the size
of initial star catalogue and guarantee the distribution of the guide stars as uniform as possible . This algorithm is
preformed by dividing the FOV into many equal angular grids and mapping the grids onto the celestial sphere. The guide
stars are selected in the extent of grids and their brightness and position in the celestial sphere are considered as well.
The experiment with real star catalogue data demonstrates the validity of the proposed algorithm.
Attitude estimation method is one of influencing factors for the attitude accuracy. Traditionally, the elements of the
rotation matrix as attitude unknowns are estimated optimally, but the solved attitude angles based on the elements of
rotation matrix aren't optimal. A rigorous attitude estimation approach for satellite attitude determination based on star
sensor is presented in this paper, which directly considers three-axis attitude angles as attitude unknowns. The
experiment indicates the proposed approach can improve the attitude accuracy to a great degree when the position errors
of image points are within ±0.5 pixel, and the efficiency can be guaranteed as well.
The low satellite attitude accuracy determined by star sensors is one of the key problems to high accuracy satellite data
acquired in China. Major error sources affecting the attitude accuracy are systematically analyzed, and the relationships
between these error sources and attitude accuracy are investigated qualitatively and quantitatively in the paper. The
regularity will be summarized, which can provide a helpful reference guide for improving the attitude accuracy. Some
methods and strategies to improve the attitude accuracy can be brought forwards and discussed based on the results of
Traditionally, the splitting and merging algorithm of image segmentation is based on quad tree data structure, which is not convenient to express the topography of regions, the line segments and other information. A new framework is discussed in this paper. It is "TIN based image segmentation and grouping", in which edge information and region information are integrated directly. Firstly, the constrained triangle mesh is constructed with edge segments extracted by EDISON or other algorithm. And then, region growing based on triangles is processed to generate a coarse segmentation. At last, the regions are combined further with perceptual organization rule.