Volume XLII-1/W1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1/W1, 29-33, 2017
https://doi.org/10.5194/isprs-archives-XLII-1-W1-29-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1/W1, 29-33, 2017
https://doi.org/10.5194/isprs-archives-XLII-1-W1-29-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

  30 May 2017

30 May 2017

AN ATTITUDE MODELLING METHOD BASED ON THE INHERENT FREQUENCY OF A SATELLITE PLATFORM

F. Mo, X. Tang, J. Xie, and C. Yan F. Mo et al.
  • Research and Development Department, Satellite Surveying and Mapping Application Center, NASG, Beijing, China

Keywords: Satellite Attitude, Post-Process, AttModel, FFT, Inherent Frequency

Abstract. The accuracy of attitude determination plays a key role in the improvement of surveying and mapping accuracy for high-resolution remote-sensing satellites, and it is a bottleneck in large-scale satellite topographical mapping. As the on-board energy is constrained and the performance of an attitude-measurement device is limited, the attitude acquired is discretely sampled with a settled time interval. The larger the interval, the easier the data transmission, and the more deviation the attitude data will have. Meanwhile, several kinds of jitter frequencies have been detected in satellite platforms. This paper presents a novel attitude modelling (AttModel) method that sufficiently considers the discrete and periodic characteristics, and the attitude model built is continuous and consists of several inherent waves of different frequencies. The process of modelling includes two steps: (a) frequency detection, which uses raw gyroscope data within a period of time to detect the attitude frequencies (as the gyroscope data can actually reflect continuous, very small changes of the satellite platform), and (b) attitude modelling , which processes the attitude data that was filtered by extended Kalman filtering based on general polynomial and trigonometric polynomials, and these trigonometric polynomials are rebuilt by those frequencies detected in the first part of the modelling process. Finally, one experiment designed for verifying the effectiveness of the presented method shows that the AttModel method can reach a slightly better pointing accuracy without ground-control points than traditional attitude-interpolation methods.