Research and Realization of Highly Accurate Data Generation Based on Channel Simulator

Abstract:

Article Preview

With high accuracy, the channel simulator plays an important role in the docking experiment between the ground and the responder beacon. To begin with, this paper introduces the data generation algorithm including the data generation based on simulation technology, the principle of the linear least squares algorithm and then proposes the least squares quadratic spline method to generate highly accurate data in this channel simulator. Secondly, this paper introduces the system design to realize the data generation. Finally, a case which studies the approximation and an error analysis of the data generation algorithm is realized. The algorithm is considered to be accurate and easy to get the source data. The core of the algorithm is using data from Satellite Tool Kit to generate distance and speed sequence, and using the least squares to approximate real data and quadratic spline to fit for obtaining highly accurate data.

Info:

Periodical:

Advanced Materials Research (Volumes 588-589)

Edited by:

Lawrence Lim

Pages:

1316-1319

Citation:

Z. Zheng et al., "Research and Realization of Highly Accurate Data Generation Based on Channel Simulator", Advanced Materials Research, Vols. 588-589, pp. 1316-1319, 2012

Online since:

November 2012

Export:

Price:

$38.00

[1] Hao Xiaoqin, Surface Acoustic Wave Delay Line, in Modern Radar, Vol 32 No. 4, pp.79-81, Apr (2010).

[2] Xie an-guo, Xue Yuwang, Guo Jianwen, Study of microwave optical fiber delay-line techniques, in Optical Fiber & Electric Cable, No. 4, pp.1-5, (2002).

[3] Zou Xiuyen, Error theory and experimental data processing, Beijing press, (1986).

[4] Xiao Mingyao, Error theory and its applications, Metr. Press, (1985).

[5] Eykhoff P., System identification: parameter and state estimation, London Wiley, (1974).

[6] Li Xiaoye, An Adaptive Algorithm for Knots of Cubic B-Spline in Data Fitting, M.S. thesis, DaLian, China: Computational Mathematics, pp.1-4, (2008).

[7] Chen Lu, Cubic B-spline Fitting Method Based on Dominant Information, M.S. thesis, DaLian, China: Computational Mathematics, pp.7-10, (2009).

[8] Zhao Cheng, Structured perturbation problem in linear least squares problem and spline curve fitting, M.S. thesis, Shanghai, China: FuDan University, pp.3-7, (2009).