A Polar Coordinate System Based Grid Algorithm for Star Identification

Hua ZHANG, Hongshi SANG, Xubang SHEN

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DOI: 10.4236/jsea.2010.31004                

Abstract

In Cartesian coordinate systems, the angular separation-based star identification algorithms involve much trigon- ometric function computing. That delays the algorithm process. As in a polar coordinate system, the coordinates are denoted by angular values, it is potential to speed up the star identification process by adopting a polar coordinate sys-tem. An angular polar coordinate system is introduced and a grid algorithm based on the coordinate system is proposed to enhance the performances of the star identification process. The simulations demonstrate that the algorithm in the angular polar coordinate system is superior to the grid algorithm in the rectangle Cartesian coordinate system in com-puting cost and identification rate. It can be used in the star sensors for high precision and high reliability in spacecraft navigation.

Keywords

Star Identification, Grid Algorithm, Polar Coordinate System, Star Sensor

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	C. C. Liebe, “tar trackers for attitude determination,” EEE Aerospace and Electronics Systems Magazine, Vol. 10, No. 6, pp. 10–16, June 1995.
[2]	C. C. Liebe, “Accuracy performance of star tracker-a tutorial,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 38, No. 2, pp. 587–589, April 2002.
[3]	A. Domenico, R. Giancarlo, “Brightness-independent start-up routine for star trackers,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 38, No. 3, pp. 813–823, July 2002.
[4]	D. Mortari, M. A. Samaan, and C. Bruccoleri, et al, “The pyramid star identification technique,” Journal of The In-stitute of Navigation, Vol. 51, No. 3, pp. 171–184, 2004.
[5]	S. C. Daniel, W. P. Curtis, “Small field-of-view star iden-tification using bayesian decision theory,” IEEE Transac-tions on Aerospace and Electronic Systems, Vol. 36, No. 3, pp. 773–783, July 2000.
[6]	M. A. Samaan, D. Mortari, and J. L. Junkins, “Non-di-mensional star identification for uncalibrated star cam-eras,” AAS/AIAA Space Flight Mechanics Meeting, Ponce, Puerto Rico, Paper No. AAS 03-131, February, 2003.
[7]	M. A. Samaan, D. Mortari, and J. L. Junkins, “Recursive- mode star identification algorithms,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 41, No. 4, pp. 1246–1254, October 2005.
[8]	C. Padgett and K. Kreutz-Delgado, “A grid algorithm for autonomous star identification,” IEEE Transactions on Aerospace and Electronics Systems, Vol. 33, No.1, pp. 202–213, January 1997.
[9]	C. Padgett, K. Kreutz-Delgado and S. Udomkesmalee, “Evaluation of star identification techniques,” Journal of Guidance, Control and Dynamics, Vol. 20, No. 2, pp. 259–267, 1997.
[10]	G. Zhang, X. Wei and J. Jiang, “Full-sky autonomous star identification based on radial and cyclic features of star pattern,” Image and Vision Computing, Vol. 26, No. 7, pp. 891–897, July 2008.
[11]	G. B. Richard, M. G. Andrew, et al, “Advanced mathe-matics: precalculus with discrete mathematics and data analysis,” Boston: Houghton Mifflin, 1994.