Abstract

We use robust nonlinear regression techniques to estimate the separation, brightness ratio, and orientation of binary stars. We perform the regression by fitting a binary-star model to a measurement of the object complex visibility obtained from infrared speckle data. Examination of χ² for subplanes of the parameter range provides predictions of the accuracy required in the initial guesses at the parameters. We use the predictions to design an effective global search. The results of the global least-squares fit provide the necessary starting point for the robust regression. Using observational data, we show the robust regression solution to be superior to the conventional least-squares solution.

© 1992 Optical Society of America

Estimation of binary star parameters by model fitting the bispectrum phase

A. Glindemann, R. G. Lane, and J. C. Dainty
J. Opt. Soc. Am. A 9(4) 543-548 (1992)

Image truncation in stellar speckle imaging

Robert W. Johnson and George J. M. Aitken
J. Opt. Soc. Am. A 9(11) 1955-1963 (1992)

Object fitting to the bispectral phase by using least squares

A. Glindemann and J. C. Dainty
J. Opt. Soc. Am. A 10(5) 1056-1063 (1993)

Practical aspects of image recovery by means of the bispectrum

Pedro Negrete-Regagnon
J. Opt. Soc. Am. A 13(7) 1557-1576 (1996)

Least-squares phase estimation with multiple parameters in phase-shifting electronic speckle pattern interferometry

Hae Young Yun, Chung Ki Hong, and Seok Won Chang
J. Opt. Soc. Am. A 20(2) 240-247 (2003)