Artículo de revista
Optimality of the maximum likelihood estimator in astrometry
Fecha
2018Registro en:
Astronomy and Astrophysics, Volumen 616, 2018
14320746
00046361
10.1051/0004-6361/201732537
Autor
Espinosa, Sebastian
Silva, Jorge
Mendez, Rene
Lobos, Rodrigo
Orchard Concha, Marcos
Institución
Resumen
Context. Astrometry relies on the precise measurement of positions and motions of celestial objects. Driven by the ever-increasing
accuracy of astrometric measurements, it is important to critically assess the maximum precision that could be achieved with these
observations.
Aims. The problem of astrometry is revisited from the perspective of analyzing the attainability of well-known performance limits (the
Cramér-Rao bound) for the estimation of the relative position of light-emitting (usually point-like) sources on a CCD-like detector
using commonly adopted estimators such as the weighted least squares and the maximum likelihood.
Methods. Novel technical results are presented to determine the performance of an estimator that corresponds to the solution of
an optimization problem in the context of astrometry. Using these results we are able to place stringent bounds on the bias and
the variance of the estimators in close form as a function of the data. We confirm these results through comparisons to numerical
simulations under a broad range of realistic observing conditions.
Results. The maximum likelihood and the weighted least square estimators are analyzed. We confirm the sub-optimality of the
weighted least squares scheme from medium to high signal-to-noise found in an earlier study for the (unweighted) least squares
method. We find that the maximum likelihood estimator achieves optimal performance limits across a wide range of relevant observational conditions. Furthermore, from our results, we provide concrete insights for adopting an adaptive weighted least square
estimator that can be regarded as a computationally efficient alternative to the optimal maximum likelihood solution.
Conclusions. We provide, for the first time, close-form analytical expressions that bound the bias and the variance of the weighted
least square and maximum likelihood implicit estimators for astrometry using a Poisson-driven detector. These expressions can be
used to formally assess the precision attainable by these estimators in comparison with the minimum variance bound.