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Paper: |
Centroiding Experiment for Determining the Positions of Stars with High Precision |
Volume: |
434, Astronomical Data Analysis Software and Systems XIX |
Page: |
151 |
Authors: |
Yano, T.; Araki, H.; Hanada, H.; Tazawa, S.; Gouda, N.; Kobayashi, Y.; Yamada, Y.; Niwa, Y. |
Abstract: |
We have experimented with the determination of the positions of star images on a detector with high precision such as 10 microarcseconds, required by a space astrometry satellite, JASMINE. In order to accomplish such a precision, we take the following two procedures. (1) We determine the positions of star images on the detector with the precision of about 0.01 pixel for one measurement, using an algorithm for estimating them from photon weighted means of the star images. (2) We determine the positions of star images with the precision of about 0.0001-0.00001 pixel, which corresponds to that of 10 microarcseconds, using a large amount of data over 10000 measurements, that is, the error of the positions decreases according to the amount of data. Here, we note that the procedure 2 is not accomplished when the systematic error in our data is not excluded adequately even if we use a large amount of data. We first show the method to determine the positions of star images on the detector using photon weighted means of star images. This algorithm, used in this experiment, is very useful because it is easy to calculate the photon weighted mean from the data. This is very important in treating a large amount of data. Furthermore, we need not assume the shape of the point spread function in deriving the centroid of star images. Second, we show the results in the laboratory experiment for precision of determining the positions of star images. We obtain that the precision of estimation of positions of star images on the detector is under a variance of 0.01 pixel for one measurement (procedure 1). We also obtain that the precision of the positions of star images becomes a variance of about 0.0001 pixel using about 10000 measurements (procedure 2). |
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