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Treatment of star catalog biases in asteroid astrometric observations

Author:
Chesley, Steven R.  Baer, James  Monet, David G.  


Journal:
ICARUS


Issue Date:
2010


Abstract(summary):

In this paper, we discuss the detection of systematic biases in star positions of the USNO A1.0, A2.0, and B1.0 catalogs, as deduced from the residuals of numbered asteroid observations. We present a technique for the removal of these biases, and validate this technique by illustrating the resulting improvements in numbered asteroid residuals, and by establishing that debiased orbits predict omitted observations more accurately than do orbits derived from non-debiased observations. We also illustrate the benefits of debiasing to high-precision astrometric applications such as asteroid mass determination and collision analysis, including a refined prediction of the impact probability of 99942 Apophis. Specifically, we find the IP of Apophis to be lowered by nearly an order of magnitude to 4.5 x 10(-6) for the 2036 close approach. (C) 2010 Elsevier Inc. All rights reserved.


Page:
158---181


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