A Statistical Size Estimation Model for Haystack and HAX Radar Detections
- Paper number
IAC-05-B6.1.02
- Author
Dr. Yu-lin Xu, Jacobs Sverdrup, United States
- Coauthor
Dr. Mark J. Matney, National Aeronautics and Space Administration (NASA), United States
- Coauthor
Mr. Eugene Stansbery, National Aeronautics and Space Administration (NASA), United States
- Coauthor
Dr. Christopher Stokely, Barrios Technology, Inc., United States
- Year
2005
- Abstract
The Long Range Imaging Radar (LRIR), also known as Haystack, and the Haystack Auxiliary (HAX) radar have been observing the orbital debris environment for more than a decade. One of the key radar measurements is the radar cross section (RCS) of each object detected. The conversion from RCS to target size is a complicated inverse problem especially when the size of the object is comparable to the wavelength of incident radiation, i.e., in the so-called resonant region of radiative scattering. The basis of the size estimation model (SEM) NASA developed in 1991 was a static RCS measurement experiment using a set of hypervelocity impact fragments. As one of the end products of the experiment, SEM is a simple model for one-to-one RCS-to-size conversion based on the orientation- and shape-averaged RCS of the hypervelocity impact fragments as a function of size. In this paper, we propose a Bayesian approach to improve the original NASA SEM. It takes into account the distribution of an object’s RCS with shape, composition, structure, and orientation for a given size. A given RCS does not correspond to a unique size. The statistical inference of the size distribution is based on the posterior distributions obtained iteratively from the Bayes’ rule. One benefit associated with the statistical approach is that the uncertainty analysis becomes easy and straightforward. This new approach has been applied to recent Haystack and HAX data. Results of the Bayesian inference and comparisons with the original SEM are included in the paper.
- Abstract document
- Manuscript document
IAC-05-B6.1.02.pdf (🔒 authorized access only).
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