Estimation Method of Micro-debris Population from Solar Array Images

Paper number

IAC-06-B6.P.1.05

Author

Dr. Koki Fujita, Kyushu University, Japan

Coauthor

Prof. Toshiya Hanada, Kyushu University, Japan

Year

2006

Abstract

In this study, we propose a new approach to estimating micro-debris population from solar array images. In Geosynchronous Earth Orbit (GEO), enough space debris measurement has not been done because of the long distance from the earth to the orbit. On the other hand, most of the satellites have the solar panels on board as an indispensable power source. With the geostationary satellite, the area of a solar panel reaches to a hundred meter squared, which makes the satellite be the reasonable target of the micro-debris and cosmic dust.
      We propose to realize debris measurement from observed impact craters in the solar array images. As the pictures of the solar arrays are generally taken from slant views, the real shapes of the impact craters should be obtained from the original images. To recover the real shape of the craters, we apply a projective invariant property to the solar array images. For a solar array image, if there are one point in the area of the impact craters and the other four point markers whose locations on the surface of the array are exactly known, the array image taken from front view can be recovered, and it similarly expresses the real shapes of the craters.
      Furthermore, to estimate the size distribution of the debris, Bayesian approach is applied. This approach was originally proposed by Xu et al. (2005) aiming at improving the NASA’s size estimation model (SEM). If the shapes of the impact craters on the solar arrays are measured and the conditional probability distribution function between the size of the debris and the diameter of the impact crater is also given, the debris’ size distribution is estimated with Bayesian inference algorithm.
      The effectiveness of the proposed method is demonstrated by a series of the numerical simulations utilizing artificial camera images, and the current problem to be solved is also discussed.

Abstract document

IAC-06-B6.P.1.05.pdf

Manuscript document

IAC-06-B6.P.1.05.pdf (🔒 authorized access only).

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