Three-dimensional orientation vector estimation for sub-components of space object imagery

Xun Du; Stanley C. Ahalt; Bruce E. Stribling

doi:10.1117/1.601912

1 March 1998 Three-dimensional orientation vector estimation for sub-components of space object imagery

Xun Du, Stanley C. Ahalt, Bruce E. Stribling

Optical Engineering, Vol. 37, Issue 3, (March 1998). https://doi.org/10.1117/1.601912

We describe a model-based image analysis system that automatically estimates the 3-D orientation vectors of satellites and their subcomponents by analyzing images obtained from a ground-based optical surveillance system. We adopt a two-step approach: pose estimates are derived from comparisons with a model database and pose refinements are derived from photogrammetric information. The model database is formed by representing each available training image by a set of derived geometric primitives. To obtain fast access to the model database and to increase the probability of early successful matching, a novel index-hashing method is introduced. An affine point-matching method is also introduced for improving system performance on a wide variety of satellite shapes. We present recent results, which include our efforts at isolating and estimating orientation vectors from degraded imagery on a significant database of satellites.

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Xun Du, Stanley C. Ahalt, and Bruce E. Stribling "Three-dimensional orientation vector estimation for sub-components of space object imagery," Optical Engineering 37(3), (1 March 1998). https://doi.org/10.1117/1.601912

Published: 1 March 1998

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