Augmenting Light Curve Based Static Attitude Estimation with Geometric Information

This paper studies nonlinear features of the Blin-Phong light intensity model and associated loss function in flatland. In particular features arising from the specific geometry of the observed object and observer locations are considered, and an approach for identifying the true attitude using nonlinear least squares estimation by leveraging knowledge of these characteristics is developed. In addition, characterization of the performance of the approach for varying observer locations and true attitudes is considered, and rules for observer placement to avoid loss function ambiguities are developed. Finally, conclusions are drawn, and extension of the developed gradient based techniques to the full 3D case is discussed.