1. Identifying illumination conditions most suitable for attitude detection in light curves of simple geometries
- Author
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Laurence Blacketer, Hodei Urrutxua, and Hugh G. Lewis
- Subjects
Atmospheric Science ,Brightness ,Offset (computer science) ,business.industry ,Aerospace Engineering ,Astronomy and Astrophysics ,Rotation matrix ,Light curve ,Geophysics ,Optics ,Phase angle (astronomy) ,Space and Planetary Science ,Reflection (physics) ,Range (statistics) ,General Earth and Planetary Sciences ,Bidirectional reflectance distribution function ,business ,Mathematics - Abstract
The objective of this paper is to identify the illumination conditions that maximise the differences that can be measured between light curves of an object resulting from its attitude state. This is relevant to attitude determination techniques using light curve data, and is valuable for the design of observation strategies that maximise the information contained in light curves. For this purpose, synthetic light curves were generated for a number of attitude states, object geometries and illumination configurations. The light curves were generated through application of a Bidirectional Reflectance Distribution Function (BRDF) to a faceted object geometry. The differences between the light curves were quantified using a Root Mean Square Error (RMSE). Results showed that, depending on the reflection model, the object geometry and the attitude state, particular illumination conditions existed that led to the largest RMSE between different attitude states. In most cases, increasing the phase angle increased the RMSE between light curves arising from different attitude states. The maximum RMSE occurred when the illumination vector was either aligned with the rotation vector or offset from it by 90°. It is concluded that characterising the rotational motion of an object from its brightness data is best performed using multiple observations. These observations should be constructed in a way that maximises the difference in the illumination geometry. One way of achieving this would be to use observations from multiple observatories with a diverse range of geographical locations.
- Published
- 2022