Multi-spectral Light Curves For Attitude Estimation via Optimization

This paper investigates the effect of an object’s design on its suitability for attitude estimation via light curve measurements. First a 2D analysis of the light curve model is conducted, and the effects of various facet properties, such as spectral-dependant parameters, are observed. Then strategies for designing objects to be more observable are investigated and simulations, including 3D attitude optimization, are conducted to demonstrate the advantages of these approaches. It is shown that multi-spectral measurements, in combination with sufficiently diverse spectral-dependant material properties, can be used to make the objects attitude more easily estimated, and even reduce the number of observers required to obtain static attitude observability.