Analytical field-of-regard representation for rapid and accurate prediction of agile satellite imaging opportunities

Abstract

Agile Earth observation satellites (AEOSs) possess high-attitude maneuverability and achieve better efficiency than traditional platforms in imaging missions. Onboard mission scheduling of agile satellites requires rapid and accurate prediction of imaging opportunities. This problem has not yet been fully investigated in the previous literature. Our study presents a precise analytical model for field-of-regard (FoR) representation of agile satellites and applies a self-adaptive Hermite interpolation technique for rapid determination of imaging opportunities. The FoR of an agile satellite is regarded as a large virtual field-of-view (FoV) synthesized from infinite instantaneous FoVs of onboard camera corresponding to all possible orientations of agile satellite within limits of maximum maneuverability. Analytical equations of the bounding envelope of the FoR are formulated through quadratic curve fitting. Visibility criteria of the analytical FoR model are derived and piecewise cubic polynomials featured with autonomous searching for interpolation points are used to approximate the visibility functions. Numerical simulations show that the analytical FoR model approximates the truth model with an accuracy of better than 99%. In addition, the self-adaptive algorithm significantly reduces the computational cost for imaging opportunity determination compared to traditional trajectory checking method.