Envelope-Based Grid-Point Approach: Efficient Runtime Complexity for Remote Sensing Coverage Analysis

Abstract

Modern remote sensing science objectives call for multi-instrument measurement collection under ever-stringent mission requirements. Distributed spacecraft missions (DSMs) answer the demand, with multisatellite mission architectures, capable of short revisit intervals and expansive coverage capacity. Variations in instrument, orbit, and the number of satellites expand the trade space combinatorically, leading to a computationally demanding mission design problem. Evaluating trade space intelligently is prevalent in literature, but the fundamental computational burden rests on figure of merit (FOM) calculation, quantifying architecture performance. The grid-point approach (GPA) and quick search and correction (QSC) methods are used to develop FOMs, but poor efficiency leads to slow evaluation of prospective DSM candidates. In this paper, a novel method is introduced, envelope grid-point approach (EGPA), fulfilling the need for faster DSM FOM calculation. The EGPA runtime is nearly invariant to temporal accuracy and varies by the inverse of grid cell size (GCS) for constant GCS-to-swath ratio, thereby scaling to high temporal and spatial resolution. The new method EGPA is validated with GPA for conical and rectangular fields of view, and then the performance of EGPA is compared against QSC, a modern improvement of GPA. Both are compared for a computationally demanding Walker Delta constellation (80°:6/3/1) over 1 day propagation, demonstrating EGPA utility in quickly determining FOMs for DSM design.