Parametric Sizing Equations for Earth Observation Satellites

Abstract

This paper presents an improved technique for predicting wet mass, dry mass, end-of-life power, and launch-configuration volume for Earth observation satellites based on inputs of mission type, payload mass, and payload power. These equations are meant to be used as an assistive design tool for mission planners in the pre–phase A stage to check for mission feasibility. Previous methods of estimating these characteristics entailed assuming payload mass and payload power comprised certain percentages of the final spacecraft mass, power, and volume budgets, where the percentages and density were either given as a range of observed values from past missions or taken as an average across many past missions (and mission types). Instead, this paper presents a method in which multiple regression statistics are run on past missions that are subdivided into five categories based on mission type to produce more accurate prediction equations and scaling relationships. The 95% confidence intervals for the wet mass predictions are then shown to shrink by up to 74% for GEO missions and over 50% for LEO environmental science, atmospheric science, and imaging missions compared with linear proportioning methods.