Spacecraft Attitude Determination Using Terrestrial Illumination Matching

An algorithm to conduct spacecraft attitude determination via terrestrial illumination matching (TIM) is presented consisting of a novel method that uses terrestrial lights as a surrogate for star fields. Although star sensors represent a highly accurate means of attitude determination with considerable spaceflight heritage, TIM provides a potentially viable alternative in the event of star sensor malfunction or performance degradation. The research defines a catalog of terrestrial light “constellations,” which are then implemented within the TIM algorithm for position acquisition of a generic spacecraft bus. With the algorithm relying on terrestrial lights rather than the establish standard of star fields, a series of sensitivity studies are showcased to determine performance during specified operating constraints, to include varying orbital altitude and cloud cover conditions. Also, a comparison of relative accuracy will be presented for TIM with a generic star sensor.

I. Introduction

TRADITIONALLY, star measurements are used for on-board spacecraft attitude determination, but the use of terrestrial-focused optical sensors for this purpose is growing in popularity. The most common method of accurate attitude determination uses star trackers [1]. However, since the 1970s and the debut of the U.S. Air Force's (USAF) Defense Meteorological Satellite Program (DMSP), sensors have been able to detect the visible spectrum, allowing the Earth to be seen in a whole new way [2]. As the on-board equipment that supports these capabilities advances, viable options other than star trackers or sun sensors can be explored. A concise image of Earth's terrestrial lights is given by the National Air and Space Administration's (NASA) “Black Marble,” a composite image of all nighttime city lights. Black Marble was created using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Partnership (NPP) [3]. Data from VIIRS and similar sensors on the LandSat missions have been used for various disciplines and forms of analysis from cartography to the estimation of Gross Domestic Product (GDP) [4].