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Intelligent Star Pattern Recognition for Attitude Determination: the "Lost in Space" Problem

2006; American Institute of Aeronautics and Astronautics; Volume: 3; Issue: 11 Linguagem: Inglês

10.2514/1.19398

1940-3151

Lalitha Paladugu, Ebenezer Seisie-Amoasi, Brian G. Williams, Marco P. Schoen,

Astronomical Observations and Instrumentation

This paper presents a novel approach to the attitude determination problem of space vehicles. The proposed algorithm utilizes a modified Genetic Algorithm (GA) to solve the “lost in space” star pattern recognition problem associated with star tracker attitude determination systems. Characteristics of the stars that are visible within the Field of View (FOV) – reflected on an image taken by the onboard star tracker – are formulated using simple geometric descriptions. The proposed GA minimizes the discrepancy between the characteristics of the stars inside the actual FOV and a candidate FOV selected from the on board stored star map. The global minimum of the discrepancy represents the inertial coordinates of the FOV bore-sight. The concept of a Spiral Genetic Algorithms (SGA) is proposed where the search area decreases for consecutive GA, with consequently tighter constraints, making it converge to the desired location. Also the algorithm presented has the capability of determining the rotational angle between the spacecraft’s coordinate system and that of a real star map. Simulation results indicate competitive results to current star trackers in terms of accuracy.