PRELIMINARY ANALYSIS OF A COMBINED LIGHT CURVE AND LASER RANGING APPROACH FOR INITIAL ATTITUDE ESTIMATION OF RESIDENT SPACE OBJECTS

The accurate estimation of the attitude of Resident Space Objects (RSOs) is a fundamental task in Space Situational Awareness (SSA) applications. Light curves (LCs) are widely used for this purpose due to their availability and non-intrusive nature. However, LC-based attitude determination is inherently ambiguous, particularly in the presence of geometric symmetries, uniform surface properties, or low signal-to-noise conditions. This work addresses these limitations by integrating Satellite Laser Ranging (SLR) measurements with LC data to improve attitude observability. A simulation framework incorporating high-fidelity LC and SLR measurement models is developed, and a Particle Swarm Optimization approach is employed to identify attitude states consistent with both data sources. The methodology is evaluated in a realistic simulated scenario with results demonstrating that the inclusion of SLR data significantly reduces attitude ambiguities compared to LC-only approaches, supporting improved attitude estimation for both cooperative and inactive RSOs.