A Fast Direct Position Determination Method for Tri-Satellite Based on Particle Swarm Optimization

The direct position determination method frequently depends on an exhaustive search to estimate positions. This approach can lead to substantial computational burdens, thereby constraining real-time positioning, particularly in scenarios characterized by extensive satellite coverage. To address this issue, we introduce the MSEPSO-TSDPD algorithm (Multi-Strategy Enhanced Particle Swarm Optimization for Tri-Satellite Direct Position Determination). This algorithm constructs a cost function to estimate the target position using time difference and frequency difference information. By incorporating particle swarm optimization, the algorithm leverages social interaction and a collaborative search strategy between particles, guiding the particle swarm iteratively towards the current optimal solution. This approach avoids the inefficiency of traditional exhaustive search methods that require traversing the entire search space, thus reducing unnecessary computation and enhancing search efficiency. Simulation results indicate that the proposed algorithm significantly reduces computational complexity, with computation time being only 15% of that required by exhaustive search algorithms, while maintaining comparable positioning accuracy.