Research on an Adaptive Chaotic Firefly Satellite Selection Algorithm

To address the issues of high computational complexity and susceptibility to local optima in traditional satellite selection algorithms for Global Navigation Satellite System (GNSS), this paper proposes an Adaptive Parameter Chaotic Firefly Algorithm (APCFA). The algorithm enhances global search capability and local convergence efficiency by introducing dynamic parameter adjustment and chaotic mapping, making it particularly suitable for complex nonlinear and multi-peak satellite selection problems. APCFA demonstrates significant advantages in balancing selection precision and computational efficiency, providing an efficient and reliable solution for satellite selection in GNSS.