Research on celestial positioning method with improved particle swarm optimization algorithm

Celestial navigation remains an important positioning method due to its independence from external infrastructure and high accuracy. This paper explores the application of improved Particle Swarm Optimization (PSO) algorithms to celestial positioning, especially in two-star scenarios. Traditional analytical and iterative methods face challenges such as the non-uniqueness of solutions and dependence on initial values. The proposed method enhances the fitness function to improve the convergence speed and accuracy while adopting a dynamic weight adjustment strategy to prevent premature convergence. Experimental results show that the improved PSO method achieves comparable accuracy to the analytic method and reduces the number of iterations required for convergence. These findings indicate that the improved PSO method is a viable method for celestial navigation and can be extended to multi-star positioning applications.