Research on Multi-Source Localization of Rocket Debris Based on PSO and LEO-MPA Algorithm

With the development of the space industry, the precise localization of rocket debris is crucial for safe recovery and reducing potential threats. This paper presents a multi-source rocket debris localization technology based on the Particle Swarm Optimization (PSO) algorithm and the Local Escaping Operator-Marine Predators Algorithm (LEO-MPA). By recording the arrival time of the sonic boom through seven monitoring devices, we established algebraic and optimization models to accurately determine the three-dimensional position coordinates (longitude, latitude, elevation) and time of the debris. The study found that the optimization model outperforms the algebraic model in positioning accuracy, especially when using the PSO algorithm, where the prediction location error is significantly reduced. Furthermore, to address the random errors in time recording in practical applications, this paper introduces a penalty function to correct the model and solves it using the PSO and LEO-MPA algorithms. The results show that the LEO-MPA algorithm is superior to the PSO algorithm in handling errors and improving positioning accuracy. The models and algorithms presented in this study provide an effective technical means for the rapid and accurate localization of rocket debris, with significant engineering application value and theoretical significance.