Factor Graph-Based Technique for Trajectory Tracking of Target with High Mobility

Abstract

This paper presents a trajectory tracking algorithm for high-mobility targets using an extended Kalman smoothing (EKS)-based factor graph (FG). Traditional tracking methods often face challenges in maintaining accuracy and computational efficiency when dealing with fast-moving objects. Leveraging the probabilistic framework of factor graphs and robust estimation of EKS, the algorithm enhances tracking precision for fast-moving objects. Extensive simulations across various motion models demonstrate improved accuracy and robustness. The results indicate that this method effectively addresses the limitations of conventional tracking algorithms, providing a promising solution for applications in aviation, autonomous vehicles, and other domains requiring high-mobility tracking.