A Track Splitting Determination Method for Elliptical Extended Targets Based on Spatio Temporal Similarity

Extended target tracking in occlusion scenarios often suffers from split errors due to sensor limitations and complex target interactions, leading to degraded tracking performance for autonomous vehicles and surveillance systems. To address this issue, in this paper, we propose a Gaussian Wasserstein distance-enhanced spatio-temporal similarity method for split error correction. We first analyze the spatio-temporal characteristics of split extended targets and model their geometric uncertainties via elliptical Gaussian distributions. Then, we integrate the Gaussian Wasserstein distance into the clue-aware trajectory similarity calculation framework to simultaneously capture positional and shape discrepancies, and designs an adaptive validation gate mechanism to dynamically adjust the threshold for track splitting, enabling accurate determination and fusion of split targets. Finally, simulation experiments are conducted to demonstrate the effectiveness of the proposed method.