MD-IPDA Combined with GP for ETT

초록

Target tracking using high-resolution sensors often suffers from multiple detections generated by a single target, leading to a typical multiple detection (MD) problem that requires distinguishing between true target detections and clutter. To address this issue, a Multiple Detection-Integrated Probabilistic Data Association (MD-IPDA) algorithm is combined with a Gaussian Process (GP) for robust single-target tracking in cluttered environments. The MD-IPDA framework utilizes the target existence probability (TEP) as a track scoring mechanism to ensure reliable track maintenance. Meanwhile, GP is employed to construct measurement model for multiple scattering points, based on predefined contour points determined by the target’s shape. The performance of the proposed extended target tracking (ETT) method is validated through simulation experiments and further assessed using the information reduction factor (IRF), allowing direct comparison with existing ETT algorithms.

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