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This paper proposes a novel tracking methodology for mul-tispectral and hyperspectral sequences. Our approach combines techniques used in multispectral and hyperspectral anomaly detection with a Kalman-Filter (KF) for tracking. The algorithm takes advantage of the additional information provided by the spectra in multispectral and hyperspectral sequences and combines it with a KF to track a target in the presence of occlusions. The proposed algorithm is based on modeling the tracked object's local background with the help of a Self Organizing Map (SOM), followed by the construction of a 2D Centre of Gravity Map (CoGM), the entries of which lead to the localisation of the target's current position. The KF, in prediction mode, is employed in order to perform robust tracking during occlusion.