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Ground moving target tracking of PAMIR detections with a Gaussian Mixture-PHD filter

This paper presents the application of the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter to ground moving target tracking for observations by an airborne scanning radar. An overview of modifications to the standard GM-PHD algorithm and the adaptations for ground moving target tracking is given. Experimental results for the tracking of ground truth targets and of targets of opportunity based on data acquired by the experimental radar system PAMIR are shown.