Von Mises ensemble yields angular uncertainty estimates that integrate directly into tracking via closed-form likelihoods and shows stronger perturbation sensitivity than evidential deep learning on radar DOA tasks.
RD-CFAR: Fast and accurate constant false alarm rate algorithm for automotive radar ap- plications,
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Von Mises Based Uncertainty Quantification for Closely Spaced Automotive Radar Targets
Von Mises ensemble yields angular uncertainty estimates that integrate directly into tracking via closed-form likelihoods and shows stronger perturbation sensitivity than evidential deep learning on radar DOA tasks.