Novel nonlinear measurement update improves estimation in circular states, indicating advantages over traditional methods.
In this paper, we propose a novel progressive nonlinear measurement update for circular states. This generalizes our previously published circular filter that so far was limited to identity measurement equations. The new update method is based on circular distributions in order to capture the periodic properties of a circular system better than conventional approaches that rely on standard Gaussian distributions. Besides the progressive measurement update, we propose two additional measurement updates that are obtained by adapting traditional filters to the circular case. Simulations show the superiority of the proposed progressive approach.
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Kurz et al. (2014) studied this question.
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