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Many physical systems evolved on matrix Lie groups and mixture filtering designed for such manifolds represent an inevitable tool for challenging estimation problems. However, mixture filtering faces the issue of a constantly growing number of components, hence requiring appropriate mixture reduction techniques. In this letter, we propose a mixture reduction approach for distributions on matrix Lie...
This paper presents a novel method for Bayesian bearing-only tracking. Unlike the classical approaches, which involve using Gaussian distribution, the tracking procedure is completely covered with the von Mises distribution, including state representation, transitional probability, and measurement model, since it captures and models well the peculiarities of directional data. The state is represented...
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