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Standard particle filters have shown excellent performance in many challenging scenarios of target tracking, and therefore they often are the method of choice. In cases when there is no knowledge about the noise distributions in the studied system, one cannot use these methods or will use them with assumptions that in general may lead to very poor results. An alternative to standard particle filters...
In many situations, solutions to nonlinear discrete-time filtering problems are available through approximations. Many of these solutions are based on approximating the posterior distributions of the states with Gaussian distributions. In this letter, we compare the performance of Gaussian-based filters including the extended Kalman filter, the unscented Kalman fitter, and the Gaussian particle filter...
In this paper we address the problem of tracking of a high-speed maneuvering target which moves along a two-dimensional space. We investigate and compare several approaches based on the Bayesian methodology and propose various strategies to cope with the two models that account for the different regimes of movement. The advantages and disadvantages of the considered algorithms are illustrated and...
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