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In this paper we will consider several algorithms for tracking closely spaced objects. In particular we will concentrate on various particle filter implementations. One particular problem when using a joint multi target particle filter is the so-called mixed labelling problem. This problem amounts to the fact that different particles will have a different labelling w.r.t. target identity. The combination...
Data assimilation in the context of puff based dispersion models is studied. A representative two dimensional Gaussian puff atmospheric dispersion model is used for the purpose of testing and comparing several data assimilation techniques. A continuous nonlinear observation model, and a quantized probabilistic nonlinear observation model, are used to simulate the measurements. The quantized model...
A model for vehicle motion on a road network Is developed using an enumeration of feasible routes. Combined with a generic stochastic model of distance travelled, a predicted pdf of vehicle position is derived as a mixture. This approach allows prior information on vehicle intent and behaviour to be included via the mixture weights. Illustrative examples are given using a second-order linear-Gaussian...
In this paper the so called mixed labeling problem inherent, or at least thought to be inherent to a joint state multi target particle filter implementation is treated. The mixed labeling problem would be prohibitive for track extraction from a joint state multi target particle filter. It is shown and proven using the theory of Markov chains, that the mixed labeling problem is inherently self-resolving...
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