Knowledge area(s) (original) (raw)

2006

Abstract

Stochastic hybrid systems Bayesian filtering Particle filtering State dependent switching Jump-nonlinear systems Non-Markov jumps Maneuvering target tracking Exact Bayesian and particle filtering of stochastic hybrid systems Problem area In literature on Bayesian filtering of stochastic hybrid systems most studies are limited to Markov jump systems. The main exceptions are approximate Bayesian filters for semi-Markov jump linear systems. These studies showed that nonlinear filtering becomes much more challenging under non-Markov jumps. This challenge however does not apply to particle filtering of stochastic hybrid systems. In practice, non-Markov jumps rather are the rule, not the exception. For example, on an airport, the probability at which a taxiing aircraft makes a maneuver depends heavily on its position; e.g. when taxiing near a crossing on the airport, the probability of starting a turn is relatively high, whereas outside these areas this probability may be very small. A si...

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