Sensor signal inference: evasive targets, particles and point processes
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I will describe methods for tracking from very noisy (high-clutter) sensors utilising Bayesian statistical models for sensor detections and object motion, combined with state of the art Monte Carlo computational methodology for estimation in the nonlinear and non-Gaussian scenarios that arise in this field.
This talk is part of the Horizon: A Sensory World. Novel Sensor Technologies and Applications series.
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