Approximate Bayesian algorithms for multiple target tracking with binary sensors

Abstract

In this paper, we propose an approximate Bayesian computation approach to perform a multiple target tracking within a binary sensor network. The nature of the binary sensors (getting closer - moving away information) do not allow the use of the classical tools (e.g. Kalman Filter, Particle Filer), because the exact likelihood is intractable. To overcome this, we use the particular feature of the likelihood-free algorithms to produce an efficient multiple target tracking methodology.

19 pages, 6 figures

References in corpus (3)

• Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
• Adaptive approximate Bayesian computation
• Approximate Bayesian computation (ABC) gives exact results under the assumption of model error