Stochastic Filtering with Networked Sensing

Hana Baili (1) , Hichem Snoussi (2)

1 E3S - Supélec Sciences des Systèmes
2 LM2S - Laboratoire Modélisation et Sûreté des Systèmes

This paper presents a solution to the problem of target tracking within a sensor network. This is based on modeling the target dynamics as a Markov process, and is reformulated as nonlinear filtering. When the target motion is a diffusion process, the optimal filtering involves a resolution of the backward Kolmogorov equation. Since an explicit solution for this partial differential equation does not exist in general, we recover the filtering by an alternative Monte-Carlo approach.

Domaines: Systèmes dynamiques [math.DS]; Probabilités [math.PR]

Hana Baili, Hichem Snoussi. Stochastic Filtering with Networked Sensing. IEEE 70th Vehicular Technology Conference (VTC'09), Sep 2009, Anchorage, United States. ⟨10.1109/VETECF.2009.5379078⟩. ⟨hal-00424403⟩