Abstract
In this paper, we address the issue of collaborative information processing for diffusive source localization and tracking using wireless sensor networks capable of sensing in dispersive medium/environment. We first determine the space-time concentration distribution of the dispersion from physical modeling and mathematical formulations of an underwater oil spill scenario, considering the effect of laminar water velocity as an external force. For static diffusive source localization, we propose two parametric estimation techniques based on maximum-likelihood (ML) and best linear unbiased estimator for the special case of our physical dispersion model. We prove the consistency and asymptotic normality of the obtained ML solution when the number of sensor nodes and samples approach infinity, and derive the Cramer-Rao lower bound on its performance. We also propose a particle filter-based target tracking scheme for moving diffusive source and derive the posterior Cramer-Rao lower bound for the moving source state estimates as a theoretical performance bound. The performance of the proposed schemes are shown through numerical simulations and compared with the derived theoretical bounds.
Highlights
The release of liquid petroleum hydrocarbon into the ocean or coastal water due to human activity has attracted tremendous attention because of its environmental, biological, and economical impact
We consider a Wireless sensor network (WSN) consisting of a fusion center (FC) and N spatially distributed biochemical static sensor nodes capable of sensing in dispersive environment
We proposed two parametric estimation methods based on maximum-likelihood estimator (MLE) and best linear unbiased estimator (BLUE) for determining static diffusive source location using wireless sensor network
Summary
The release of liquid petroleum hydrocarbon into the ocean or coastal water due to human activity has attracted tremendous attention because of its environmental, biological, and economical impact. 2.1 Moving diffusive source For a moving diffusive source-emitting substance continuously in a semi-infinite medium similar to our case, space-time concentration distribution can be obtained using the concept of convolution integral from the Green’s function solution corresponding to stationary impulsive source. In this case, substance concentration at any time instant is affected by all the past values of source position and release rate. For a moving diffusive source continuously releasing substance at a mass rate μ(t), the space-time concentration distribution in a semi-infinite medium can be obtained for a given Green’s function cG(r, t) using the following integral:. The advantage of solving the physical diffusion model corresponding to a moving diffusive source using (10) is that the initial, boundary, and other necessary conditions can be taken into account to solve for the stationary case in the first step before extending it to the moving source case
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