Accession Number:

ADA582222

Title:

Model-Free Stochastic Localization of CBRN Releases

Descriptive Note:

Journal article

Corporate Author:

BOSTON UNIV MA DEPT OF SYSTEMS AND COMPUTER ENGINEERING

Report Date:

2013-01-01

Pagination or Media Count:

16.0

Abstract:

We present a novel two-stage methodology for locating a Chemical, Biological, Radiological, or Nuclear CBRN source in an urban area using a network of sensors. In contrast to earlier work, our approach does not solve an inverse dispersion problem but relies on data obtained from a simulation of the CBRN dispersion to obtain probabilistic descriptors of sensor measurements under a variety of CBRN release scenarios. At its first stage, subsequent sensor observations under nominal, CBRN event-free conditions are assumed to be independent and identically distributed, and we rely on the method of types to detect a CBRN event. Conditional on such an event, subsequent sensor observations are assumed to follow a Markov process. Using composite hypothesis testing, we map sensor measurements to a source location chosen out of a discrete set of possible locations. We leverage large deviation techniques to obtain a bound on the localization probability of error and propose several methodologies for fusing sensor data to arrive at a localization decision, including a distributed one. We also address the problem of optimally placing sensors to minimize the localization probability of error. Our techniques are validated numerically using two different CBRN release simulators.

Subject Categories:

  • Statistics and Probability
  • Chemical, Biological and Radiological Warfare
  • Target Direction, Range and Position Finding
  • Nuclear Weapons

Distribution Statement:

APPROVED FOR PUBLIC RELEASE