TY - JOUR
T1 - A sequential detector for biochemical release in realistic environments
AU - Ortner, Mathias
AU - Nehorai, Arye
N1 - Funding Information:
Manuscript received January 23, 2006; revised September 21, 2006. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Carlos H. Muravchik. This work was supported by the National Science Foundation under Grant CCR-0330342.
PY - 2007/8
Y1 - 2007/8
N2 - We develop a sequential detector for the release of a biochemical substance, with potential applications in environmental security. The proposed detector provides online detection of the appearance of a biochemical source in realistic complex environments. To obtain optimal performance, we use an integrated approach combining statistical analysis of measurements given by an array of biochemical sensors with a physical model of the dispersion, amenable to arbitrary geometries and wind turbulence. We first focus on formulating a detector that is applicable in the presence of unknown source parameters (e.g., release time, intensity, and location). We then derive a bound on the expected delay before a false detection in order to select the threshold of the test. For a fixed false-alarm rate, we obtain the detection probability of a release as a function of its location and initial concentration. Numerical examples illustrate the applicability of our methods to real-world scenarios of an urban area and indoor ventilation duct.
AB - We develop a sequential detector for the release of a biochemical substance, with potential applications in environmental security. The proposed detector provides online detection of the appearance of a biochemical source in realistic complex environments. To obtain optimal performance, we use an integrated approach combining statistical analysis of measurements given by an array of biochemical sensors with a physical model of the dispersion, amenable to arbitrary geometries and wind turbulence. We first focus on formulating a detector that is applicable in the presence of unknown source parameters (e.g., release time, intensity, and location). We then derive a bound on the expected delay before a false detection in order to select the threshold of the test. For a fixed false-alarm rate, we obtain the detection probability of a release as a function of its location and initial concentration. Numerical examples illustrate the applicability of our methods to real-world scenarios of an urban area and indoor ventilation duct.
KW - Biochemical dispersion
KW - Detection
KW - Feynman-Kac
KW - Monte Carlo
KW - Realistic framework
KW - Sensor array processing
KW - Sequential detection
UR - https://www.scopus.com/pages/publications/34547878335
U2 - 10.1109/TSP.2007.894385
DO - 10.1109/TSP.2007.894385
M3 - Article
AN - SCOPUS:34547878335
SN - 1053-587X
VL - 55
SP - 4173
EP - 4182
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 8
ER -