Paper
5 May 2010 Sensor-netting algorithm for CB threat mapping
Thomas Gruber, Larry Grim, Christopher Keiser, William Ginley
Author Affiliations +
Abstract
Large networks of disparate chemical/biological (CB) sensors, MET sensors, and intelligence, surveillance, and reconnaissance (ISR) sensors reporting to various command/display locations can lead to conflicting threat information, questions of alarm confidence, and a confused situational awareness. Sensor netting algorithms (SNA) are being developed to resolve these conflicts and to report high confidence consensus threat map data products on a common operating picture (COP) display. A phase I SBIR study to develop a conceptual design for a SNA was recently completed. Mathematical approaches for assigning uncertainty to incoming data streams, doing spatial/temporal correlation of point and standoff sensor data (via vector translation based tomography), estimating uncertainty for threat maps, and consistency checking between the consensus threat map result and the individual input data streams were developed. A set of simulation environment tools for testing the SNA, including a simple threat model, sensor models, and fused and un-fused COPs, were also prototyped during phase I. The SNA development and simulation based testing will continue during the phase II effort, which was just awarded.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Gruber, Larry Grim, Christopher Keiser, and William Ginley "Sensor-netting algorithm for CB threat mapping", Proc. SPIE 7665, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XI, 76650H (5 May 2010); https://doi.org/10.1117/12.850110
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Tomography

Algorithm development

Data modeling

Sensor networks

Signal processing

Data conversion

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