Physical Sciences and Mathematics Commons^™

Detecting Clustered Chem/Bio Signals In Noisy Sensor Feeds Using Adaptive Fusion, Randy Paffenroth, Scott Lundberg, Chris Calderon

Randy C. Paffenroth

Chemical and biological monitoring systems are faced with the challenge of detecting weak signals from contam- inants of interest while at the same time maintaining extremely low false alarm rates. We present methods to control the number of false alarms while maintaining power to detect; evaluating these methods on a fixed sensor grid. Contaminants are detected using signals produced from underlying sensor-specific detection algorithms. By learning from past data, an adaptive background model is constructed and used with a multi-hypothesis testing method to control the false alarm rate. Detection methods for chemical/biological releases often depend on specific models for release …