Bayesian truthing and experimental validation in homeland security and defense

Tomasz Jannson; Thomas Forrester; Wenjian Wang; Andrew Kostrzewski; Ranjit Pradhan

doi:10.1117/12.2049027

29 May 2014 Bayesian truthing and experimental validation in homeland security and defense

Tomasz Jannson, Thomas Forrester, Wenjian Wang, Andrew Kostrzewski, Ranjit Pradhan

Proceedings Volume 9074, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XIII; 90740M (2014) https://doi.org/10.1117/12.2049027
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

In this paper we discuss relations between Bayesian Truthing (experimental validation), Bayesian statistics, and Binary Sensing in the context of selected Homeland Security and Intelligence, Surveillance, Reconnaissance (ISR) optical and nonoptical application scenarios. The basic Figure of Merit (FoM) is Positive Predictive Value (PPV), as well as false positives and false negatives. By using these simple binary statistics, we can analyze, classify, and evaluate a broad variety of events including: ISR; natural disasters; QC; and terrorism-related, GIS-related, law enforcement-related, and other C3I events.

Citation Download Citation

Tomasz Jannson, Thomas Forrester, Wenjian Wang, Andrew Kostrzewski, and Ranjit Pradhan "Bayesian truthing and experimental validation in homeland security and defense", Proc. SPIE 9074, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XIII, 90740M (29 May 2014); https://doi.org/10.1117/12.2049027

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