Irma 5.2 multi-sensor signature prediction model

James Savage; Charles Coker; Bea Thai; Omar Aboutalib; Anthony Chow; Neil Yamaoka; Charles Kim

doi:10.1117/12.720898

10 May 2007 Irma 5.2 multi-sensor signature prediction model

James Savage, Charles Coker, Bea Thai, Omar Aboutalib, Anthony Chow, Neil Yamaoka, Charles Kim

Proceedings Volume 6564, Modeling and Simulation for Military Operations II; 656403 (2007) https://doi.org/10.1117/12.720898
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

The Irma synthetic signature prediction code is being developed by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN) to facilitate the research and development of multi-sensor systems. There are over 130 users within the Department of Defense, NASA, Department of Transportation, academia, and industry. Irma began as a high-resolution, physics-based Infrared (IR) target and background signature model for tactical weapon applications and has grown to include: a laser (or active) channel (1990), improved scene generator to support correlated frame-to-frame imagery (1992), and passive IR/millimeter wave (MMW) channel for a co-registered active/passive IR/MMW model (1994). Irma version 5.0 was released in 2000 and encompassed several upgrades to both the physical models and software; host support was expanded to Windows, Linux, Solaris, and SGI Irix platforms. In 2005, version 5.1 was released after an extensive verification and validation of an upgraded and reengineered active channel. Since 2005, the reengineering effort has focused on the Irma passive channel. Field measurements for the validation effort include the unpolarized data collection. Irma 5.2 is scheduled for release in the summer of 2007. This paper will report the validation test results of the Irma passive models and discuss the new features in Irma 5.2.

Citation Download Citation

James Savage, Charles Coker, Bea Thai, Omar Aboutalib, Anthony Chow, Neil Yamaoka, and Charles Kim "Irma 5.2 multi-sensor signature prediction model", Proc. SPIE 6564, Modeling and Simulation for Military Operations II, 656403 (10 May 2007); https://doi.org/10.1117/12.720898

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