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Proceedings Paper

Sensor modeling and demonstration of a multi-object spectrometer for performance-driven sensing
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Paper Abstract

A novel multi-object spectrometer (MOS) is being explored for use as an adaptive performance-driven sensor that tracks moving targets. Developed originally for astronomical applications, the instrument utilizes an array of micromirrors to reflect light to a panchromatic imaging array. When an object of interest is detected the individual micromirrors imaging the object are tilted to reflect the light to a spectrometer to collect a full spectrum. This paper will present example sensor performance from empirical data collected in laboratory experiments, as well as our approach in designing optical and radiometric models of the MOS channels and the micromirror array. Simulation of moving vehicles in a highfidelity, hyperspectral scene is used to generate a dynamic video input for the adaptive sensor. Performance-driven algorithms for feature-aided target tracking and modality selection exploit multiple electromagnetic observables to track moving vehicle targets.

Paper Details

Date Published: 27 April 2009
PDF: 12 pages
Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73340J (27 April 2009); doi: 10.1117/12.819265
Show Author Affiliations
John P. Kerekes, Rochester Institute of Technology (United States)
Michael D. Presnar, Rochester Institute of Technology (United States)
Air Force Institute of Technology (United States)
Kenneth D. Fourspring, Rochester Institute of Technology (United States)
Zoran Ninkov, Rochester Institute of Technology (United States)
David R. Pogorzala, Rochester Institute of Technology (United States)
Alan D. Raisanen, Rochester Institute of Technology (United States)
Andrew C. Rice, Numerica Corp. (United States)
Juan R. Vasquez, Numerica Corp. (United States)
Jeffrey P. Patel, Rochester Institute of Technology (United States)
Robert T. MacIntyre, Rochester Institute of Technology (United States)
Scott D. Brown, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7334:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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