Hyperspectral Analysis paper, 2007

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Title

A hyperspectral model for target detection

Abstract:

In this paper an end-to-end hyperspectral imaging system model is described. This model is able to predict the performance of hyperspectral imaging sensors in the visible through to the short-wave infrared regime for sub-pixel targets.

The model represents all aspects of the system including the target signature and background, the atmosphere, the optical and electronic properties of the imaging spectrometer as well as details of the processing algorithms employed. It is efficient, allowing Monte-Carlo runs for sensitivity analysis or to sweep model parameters over a wide range. It is also capable of representing certain types of non-Gaussian hyperspectral clutter arising from heterogeneous backgrounds.

The capabilities of the model are demonstrated in this paper by considering the effect that different levels of heavy-tailed non-Gaussian clutter have on both anomaly detection and spectral matched-filter algorithms in terms of Receiver Operating Characteristic curves. Finally, some results from a preliminary validation exercise are presented.

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Authors:

M. Bernhardt, Waterfall Solutions, UK;
P. E. Clare, DSTL Farnborough, UK;
C. Cowell, Waterfall Solutions, UK;
M. I. Smith, Waterfall Solutions, UK;

Conference:

SPIE Defense and Security Symposium. Conference 6565 : Algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XIII