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Proceedings Paper

Temperature discrimination of closely spaced objects
Author(s): Jerzy Nowakowski
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Paper Abstract

Temperature discrimination of closely spaced objects (CSO's) may be a difficult problem for passive sensors with limited spatial resolution. In this paper, we establish limits on the accuracy of temperature estimation of two closely spaced point targets having different temperatures, when such targets are observed in several spectral bands. The effect of a priori knowledge (e.g., emissivities, areas, earthshine) on temperature estimation is discussed. An analytical framework is developed to establish the fundamental limits on temperature resolution of a passive system, and to obtain a quantitative understanding of the dependence of estimation accuracy on parameters describing the targets (e.g., temperatures, emissivities), and on the number of photons available. We examine the sensitivity of temperature estimation to target parameters and the selection of the number and location of the spectral bands in which the measurements are made. The advantage of partial resolution of targets in one or more spectral bands is examined. The analysis is carried out for Poisson photon statistics. The Cramr-Rao bounds (CRB) are computed for the estimation of various parameters describing a two point source, and to the sensitivity of the CRB to different parameter values, changes in the number of unknown parameters, and the selection of spectral bands is examined. The results presented provide a more comprehensive definition of temperature resolution and can be useful in astronomy, multispectral scene analysis, and other commercial and military applications.

Paper Details

Date Published: 1 October 1990
PDF
Proc. SPIE 1305, Signal and Data Processing of Small Targets 1990, (1 October 1990); doi: 10.1117/12.2321757
Show Author Affiliations
Jerzy Nowakowski, Riverside Research Institute (United States)


Published in SPIE Proceedings Vol. 1305:
Signal and Data Processing of Small Targets 1990
Oliver E. Drummond, Editor(s)

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