High-resolution algorithms for locating closely spaced objects via     infrared focal-plane arrays

Yasemin C. Yardimci; James A. Cadzow

doi:10.1117/12.179388

1 October 1994 High-resolution algorithms for locating closely spaced objects via infrared focal-plane arrays

Yasemin C. Yardimci, James A. Cadzow

Author Affiliations +

Optical Engineering, Vol. 33, Issue 10, (October 1994). https://doi.org/10.1117/12.179388

Abstract

The location of a single point source in infrared imaging is typically achieved through conventional methods such as centroiding. More challenging problems with multiple point sources require alternative location-finding methods with the potential of resolving closely spaced objects. The authors introduce an algorithm predicated on least-squared-error (LSE) modeling with a Gram-Schmidt orthogonalization step. Its noise performance is compared with two other high-resolution algorithms based on the eigendecomposition of the input data. Estimates obtained through the LSE modeling approached the Cramer-Rao lower bound for high signal-to-noise ratios. However, its performance is severely degraded in the presence of non-Gaussian noise. An outlier detection scheme that may be used in conjunction with the location and amplitude estimation procedure is described, Its effectiveness is demonstrated through Monte Carlo simulations.

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Yasemin C. Yardimci and James A. Cadzow "High-resolution algorithms for locating closely spaced objects via infrared focal-plane arrays," Optical Engineering 33(10), (1 October 1994). https://doi.org/10.1117/12.179388

Published: 1 October 1994

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