1 October 1994 High-resolution algorithms for locating closely spaced objects via infrared focal-plane arrays
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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.
Yasemin C. Yardimci, 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 . Submission:
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