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Cornell S L Chun

Publications and source records attributed to Cornell S L Chun.

2 recordsLinked to original sources

Polarimetric laser radar target classification.

Imaging laser radar (ladar) systems have been developed for automatic target identification in surveillance systems. Ladar uses the range value at the target pixels to estimate the target's 3-D shape and identify the target. For targets in clutter and partially hidden targets, there are ambiguities in determining which pixels are on target that lead to uncertainties in determining the target's 3-D shape. An improvement is to use the polarization components of the reflected light. We describe the operation and preliminary evaluation of a polarization diverse imaging ladar system. Using a combination of intensity, range, and degree of polarization, we are better able to identify and distinguish the target from other objects of the same class.

Algorithms↗

Automatic detection of small objects from their infrared state-of-polarization vectors.

A technique for automatic detection of targets from their infrared signature's state-of-polarization vector is described. The bounds on the Bayesian total probability of errors are estimated from the observed Stokes vector imagery and used as metrics for separating targets from background clutter. The performance of the proposed approach for objects under various geometries is studied in terms of receiver operating characteristic curves. The new results, which have been obtained from data from the U.S. Air Force's Infrared Modeling and Analysis polarimetric infrared simulation tool, indicate the usefulness of polarimetric infrared signatures for the automatic detection of small targets.

Journal Article↗