Algorithm Development - Polarization Analysis and Measurement


LADAR Light Reflection Analysis for Target Surface Characterization

As part of an STTR effort for the Army Research Office (ARO) SDI and its research partners, Washington University, Polaris Sensor Technologies and Rochester Institute of Technology (RIT) are conducting fundamental research to develop and demonstrate algorithms for characterizing surface material, texture and other pertinent information for multispectral LADAR-based remote target classification.  As part of this program we will design and build a Polarimetric bidirectional reflectance distribution function (BRDF) Instrumentation System (PBIS) (see diagram), which will overcome some significant shortcomings of current instrumentation; and we will use the PBIS to significantly expand the Mueller matrix data base.


Based on this expanded data base we will perform a Surface Characterization Analysis that will model the statistics of the spectropolarimetric returns from samples in the data base and determine optimal transmit wavelengths and polarization states for selected LADAR remote target classification scenarios.  We will develop algorithm suites for these scenarios that segment, detect and classify targets of importance and demonstrate these on synthetic multi-discriminant LADAR images (see sample segmented image with a personnel target detected) and measured images where available.  We will also determine the theoretical and practical performance limits for such algorithms via the models developed in the Surface Characterization Analysis and the principles of information theory and statistical pattern recognition.  Finally we will test the specific algorithm suites we develop using SDI’s LEAP LADAR ATR simulation.  For more information contact Steve Smith in SDI’s St. Louis office.


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