Diffusion Maps and Geometric Harmonics for Automatic Target Recognition (ATR). Volume 2. Appendices
Final rept. 23 Nov 2004-31 Oct 2007
YALE UNIV NEW HAVEN CT DEPT OF COMPUTER SCIENCE
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Geometric harmonics provides a framework for taking data in high-dimensional measurement spaces and embedding them in low dimensional Euclidean space according to a similarity measure. Euclidean coordinates then characterize the manifold on or near which the data live. Our goal in this project is to develop this manifold as a mechanism for integrating data from different sensors to facilitate automatic recognition. During the tenure of this research grant, we were able to formulate and complete the first series of experiments on embedded fusion. The resulting experiment on integrating voice and audio streams was extremely successful. This definitely revealed the potential for this approach and set the stage for further experiments. The problem formulation has been completed and confirmed with an experiment on the integration of audio and video streams. Researchers at AFRL, Wright-Patterson Air Force Base, have received a first version of the software, and are attempting to apply it to radar signal interpretation.
- Target Direction, Range and Position Finding