Public Reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comment regarding this burden estimates or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and The views, opinions and/or findings contained in this teport are thcJ&e^pf the authors) and should not be construed as an official Department of the Army position, policy or decision, unless so designated by other documentation. The efforts of CIS during the 1999-2001 years built on the mathematical foundations that have been emerging over the past several decades. Examining a broad class of remote sensing problems, we have been establishing the fundamental framework for the inference and representation of structures in complex systems and scenes of complex shapes proceeding from the representation of complex scenes, to image formation and sensor modeling, and culminating in the development of the fundamental underpinnings for optimal decision/recognition strategies in image understanding and ATR. Within this framework, we are establishing the methodology for establishing the limits of performance of detection, identification and recognition algorithms solving remote sensing problems involving data from multiple active and passive sensors. The Web site continues to receive 5000-7000 visitors a month and has distributed databases to an average of 500 unique visitors each month. CIS members have submitted for publication 6 papers, published 34 papers, gave 32 talks, and have been involved in numerous meetings with the Army and DOD. CIS has a publications index of 253 papers in the areas of target recognition, deformable geometry, image formation and sensor modeling, tomographic imaging, computational vision, inference and optimization, adaptation and learning, multiple sensor fusion, clutter modeling, and performance bounds.
SUBJECT TERMS
Automatic Target Recognition
Summary of the most important resultsThe major results in the Center: 1. Performance bounds and metrics: We have established Performance Bounds and Metrics for pose estimation and identification. We have established for pose the MMSE estimator, and established curves of performances for multiple sensors, FLIR, LADAR, HRR, VIDEO.We have established the tight connection between estimator bounds and ID bounds. Exponential ID bounds are determined by estimator accuracy bounds.
Sensor fusion:We have established the optimum methodology for combining information optimally from multiple sensors. Estimation and ID bounds have been calculated for combinations of HRR, LADAR, and FLIR.3. FLIR signature variation: We have established a methodology for accommodating the infinit...