Automatic target recognition, or target discrimination, is an ever-increasing need in both tactical and strategic engagements. Complex imaging systems, such as those based on adaptive optics compensation, are proven but expensive. This paper addresses a specific problem amenable to non-imaging distinction of targets, specifically symmetric and oblong. The approach is to illuminate a target with a rotating oblong beam, either in the near field (tactical) or far field (strategic). The returns from a symmetric object in the absence of pointing errors will be constant while returns from an oblong object will produce a sinusoidal signal, thus distinguishing the objects without imaging. This paper addresses the result of illumination with an oblong beam, starting with a pure beam, a beam corrupted by atmospheric effects and a beam affected by pointing errors referred to as jitter and boresight.
On September 1, 2003, Nukove Scientific Consulting, together with partner New Mexico State University, began work on a Phase 1 Small Business Technology TRansfer (STTR) grant from the United States Air Force Office of Scientific Research (AFOSR). The purpose of the grant was to show the feasibility of taking Nukove's pointing estimation technique from a post-processing tool for estimation of laser system characteristics to a real-time tool usable in the field. Nukove's techniques for pointing, shape, and OCS estimation do not require an imaging sensor nor a target board, thus estimates may be made very quickly. To prove feasibility, Nukove developed an analysis tool RHINO (Real-time Histogram Interpretation of Numerical Observations) and successfully demonstrated the emulation of real-time, frame-by-frame estimation of laser system characteristics, with data streamed into the tool and the estimates displayed as they are made. The eventual objective will be to use the frame-by-frame estimates to allow for feedback to a fielded system. Closely associated with this, NMSU developed a laboratory testbed to illuminate test objects, collect the received photons, and stream the data into RHINO. The two coupled efforts clearly demonstrate the feasibility of real-time pointing control of a laser system.
On September 1, 2003, Nukove Scientific Consulting, together with partner New Mexico State University (NMSU), began work on a Phase I Small Business Technology TRansfer (STTR) grant from the Air Force Office of Scientific Research (AFOSR). The purpose of the grant was to show the feasibility of taking Nukove's pointing estimation technique from a post-processing tool for estimation of laser system characteristics to a real-time tool usable in the field. Nukove's techniques for pointing, shape, and OCS estimation do not require an imaging sensor nor a target board, thus estimates may be made very quickly. To prove feasibility, Nukove developed an analysis tool RHINO (Real-time Histogram Interpretation of Numerical Observations) and successfully demonstrated the emulation of real-time, frame-by-frame estimation of laser system charcteristics, with data streamed into the tool and the estimates displayed as they are made. The eventual objective will be to use the frame-by-frame estimates to allow for feedback to a fielded system. Closely associated with this, NMSU has developed a laboratory testbed to illuminate test objects, collect the received photons, and stream the data into RHINO. The two coupled efforts clearly demonstrate the feasibility of real-time pointing control of a laser system.
When a laser beam propagates through the atmosphere, it is subject to corrupting influences including mechanical vibrations, turbulence and tracker limitations. As a result, pointing errors can occur, causing loss of energy or signal at the target. Nukove Scientific Consulting has developed algorithms to estimate these pointing errors from the statistics of the return photons from the target. To prove the feasibility of this approach for real-time estimation, an analysis tool called RHINO was developed by Nukove. Associated with this effort, New Mexico State University developed a laboratory testbed, the ultimate objective being to test the estimation algorithms under controlled conditions and to stream data into RHINO to prove the feasibility of real-time operation. The present paper outlines the description of this testbed and the results obtained through RHINO when the testbed was used to test the estimation approach.
Conference Committee Involvement (3)
Advanced Signal Processing Algorithms, Architectures, and Implementations XV
2 August 2005 | San Diego, California, United States
Advanced Wavefront Control: Methods, Devices, and Applications
6 August 2003 | San Diego, California, United States
Quantum Communications and Quantum Imaging
6 August 2003 | San Diego, California, United States
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