Exploiting Multipath for Efficient Target Classification Navy SBIR FY2010.2 Sol No.: Navy SBIR FY2010.2 Topic No.: N102-139 Topic Title: Exploiting Multipath for Efficient Target Classification Proposal No.: N102-139-0180 Firm: Signal Innovations Group, Inc. 1009 Slater Rd. Suite 200 Durham, North Carolina 27703 Contact: James Baxter Phone: (919) 323-4813 Web Site: www.siginnovations.com Abstract: Automatic target recognition(ATR) for tactical military targets is a very challenging problem, particularly when the number of observed aspects of a target is subject to the operational constraints of the sensor platform. When the target is situated in the presence of a complicated background medium, such as in urban or hilly settings, the observed signals might be deformed significantly, thus the classification performance suffers. However, it can be proved that the observed signals of a target in the presence of a complicated environment are linear combination of the target's scattering fields situated in free space. Thus the target is actually observed from multiple aspects for each such measurement. On the other hand, the angle-dependent target responses are typically a smooth function of aspect angles, and therefore are highly compressible. In this Phase I, the concept of in situ compressive sensing (CS) will be employed to exploit the multipath response. ATR can subsequently be performed with a relatively smaller number of observations within compact aspect range. The target RCS/far fields in free space will be simulated via multilevel fast multipole algorithm (MLFMA), and various random projection matrices will be generated to simulate simple and complicated environments, respectively. Sparse Bayesian classifiers will be used to assess the classification performance and efficiency of CS compared with conventional approaches. Benefits: The environmental multipath can be exploited via in situ CS thus the specified target classification performance can be achieved with a relatively smaller number of observations. Similarly, by exploiting the surrounding structure, the effective aperture of an antenna array can be enhanced significantly. Therefore, the proposed approach in this Phase I can find many applications in areas including automatic target recognition, maritime navigation and control, multiple air target tracking, detection of unexploded ordnances, medical screening, air traffic control, municipal and private security, and surveillance systems, as well as natural-resource exploration. The success of the in situ CS will help satisfy the needs of current and prospective clients, including the Navy, the Air Force, the Army, and Homeland Security. We are also investigating non-government applications of this technology in areas such as medical imaging and municipal public safety and security. Return