Paper
13 June 2014 Radar target identification using various nearest neighbor techniques
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Abstract
Radar target identification using decision-theoretic distance based methods have long been used for classifying unknown non-cooperative radar targets using their Radar Cross Section (RCS). This study revisits this subject using the recently developed Large Margin Nearest Neighbor (LMNN) technique in addition to other traditional nearest neighbor methods. Radar target recognition has been defined by two performance limiting issues namely 1) azimuth ambiguity (and/or erroneous estimation of target azimuth) and 2) presence of extraneous scatterers along the target. This study examines these different scenarios and highlights any of the benefits that LMNN may add to the radar target classification problem.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
I. Jouny "Radar target identification using various nearest neighbor techniques", Proc. SPIE 9090, Automatic Target Recognition XXIV, 90900B (13 June 2014); https://doi.org/10.1117/12.2049839
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KEYWORDS
Radar

Target recognition

Backscatter

Signal to noise ratio

Classification systems

Data modeling

Performance modeling

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