HRR Signature Classification using Syntactic Pattern Recognition

• Published in: 2008 IEEE Aerospace Conference pp. 1 - 9
• Main Authors: Turnbaugh, M.A., Bauer, K.W., Oxley, M.E., Miller, J.O.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 2008
• Subjects: Biographies; Cities and towns; Counting circuits; Distributed control; Formal languages; Object detection; Pattern recognition; Prototypes; Testing
• ISBN: 1424414873; 9781424414871
• ISSN: 1095-323X; 2996-2358
• DOI: 10.1109/AERO.2008.4526421

An automatic target classification system contains a classifier that maps a vector of real numbered features characteristic to a specific target onto a class label. Other features can be a string of symbols or alphabets that may not involve real numbers at all. There are certain orderings of the symbols in the strings governed by syntax rules, thus, generating a language, (that is, a collection of strings). Thus, a classifier would map a string to a class label. Such a classifier is called a syntactical classifier and varies greatly from its vector space counter part. This paper will give an overview of the construction of a grammar that generates a language then shows how they fit into a syntactical classification system. The performances of two syntactical classification systems with two and ten labels respectively are presented via confusion matrices. Experiments performed on public release DCS database indicate this approach has sufficient power to perform target detection using HRR signatures.