Pattern Representations and Syntactic Classification of Radar Measurements of Commercial Aircraft February 1990 (vol. 12 no. 2) pp. 204-211
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.44406
A syntactic pattern recognition system is evaluated for applications to radar signal identification. Three different level-crossing-based pattern representation algorithms are considered. The utility of the resulting symbolic pattern representations is assessed by evaluating the performance of a maximum-likelihood classifier when the observed symbol strings are used as inputs to the decision algorithm. A syntax analysis algorithm is derived from the likelihood function classifier. Performance results of simulated classification experiments for both maximum-likelihood and language-theoretic classifiers are presented. [1] B. Bhanu, "Automatic target recognition: State of the art survey,"IEEE Trans. Aerosp. Electron. Syst., vol. AES-22, no. 4, pp. 364- 379, July 1986.
Index Terms:
computerised pattern recognition; radar measurements; commercial aircraft; syntactic pattern recognition; radar signal identification; symbolic pattern representations; maximum-likelihood classifier; symbol strings; decision algorithm; language-theoretic classifiers; artificial intelligence; computerised pattern recognition; radar measurement
Citation:
O.S. Sands, F.D. Garber, "Pattern Representations and Syntactic Classification of Radar Measurements of Commercial Aircraft," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 2, pp. 204-211, Feb. 1990, doi:10.1109/34.44406 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||