Comparison of Classifiers for Radar Emitter Type Identification
Date
1999-05
DOI
Authors
Granger, Eric
Grossberg, Stephen
Lavoie, Pierre
Rubin, Mark
Version
OA Version
Citation
Abstract
ARTMAP neural network classifiers are considered for the identification of radar emitter types from their waveform parameters. These classifiers can represent radar emitter type classes with one or more prototypes, perform on-line incremental learning to account for novelty encountered in the field, and process radar pulse streams at high speed, making them attractive for real-time applications such as electronic support measures (ESM). The performance of four ARTMAP variants- ARTMAP (Stage 1), ARTMAP-IC, fuzzy ARTMAP and Gaussian ARTMAP - is assessed with radar data gathered in the field. The k nearest neighbor (kNN) and radial basis function (RDF) classifiers are used for reference. Simulation results indicate that fuzzy ARTMAP and Gaussian ARTMAP achieve an average classification rate consistently higher than that of the other ARTMAP classifers and comparable to that of kNN and RBF. ART-EMAP, ARTMAP-IC and fuzzy ARTMAP require fewer training epochs than Gaussian ARTMAP and RBF, and substantially fewer prototype vectors (thus, smaller physical memory requirements and faster fielded performance) than Gaussian ARTMAP, RBF and kNN. Overall, fuzzy ART MAP performs at least as well as the other classifiers in both accuracy and computational complexity, and better than each of them in at least one of these aspects of performance. Incorporation into fuzzy ARTMAP of the MT- feature of ARTMAP-IC is found to be essential for convergence during on-line training with this data set.
Description
License
Copyright 1999 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission.