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21 September 2004Classification of underwater mine-like and non-mine-like objects using canonical correlations
A feature extraction method for underwater target classification
is developed that exploits the linear dependence (coherence)
between two sonar returns. A canonical coordinate decomposition is
applied to resolve two consecutive acoustic backscattered signals
into their dominant canonical coordinates. The corresponding
canonical correlations are selected as features for classifying
mine-like from non-mine-like objects. Test results are based on a
subset of a wideband data set that has been collected at the
Applied Research Lab (ARL), University of Texas (UT)-Austin. This
subset includes returns from different mine-like and non-mine-like
objects at several aspect angles in a smooth bottom condition. The
test results demonstrate the potential of the canonical
correlation-based feature extraction for underwater target
classification and indicate that canonical correlation features
are indeed robust to variations in aspect angle.
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Ali Pezeshki, Mahmood R. Azimi-Sadjadi, Louis L. Scharf, "Classification of underwater mine-like and non-mine-like objects using canonical correlations," Proc. SPIE 5415, Detection and Remediation Technologies for Mines and Minelike Targets IX, (21 September 2004); https://doi.org/10.1117/12.543169