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Proceedings Paper

Comparison of effects of sonar bandwidth for underwater target classification
Author(s): Mahmood R. Azimi-Sadjadi; De Yao; Donghui Li; Arta A. Jamshidi; Gerald J. Dobeck
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Paper Abstract

In this paper, two different data sets which use linear FM incident signals with different bandwidths, namely 40 KHz and 80 KHz, are used for benchmarking. The goal is to study the effects of using larger bandwidth for underwater target classification. The classification system is formed of several subsystems including preprocessing, a subband decomposition suing wavelet packets, linear predictive coding in subbands, feature selection and neural network classifier. The classification performance is demonstrated on ten noisy realizations of the data sets formed by adding synthesized reverberation effects with 12 dB signal-to- reverberation ratio. The ROC and the error location plots for these dat sets are generated. To compare the generalization and robustness of the system on these data sets, the error and classification rate statistics are generated using Monte Carlo simulations on a large set of noisy data. The results point to the fact that the wideband sonar provides better robustness property. Three-aspect fusion is also adopted which yields almost perfect classification performance. These issues will be thoroughly studied and analyzed in this paper.

Paper Details

Date Published: 22 August 2000
PDF: 11 pages
Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); doi: 10.1117/12.396257
Show Author Affiliations
Mahmood R. Azimi-Sadjadi, Colorado State Univ. (United States)
De Yao, Colorado State Univ. (United States)
Donghui Li, Colorado State Univ. (United States)
Arta A. Jamshidi, Colorado State Univ. (United States)
Gerald J. Dobeck, Naval Surface Warfare Ctr. (United States)

Published in SPIE Proceedings Vol. 4038:
Detection and Remediation Technologies for Mines and Minelike Targets V
Abinash C. Dubey; James F. Harvey; J. Thomas Broach; Regina E. Dugan, Editor(s)

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