Paper
22 August 2000 Comparison of effects of sonar bandwidth for underwater target classification
Mahmood R. Azimi-Sadjadi, De Yao, Donghui Li, Arta A. Jamshidi, Gerald J. Dobeck
Author Affiliations +
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.
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Mahmood R. Azimi-Sadjadi, De Yao, Donghui Li, Arta A. Jamshidi, and Gerald J. Dobeck "Comparison of effects of sonar bandwidth for underwater target classification", Proc. SPIE 4038, Detection and Remediation Technologies for Mines and Minelike Targets V, (22 August 2000); https://doi.org/10.1117/12.396257
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Classification systems

Data fusion

Neural networks

Error analysis

Mining

Wavelets

Feature extraction

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