HMM-Based Underwater Target Classification with Synthesized Active Sonar Signals

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概要

• 論文の詳細を見る

• This paper deals with underwater target classification using synthesized active sonar signals. Firstly, we synthesized active sonar returns from a 3D highlight model of underwater targets using the ray tracing algorithm. Then, we applied a multiaspect target classification scheme based on a hidden Markov model to classify them. For feature extraction from the synthesized sonar signals, a matching pursuit algorithm was used. The experimental results depending on the number of observations and signal-to-noise ratios are presented with our discussions.

• （社）電子情報通信学会の論文
• 2011-10-01

著者

• Bae Keunsung

  School Of Electrical Engineering And Computer Science Kyungpook National University

• Kim Taehwan

  School Of Electrical Engineering And Computer Science Kyungpook National University

• Bae Keunsung

  School Of Electrical Engineering And Computer Sci. Kyungpook National Univ.

• Kim Taehwan

  School Of Electrical Engineering And Computer Sci. Kyungpook National Univ.

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• HMM-Based Underwater Target Classification with Synthesized Active Sonar Signals

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