Separation of passive sonar target signals using frequency domain independent component analysis

주파수영역 독립성분분석을 이용한 수동소나 표적신호 분리

Lee, Hojae;Seo, Iksu;Bae, Keunsung

  • Received : 2015.10.02
  • Accepted : 2015.12.25
  • Published : 2016.03.31


Passive sonar systems detect and classify the target by analyzing the radiated noises from vessels. If multiple noise sources exist within the sonar detection range, it gets difficult to classify each noise source because mixture of noise sources are observed. To overcome this problem, a beamforming technique is used to separate noise sources spatially though it has various limitations. In this paper, we propose a new method that uses a FDICA (Frequency Domain Independent Component Analysis) to separate noise sources from the mixture. For experiments, each noise source signal was synthesized by considering the features such as machinery tonal components and propeller tonal components. And the results of before and after separation were compared by using LOFAR (Low Frequency Analysis and Recording), DEMON (Detection Envelope Modulation On Noise) analysis.


Passive sonar;Separation of target signals;Independent component anlaysis;Independent vector analysis


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Grant : BK21플러스

Supported by : 경북대학교