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Research Article

Comparison of independent component analysis algorithms for low-frequency interference of passive line array sonars

수동 선배열 소나의 저주파 간섭 신호에 대한 독립성분분석 알고리즘 비교

Juho Kim2
,
Hina Ashraf2
,
Chong-Hyun Lee2∗
,
Myoung Jun Cheong1
김 주호2
,
Ashraf Hina2
,
이 종현2∗
,
정 명준1
1국방과학연구소
2제주대학교
∗Corresponding Author
31 March 2019. pp. 177-183
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Abstract

In this paper, we proposed an application method of ICA (Independent Component Analysis) to passive line array sonar to separate interferences from target signals in low frequency band and compared performance of three conventional ICA algorithms. Since the low frequency signals are received through larger bearing angles than other frequency bands, neighboring beam signals can be used to perform ICA as measurement signals of the ICA. We use three ICA algorithms such as Fast ICA, NNMF (Non-negative Matrix Factorization) and JADE (Joint Approximation Diagonalization of Eigen-matrices). Through experiments on real data obtained from passive line array sonar, it is verified that the interference can be separable from target signals by the suggested method and the JADE algorithm shows the best separation performance among the three algorithms.

Keywords
Low-frequency passive sonar
Line array
Blind source separation
Independent component analysis

본 논문에서는 수동 선배열 소나의 저주파 영역에서 수신된 표적 신호로부터 간섭신호를 분리해 내기 위해 독립성분분석 알고리즘을 적용하는 방안을 제안하고 기존 알고리즘들의 성능을 비교해 보았다. 저주파 대역 신호의 경우 비교적 넓은 방위로부터 수신되기 때문에 인접 빔 신호를 관측신호로 활용하여 독립성분분석을 수행할 수 있다. 신호분리에 사용한 독립성분분석 알고리즘은 FastICA(Fast Independent Component Analysis), NNMF (Non-negative Matrix Factorization), JADE (Joint Approximation Diagonalization of Eigen-matrices)이다. 실측 선배열 수동소나신호를 이용하여 독립성분분석을 수행한 결과 제안한 방법으로 간섭신호분리가 가능함을 확인하였으며, JADE 알고리즘의 신호 분리 성능이 가장 우수한 것으로 나타났다.

키워드
저주파 수동 소나
선배열 센서
암묵신호분리
독립성분분석
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Information
  • Publisher :The Acoustical Society of Korea
  • Publisher(Ko) :한국음향학회
  • Journal Title :The Journal of the Acoustical Society of Korea
  • Journal Title(Ko) :한국음향학회지
  • Volume : 38
  • No :2
  • Pages :177-183
  • Received Date : 2018-11-06
  • Accepted Date : 2019-03-26
  • DOI :https://doi.org/10.7776/ASK.2019.38.2.177
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