A study on the active sonar reverberation suppression method based on non-negative matrix factorization with beta-divergence function

Seokjin Lee; Geunhwan Kim

doi:10.7776/ASK.2024.43.4.369

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2024 Vol.43, Issue 4 Next Page

Research Article

A study on the active sonar reverberation suppression method based on non-negative matrix factorization with beta-divergence function 베타-발산 함수를 활용한 비음수 행렬 분해 기반의 능동 소나 잔향 제거 기법에 대한 연구

31 July 2024. pp. 369-382

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Abstract

To suppress the reverberation in the active sonar system, the non-negative matrix factorization-based reverberation suppression methods have been researched recently. An estimation loss function, which makes the multiplication of basis matrices same as the input signals, has to be considered to design the non-negative matrix factorization methods, but the conventional method simply chooses the Kullback-Leibler divergence as the loss function without any considerations. In this paper, we examined that the Kullback-Leibler divergence is the best loss function or there is the other loss function enhancing the performance. First, we derived a modified reverberation suppression algorithm using the generalized beta-divergence function, which includes the Kullback-Leibler divergence. Then, we performed Monte-Carlo simulations using synthesized reverberation for the modified reverberation suppression method. The results showed that the Kullback-Leibler divergence function (β = 1) has good performances in the high signal-to-reverberation environments, but the intermediate function (β = 1.25) between Kullback-Leibler divergence and Euclidean distance has better performance in the low signal-to-reverberation environments.

Keywords

Reverberation suppression

Non-negative matrix factorization

Loss function

Beta-divergence

능동 소나 시스템에서 잔향을 제거하기 위하여 최근 비음수 행렬 분해 기법을 활용한 잔향 제거 알고리즘이 고안된 바 있다. 비음수 행렬 분해 알고리즘을 설계하기 위해서는 분해된 기저 행렬의 곱이 원본 신호와 같도록 유도하는 추정 비용 함수가 필요한데, 기존의 연구에서는 이에 대한 고찰이 없이 쿨백-라이블러 발산 함수를 활용하였다. 본 논문에서는 쿨백-라이블러 발산 함수의 선택이 좋은 선택이었는지, 혹은 성능을 개선할 수 있는 다른 추정 비용 함수가 있는지 연구하고자 하였다. 이를 위하여, 먼저 쿨백-라이블러 함수를 포함하여 일반화된 베타-발산 함수를 활용하여 수정된 잔향 제거 알고리즘을 제안하였다. 그리고 수정된 잔향 제거 알고리즘에 대해 합성된 잔향 신호를 활용한 몬테-카를로 시뮬레이션을 수행하였다. 그 결과 높은 신호대잔향비 환경에서는 쿨백-라이블러 발산 함수(β = 1)가 좋은 성능을 보이지만, 낮은 신호대잔향비 환경에서는 쿨백-라이블러 발산 함수와 유클리드 거리의 중간 특성을 가지는 함수(β = 1.25)가 더 좋은 성능을 보이는 것을 확인하였다.

키워드

잔향 제거

비음수 행렬 분해

비용 함수

베타-발산

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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 : 43
No :4
Pages :369-382
Received Date : 2024-04-22
Revised Date : 2024-07-16
Accepted Date : 2024-07-23
DOI :https://doi.org/10.7776/ASK.2024.43.4.369

The Journal of the Acoustical Society of KoreaISSN:1225-4428(Print) 2287-3775(Online)한국음향학회

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