DOI QR코드

DOI QR Code

잔향 환경을 위한 기저집단 빔공간 비음수 행렬 분해 기반의 협대역 지속파 능동 소나 표적 탐지 기법

Target detection method of the narrow-band continuous-wave active sonar based on basis-group beamspace-domain nonnegative matrix factorization for a reverberant environment

  • 이석진 (경북대학교 전자공학부)
  • Lee, Seokjin (School of Electronics Engineering, Kyungpook National University)
  • 투고 : 2019.01.25
  • 심사 : 2019.05.20
  • 발행 : 2019.05.31

초록

본 논문에서 제안하는 알고리즘은 수중에서 협대역 지속파 능동 소나를 이용하여 표적 반향음을 탐지하는 문제를 다루고 있다. 능동 소나에서 표적 탐지를 위해 방사한 핑 신호는 주변의 많은 산란체에 의해 반사되는 신호를 만들어내며, 이를 잔향이라 한다. 본 논문에서 제안하는 알고리즘은 잔향 환경에서 낮은 도플러의 표적 반향음을 탐지하는 것을 목표로 한다. 제안하는 알고리즘은 빔공간 다채널 비음수 행렬 분해 기법을 기반으로 하여 방위, 주파수, 시간 기저를 추정하며, 특히 기저를 두 개의 기저집단 -잔향음 기저집단과 반향음 기저집단으로 나누어 독립적으로 추정한다. 제안하는 알고리즘의 성능을 평가하기 위하여 합성된 잔향 신호를 이용하여 시뮬레이션을 진행하였으며, 시뮬레이션 결과 제안하는 알고리즘이 기존의 알고리즘에 비해 향상된 성능을 보이는 것을 확인할 수 있었다.

The proposed algorithm deals with a detection problem of target echo for narrow-band continuous-wave active sonar in the underwater environment in this paper. In the active sonar systems, ping signal emitted for target detection produces a signal that consists of multiple reflections by many scatterers around, which is called reverberation. The proposed algorithm aims to detect the low-Doppler target echo in the reverberant environment. The proposed algorithm estimates the bearing, frequency, and temporal bases based on beamspace-domain multichannel nonnegative matrix factorization. In particular, the bases are divided into two basis groups - the reverberation group and the echo group, then the basis groups are estimated independently. In order to evaluate the proposed algorithm, a simulation with synthesized reverberation was performed. The results show that the proposed algorithm has enhanced performance than the conventional algorithms.

키워드

GOHHBH_2019_v38n3_290_f0001.png 이미지

Fig. 1. Graphs of simulated reverberation displayed in (a) a time-frequency domain and (b) a frequency-bearing domain. The regions A, B, and C mean very-low-Doppler, low-Doppler, and high-Doppler zones, respectively.

GOHHBH_2019_v38n3_290_f0002.png 이미지

Fig. 2. A block diagram of proposed target detection algorithm.

GOHHBH_2019_v38n3_290_f0003.png 이미지

Fig. 3. Basis-group multichannel nonnegative matrix factorization model for the proposed algorithm.

GOHHBH_2019_v38n3_290_f0004.png 이미지

Fig. 4. Examples of estimated (a) temporal, (b) frequency, (c) bearing basis matrices without own Doppler suppression, and (d) bearing basis matrix with own Doppler suppression. The white dashed lines and the gray dotted line indicate the range of ground truth and selected target basis, respectively.

GOHHBH_2019_v38n3_290_f0005.png 이미지

Fig. 5. Detection performances of (a) frequency, (b) time, and (c) bearing of the target echo based on F-measure.

GOHHBH_2019_v38n3_290_f0006.png 이미지

Fig. 6. Estimated results of the frequency basis matrices of (a) the conventional BD-MC-NMF-based method and (b) the proposed method, respectively, and the temporal basis matrices of the (c) the conventional BD-MC-NMF-based method and (d) the proposed method, respectively.

GOHHBH_2019_v38n3_290_f0007.png 이미지

Fig. 7. Detection performances of (a) frequency, (b) time, and (c) bearing of the target echo based on F-measure, when the beamwidth is 1°.

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