한국음향학회지 (The Journal of the Acoustical Society of Korea)

  • 제38권2호
  • /
  • Pages.168-176
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  • 2019
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  • 1225-4428(pISSN)
  • /
  • 2287-3775(eISSN)
한국음향학회 (The Acoustical Society of Korea)
권호 표지
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주파수-파수 스펙트럼과 라돈변환을 이용한 희소 배열 기반 방위추정 기법 연구

Direction finding based on Radon transform in frequency-wavenumber domain with a sparse array

  • 최용화 (한국해양대학교 수중운동체특화연구센터) ;
  • 김동현 (한국해양과학기술원-한국해양대학교 해양과학기술전문대학원) ;
  • 김재수 (한국해양대학교 해양공학과)
  • 투고 : 2018.11.06
  • 심사 : 2019.03.27
  • 발행 : 2019.03.31
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⟨ 이전 논문 다음 논문 ⟩

초록

배열의 설계주파수보다 높은 주파수의 표적신호가 수신되는 경우 공간 에일리어싱에 의해 빔형성에 모호성이 발생한다. 이를 극복하기 위해 Abadi가 차주파수 빔형성 기법을 제안하였다. 하지만 차주파수 빔형성 기법은 차주파수의 값에 따라 최소한의 대역폭이 필요한 제약조건이 있다. 본 논문에서는 주파수-파수 스펙트럼의 특성과 라돈변환을 이용하여 공간 에일리어싱이 발생하는 표적신호의 방위를 추정하는 기법을 제안한다. 제안된 기법은 대역을 가지는 신호의 주파수 대역 내에서 방위추정의 모호성은 발생하지 않고, 표적의 방위를 추정할 수 있다. 하지만 대역을 가지는 신호에만 적용이 가능한 제약조건이 있다. 광대역 신호에 대해 시뮬레이션을 수행하여 알고리즘을 구현하고, 이를 SAVEX15 (Shallow Water Acoustic Variability EXperiment 2015)의 딱총새우 소음신호를 이용하여 차주파수 빔형성 기법의 결과와 비교 검증하였다.

When an array receives a signal with a frequency higher than the design frequency, there is an ambiguity in beamforming due to spatial aliasing. In order to overcome this problem, Abadi proposed frequency-difference beamforming. However, there is a constraint that the minimum frequency bandwidth is required according to the value of the difference frequency. In this paper, we propose a method to find the direction of the target signal with spatial aliasing based on the frequency-wavenumber spectrum combined with Radon transform. The proposed method can estimate the direction of the target without ambiguities when the signal has nonnegligible bandwidth. We tested the algorithm by simulating a broadband signal and verified the results with the frequency-difference beamforming method using SAVEX15 (Shallow Water Acoustic Variability EXperiment 2015)'s shrimp noise data.

키워드

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Fig. 1. Direction of CW signals and geometry of VLA (Vertical Line Array).

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Fig. 2. Frequency-wavenumber spectrum from 3-directions CW signal.

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Fig. 3. LFM signal for free space simulation.

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Fig. 4. Frequency-wavenumber spectrum from 1-direction LFM signal.

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Fig. 7. Applying Radon transform to frequency wavenumber spectrum.

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Fig. 8. Frequency-wavenumber spectrum from 3-directions LFM signal.

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Fig. 9. The result of the Radon transform when the Radon domain is set to 2 kHz

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Fig. 10. Shrimp signal in SAVEX15.

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Fig. 11. Spectrogram of shrimp signal (ch #16, direct path).

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Fig. 12. The frequency-wavenumber spectrum of the shrimp signal.

GOHHBH_2019_v38n2_168_f0013.png 이미지

Fig. 13. The result of the Radon transform when the Radon domain is set to 20 kHz.

GOHHBH_2019_v38n2_168_f0014.png 이미지

Fig. 14. The result of CBF (upper) and FDBF (lower) in frequency domain.

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Fig. 15. Comparison among CBF, FDBF and the proposed algorithm.

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Fig. 16. Comparison of results of frequency-difference beamforming according to difference frequency components.

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Fig. 5. Beam pattern in 2 kHz.

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Fig. 6. Projection data.[15]

참고문헌

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