• Title/Summary/Keyword: Frequency Domain Beamforming

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Digital Beamforming in the Frequency Domain (주파수 영역 빔 형성에 관한 연구)

  • 박성범
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1996.06a
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    • pp.13-17
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    • 1996
  • 다수의 신호를 동시에 사용하는 경우에 나타나는 광대역 신호나 센서의 수와 형성하고자 하는 빔의 수가 많은 경우를 다루기 위해서는 주파수 영역 기법이 필요하다. FFT를 사용하는 낮은 샘플링 주파수에서도 시간 영역에서의 보간 방법보다 빠르게 정확한 시간 지연을 줄 수 있어 코히어런트 신호처리가 가능하다. 또한 특정 센서가 불량인 경우 보정이 상대적으로 용이하다는 장점을 가진다. 여러 가지 주파수 영역 빔형성 기법 중 계산량과 저장 용량면으로 효율적인 방법은 CZT와 FIR interpolation 방법이다. 또한, 공액 빔을 형성할 경우에는 Goertzel의 알고리듬을 이용하는 방법도 효율적이다.

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Implementation of Time-Domain Beamformer with Cummulative Processing in decomposed channel using Polynomial Interpolation (다항식 보간기법을 이용한 채널별 누적처리 시간영역 빔형성기 구현)

  • Lee, Jung-Hoon;Kim, Eui-Jun;Kwon, Dae-Yong
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.83-84
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    • 2008
  • It is efficient to use the time-domain beamforming to operate the various pulse with the different pulse length, frequency, bandwidth in active sonar system. In this paper, we propose a time-domain beamformer with the cumulative processing in the decomposed channel using the polynomial interpolation to solve the problem of the computational cost, high transmission data rate, and the lack of internal memory.

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Separation of passive sonar target signals using frequency domain independent component analysis (주파수영역 독립성분분석을 이용한 수동소나 표적신호 분리)

  • Lee, Hojae;Seo, Iksu;Bae, Keunsung
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.2
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    • pp.110-117
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    • 2016
  • 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.

A Microphone Array Beamforming Algorithm with Inverse Filtering of Relative Transfer Functions in Car Environments (상대전달함수의 역필터링을 이용한 자동차 환경에서의 마이크로폰 어레이 빔형성 기법)

  • Kang Hong-Goo;Hwang Youngsoo;Youn Dae-Hee;Han Chul-Hee
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.1
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    • pp.30-35
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    • 2006
  • In this paper. we Propose a frequency domain beamforming algorithm composed of inverse-filtering stages followed by a MVDR (Minimum-Variance Distortionless Response) beamformer or a GSC (Generalized Sidelobe Canceller). The proposed method is shown to require less complexity than the conventional RTF-MVDR and TF-GSC. respectively, and it is shown that the Proposed method is equivalent to the conventional RTF-MVDR and TF-GSC in optimum solution. In order to evaluate the performance of the Proposed method. speech recognition experiments are performed using the speech database recorded in a car. The Proposed method shows equal or slightly degraded Performance comparing to the conventional methods in terms of the speech recognition rate.

Noise source localization using comparison between candidate signal and beamformer output in time domain (시간 영역의 빔출력과 후보 신호 사이의 비교를 통한 소음원의 위치 추정)

  • Kim, Koo-Hwan;Kim, Yang-Hann
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2010.10a
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    • pp.543-543
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    • 2010
  • The objective of this research is estimating the location of interested sound source by using the similarity between a beamformer output in time domain and the candidate signal. The waveform of beamformer output at the location of sound source is similar with the waveform emitted by that source. To estimate the location of sound source by using this feature, we define quantified similarity between candidate signal and beamformer output. The candidate signal describes the signal which is generated by interested source. In this paper, similarity is defined by four methods. The two methods use time vector comparison, and the other two methods use time-frequency map or linear prediction coefficients. To figure out the results and performance of localization by using similarities, we demonstrate two conditions. The one is when two pure tone sources exist and the other condition is when several bird sounds exist. As a consequence, inner product with two time-vectors and structural similarity with spectrograms can estimate the locations of interest sound source.

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Input Signal Model Analysis for Adaptive Beamformer (적응 빔형성기의 입력신호 모델 분석)

  • Mun, Ji-Youn;Hwang, Suk-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.3
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    • pp.433-438
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    • 2017
  • Containing an Angle-of-Arrival(: AOA) estimation and interference suppression techniques, an adaptive beamformer is one of core techniques for the Signal Intelligence(: SIGINT) which collect various intelligence utilizing cutting edge devices including the radar and satellite. It generates a beam with the directivity in a corresponding direction, to efficiently receive a signal from the specific direction, using antenna array. In this paper, we present the received signal model including interference signals and noise, which can be applied to an input of the signal intelligence satellite system equipped with the AOA estimation and the interference cancellation techniques, and analysis the characteristics of various signals, which can be included in the proposed received signal model. This proposed signal model can be directly applied to the performance evaluation for a variety of beamforming techniques. Also, we verify the spectrum characteristic of the presented received signal model in the frequency domain through computer simulation examples.

Beamforming Method for Target Range Estimation Using Near Field Shading Function (근거리 쉐이딩 함수를 이용한 표적 거리 추정 빔형성 기법)

  • Choi, Joo-Pyoung;Lee, Won-Cheol
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.7
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    • pp.350-356
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    • 2008
  • In this paper, we propose shading functions to the appropriate focused beamforming for near-field target estimation. This near field shading functions are based on Chebychev and Manning windows. In order to obtain the optimum sensor weighting values with the help of the proposed shading technique, we assume that the sensor positions associated to the non-uniformly distributed array are precisely known. We calculate a series of sensor weighting values from the FFT operation of given shading functions in time domain. By applying the shading weights on the sensor array, we can see that the level of sidelobe becomes diminished and the performance of estimating range and azimuth gets improved. In addition, we propose a non-uniform structure in terms of frequency bands, which may minimize the attenuation of incoming signals.

Position Estimation of Underwater Acoustic Source Using Pulsed CW Signal (Pulsed CW 신호를 사용하는 수중 음원의 위치 추정을 위한 시간지연차 추정법)

  • 최영근;손권;도경철;김기만
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.7
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    • pp.514-520
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    • 2004
  • There are many techniques for underwater source localization. These are the methods based on TDOA (Time Difference Of Arrival) estimation. beamforming techniques and high resolution techniques, etc. In this Paper we estimate the underwater source position using MCPSP (Modified Cross Power Spectrum Phase) function that is calculated on frequency domain using sensors of small number. However, the performances of the localizing method based on MCPSP function drops greatly in the case of CW (Continuous Wave) signal . In this Paper we proposed the TDOA estimation method for pulsed CW signal. In the Proposed method we composed of new segment including a edge of ping. This segment was computed by short-time energy detection. With theoretical representation the performances of the proposed method were analyzed under various environment.

Own-ship noise cancelling method for towed line array sonars using a beam-formed reference signal (기준 빔 신호를 이용한 예인선배열 소나의 자함 소음 제거 기법)

  • Lee, Dan-Bi
    • The Journal of the Acoustical Society of Korea
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    • v.39 no.6
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    • pp.559-567
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    • 2020
  • This paper proposes a noise cancelling algorithm to remove own-ship noise for a towed array sonar. Extra beamforming is performed using partial channels of the acoustic array to get a reference beam signal robust to the noise bearing. Frequency domain Adaptive Noise Cancelling (ANC) is applied based on Normalized Least Mean Square (NLMS) algorithm using the reference beam. The bearing of own-ship noise is estimated from the coherence between the reference beam and input beam signals. Own-ship noise level is calculated using a beampattern of the noise with estimated steering angle, which prevents loss of a target signal by determining whether to update a filter so that removed signal level does not exceed the estimated noise level. Simulation results show the proposed algorithm maintains its performance when the own-ship gets out off its bearing 40 % more than the conventional algorithm's limit and detects the target even when the frequency of the target signal is same with the frequency of the own-ship signal.

Multi-channel input-based non-stationary noise cenceller for mobile devices (이동형 단말기를 위한 다채널 입력 기반 비정상성 잡음 제거기)

  • Jeong, Sang-Bae;Lee, Sung-Doke
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.7
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    • pp.945-951
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    • 2007
  • Noise cancellation is essential for the devices which use speech as an interface. In real environments, speech quality and recognition rates are degraded by the auditive noises coming near the microphone. In this paper, we propose a noise cancellation algorithm using stereo microphones basically. The advantage of the use of multiple microphones is that the direction information of the target source could be applied. The proposed noise canceller is based on the Wiener filter. To estimate the filter, noise and target speech frequency responses should be known and they are estimated by the spectral classification in the frequency domain. The performance of the proposed algorithm is compared with that of the well-known Frost algorithm and the generalized sidelobe canceller (GSC) with an adaptation mode controller (AMC). As performance measures, the perceptual evaluation of speech quality (PESQ), which is the most widely used among various objective speech quality methods, and speech recognition rates are adopted.