• Title/Summary/Keyword: time-varying decorrelation filter

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A feedback cancellation algorithm with time delay and time-varying decorrelation filter for digital hearing aid (시간 지연과 시변 상관성 제거 필터를 이용한 디지털보청기용 궤환제거 알고리즘)

  • Lee, Sang-Min;Park, Young;Jung, Se-Young;Kim, In-Young;Kim, Sun-I
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.42 no.4 s.304
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    • pp.45-50
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    • 2005
  • In digital hearing aid system, one of the main problems is acoustic feedback which is known as howling because of miniaturization md high-gain amplification. In this paper, we proposed a feedback cancellation algorithm for hearing aid using time delay and time-varying decorrelation filter. The proposed algorithm has a kind of adaptive filter structure, which is combined with time delay and time-varying decorrelation filter to improve feedback cancellation. An all pass filter was implemented as the time-varying decorrelation filter using low frequency modulator. From the result of computer simulation, it is verified that the proposed algorithm has good ability to cancel feedback.

Improvement of Small Baseline Subset (SBAS) Algorithm for Measuring Time-series Surface Deformations from Differential SAR Interferograms (차분 간섭도로부터 지표변위의 시계열 관측을 위한 개선된 Small Baseline Subset (SBAS) 알고리즘)

  • Jung, Hyung-Sup;Lee, Chang-Wook;Park, Jung-Won;Kim, Ki-Dong;Won, Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.24 no.2
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    • pp.165-177
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    • 2008
  • Small baseline subset (SBAS) algorithm has been recently developed using an appropriate combination of differential interferograms, which are characterized by a small baseline in order to minimize the spatial decorrelation. This algorithm uses the singular value decomposition (SVD) to measure the time-series surface deformation from the differential interferograms which are not temporally connected. And it mitigates the atmospheric effect in the time-series surface deformation by using spatially low-pass and temporally high-pass filter. Nevertheless, it is not easy to correct the phase unwrapping error of each interferogram and to mitigate the time-varying noise component of the surface deformation from this algorithm due to the assumption of the linear surface deformation in the beginning of the observation. In this paper, we present an improved SBAS technique to complement these problems. Our improved SBAS algorithm uses an iterative approach to minimize the phase unwrapping error of each differential interferogram. This algorithm also uses finite difference method to suppress the time-varying noise component of the surface deformation. We tested our improved SBAS algorithm and evaluated its performance using 26 images of ERS-1/2 data and 21 images of RADARSAT-1 fine beam (F5) data at each different locations. Maximum deformation amount of 40cm in the radar line of sight (LOS) was estimated from ERS-l/2 datasets during about 13 years, whereas 3 cm deformation was estimated from RADARSAT-1 ones during about two years.