• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.255-260
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• 2006

Safety-critical navigation systems have to provide 'reliable' position solutions, i.e., they must detect and exclude measurement or system faults and estimate the uncertainty of the solution. To obtain more accurate and reliable navigation systems, various filtering methods have been employed to reduce measurement noise level, or integrate sensors, such as global navigation satellite system/inertial navigation system (GNSS/INS) integration. Recently, particle filters have attracted attention, because they can deal with nonlinear/non-Gaussian systems. In most GNSS applications, the GNSS measurement noise is assumed to follow a Gaussian distribution, but this is not true. Therefore, we have proposed a fault detection and exclusion method using particle filters assuming non-Gaussian measurement noise. The performance of our method was contrasted with that of conventional Kalman filter methods with an assumed Gaussian noise. Since the Kalman filters presume that measurement noise follows a Gaussian distribution, they used an overbounded standard deviation to represent the measurement noise distribution, and since the overbound standard deviations were too conservative compared to the actual distributions, this degraded the integrity-monitoring performance of the filters. A simulation was performed to show the improvement in performance of our proposed particle filter method by not using the sigma overbounding. The results show that our method could detect smaller measurement biases and reduced the protection level by 30% versus the Kalman filter method based on an overbound sigma, which motivates us to use an actual noise model instead of the overbounding or improve the overbounding methods.

• ETRI Journal
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• 제32권6호
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• pp.837-842
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• 2010

This paper proposes robust source localization methods for estimating the azimuth angle, elevation angle, velocity, and range using a low-complexity planar antenna array in impulsive non-Gaussian noise environments. The proposed robust source localization methods for wireless communication applications are based on nonlinear M-estimation provided from Huber and Hampel. Simulation results show the robustness performance of the proposed robust methods in impulsive non-Gaussian noise.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2018년도 추계학술대회
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• pp.73-76
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• 2018

A Gaussian noise is caused by surrounding environment or channel interference when transmitting image. The noise reduces not only image quality degradation but also high-level image processing performance. The Non-Local Means (NLM) filter finds similarity in the neighboring sets of pixels to remove noise and assigns weights according to similarity. The weighted average is calculated based on the weight. The NLM filter method shows low noise cancellation performance and high complexity in the process of finding the similarity using weight allocation and neighbor set. In order to solve these problems, we propose an algorithm that shows an excellent noise reduction performance by using Summed Square Image (SSI) to reduce the complexity and applying the weighting function based on a cosine Gaussian kernel function. Experimental results demonstrate the effectiveness of the proposed algorithm.

• 한국통신학회논문지
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• 제36권6C호
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• pp.391-397
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• 2011

본 논문에서는 직교 주파수 분할 다중화 (orthogonal frequency division multiplexing: OFDM) 기반 인지 무선 (cognitive radio: CR) 시스템을 위한 주파수 옵셋 추정 기법에 대해 연구한다. CR 통신 환경에서는 종종 비정규 잡음에 발생하므로 이를 고려하지 않은 주파수 옵셋 추정 기법들의 추정 성능은 크게 하락한다. 본 논문에서는 비정규 잡음 환경에서 OFDM 기반 CR 시스템을 위한 블라인드 방식의 최대 우도 이론 기반 주파수 옵셋 추정 기법을 제안한다. 제안하는 기법은 이제까지의 기법보다 비정규 잡음 환경에서 우수한 추정 성능을 갖는다.

• 한국컴퓨터정보학회논문지
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• 제16권4호
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• pp.15-22
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• 2011

주성분 분석(PCA)은 데이터의 차원을 줄이면서 최대의 데이터 변이를 보존하는 기법으로 차원 축소나 특징 추출을 위해 널리 사용되고 있다. 하지만 PCA는 잡음에 민감하며 가우스 분포에 대하여만 유효하다는 단점이 있다. 잡음 민감성의 개선을 위해 다양한 방법이 제시되었고 그 중 퍼지 소속도를 이용한 반복적 최적화 기법인 RF-PCA2가 다른 방법에 비해 우수한 성능을 보였다. 하지만 RF-PCA2는 가우스 분포에만 사용할 수 있는 선형 알고리듬이라는 한계가 있다. 이 논문에서는 RF-PCA2와 커널 주성분 분석(kernel PCA, K-PCA)을 결합하여 가우스 분포 이외의 분포들도 다룰 수 있는 비선형 알고리듬인 improved robust kernel fuzzy PCA (RKF-PCA2)를 제안한다. RKF-PCA2는 RF-PCA2 알고리듬의 잡음 강건성과K-PCA의비선형성을 통해 기존알고리듬에 비해 잡음민감성이 적으며 가우스분포 한계를 효과적으로 극복할 수 있다. 이러한 사실은 실험 결과를 통해 확인할 수 있다.

• Structural Engineering and Mechanics
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• 제28권4호
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• pp.373-386
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• 2008

In this study stochastic analysis of non-linear dynamical systems under ${\alpha}$-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of ${\alpha}$-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with ${\alpha}/2$- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function of the system under Gaussian white noise and the probability density function of the ${\alpha}/2$-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian ${\alpha}$-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.172-175
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• 2002

This paper presents perceptual model with a stochastic rnultiresolution characteristic that can be applied with watermark embedding in the biorthogonal wavelet domain. The perceptual model with adaptive watermarking algorithm embed at the texture and edge region for more strongly embedded watermark by the SSQ(successive subband quantization). The watermark embedding is based on the computation of a NVF(noise visibility function) that have local image properties. This method uses non-stationary Gaussian model stationary Generalized Gaussian model because watermark has noise properties. In order to determine the optimal NVF, we consider the watermark as noise. The particularities of embedding in the stationary GG model use shape parameter and variance of each subband regions in multiresolution. To estimate the shape parameter, we use a moment matching method. Non-stationary Gaussian model use the local mean and variance of each subband. The experiment results of simulation were found to be excellent invisibility and robustness. Experiments of such distortion are executed by Stirmark benchmark test.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1987년도 춘계학술발표회 논문집
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• pp.223-229
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• 1987

The error rate eqations of digital modulated signals transmitted through the fading cdannel have been derived in the Gaussian/Impulsive noise environments Whing the derived equations for the error drobadillties of ASK, QAM, FSK, MSK, PSK, and DPSK signais, the error tate performance of digital modulation systems have been evaluated and represented in the graghes as parameters of carrier to \ulcornernoise power ratio (CNR) and fading figures The results show that in the fading environenet the error is occurred more frequently by gaussian noise in the deep fading Howerer in the shallow fading lmpulsive noise is more domiant than gaussian nosie in occurring the error

• 한국산학기술학회논문지
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• 제14권3호
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• pp.1416-1421
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• 2013

비-가우시안 잡음 환경의 적응 시스템을 위해, 평행 이동한 오차 분포와 오차 0에 위치한 델타 함수 사이의 유클리드 거리를 새로운 성능기준으로 제안하였다. 또한, 이 성능 기준에 근거하여 적응 알고리듬을 개발하였고, 얕은 바다에서 구한 수중 통신 다경로 채널에 충격성 잡음과 직류 바이어스 잡음이 더해진 환경으로 등화 성능을 시뮬레이션한 결과, 제안한 알고리듬이 기존의 MEDE 알고리듬 보다 5 dB 이상 향상된 MSE 성능을 보이며 오차 분포의 중심 위치가 정확히 0에 위치하였다.

• 한국통신학회논문지
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• 제37A권12호
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• pp.1038-1042
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• 2012

이 논문에서는 편이된 확률밀도함수 간 거리 측정이라는 새로운 거리 측정 기준을 제안하고 이에 관련된 등화 알고리듬을 도출하여 충격성 잡음과 시변 직류 잡음이 있는 다경로 채널에 적용하였다. 이러한 비 가우시안 잡음 환경에서 시행한 시뮬레이션의 결과로부터, 제안한 알고리듬이 충격성 잡음에 강인성을 보일 뿐 아니라 시변 직류 잡음도 제거하는 탁월한 능력을 가짐을 입증하였다.