• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2400-2413
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• 2019

Doubly-selective (DS) fading channel is often occurred in many orthogonal frequency division multiplexing (OFDM) communication systems, such as high-speed rail communication systems and underwater acoustic (UWA) wireless networks. It is challenging to provide an accurate and fast estimation over the doubly-selective channel, due to the strong Doppler shift. This paper addresses the doubly selective channel estimation problem based on complex exponential basis expansion model (CE-BEM) in OFDM systems from the perspective of distributed compressive sensing (DCS). We propose a novel DCS-based improved sparsity adaptive matching pursuit (DCS-IMSAMP) algorithm. The advantage of the proposed algorithm is that it can exploit the joint channel sparsity information using dynamic threshold, variable step size and tailoring mechanism. Simulation results show that the proposed algorithm achieves 5dB performance gain with faster operation speed, in comparison with traditional DCS-based sparsity adaptive matching pursuit (DCS-SAMP) algorithm.

• Smart Structures and Systems
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• 제25권2호
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• pp.123-133
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• 2020

Compressive sensing (CS) is a newly developed data acquisition and processing technique that takes advantage of the sparse structure in signals. Normally signals in their primitive space or format are reconstructed from their compressed measurements for further treatments, such as modal analysis for vibration data. This approach causes problems such as leakage, loss of fidelity, etc., and the computation of reconstruction itself is costly as well. Therefore, it is appealing to directly work on the compressed data without prior reconstruction of the original data. In this paper, a direct approach for modal analysis of damped systems is proposed by decomposing the compressed measurements with an appropriate dictionary. The damped free vibration function is adopted to form atoms in the dictionary for the following sparse decomposition. Compared with the normally used Fourier bases, the damped free vibration function spans a space with both the frequency and damping as the control variables. In order to efficiently search the enormous two-dimension dictionary with frequency and damping as variables, a two-step strategy is implemented combined with the Orthogonal Matching Pursuit (OMP) to determine the optimal atom in the dictionary, which greatly reduces the computation of the sparse decomposition. The performance of the proposed method is demonstrated by a numerical and an experimental example, and advantages of the method are revealed by comparison with another such kind method using POD technique.

• 한국군사과학기술학회지
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• 제21권4호
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• pp.437-446
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• 2018

This paper describes the real-time logic implementation of orthogonal matching pursuit(OMP) algorithm for compressive sensing digital receiver. OMP contains various complex-valued linear algebra operations, such as matrix multiplication and matrix inversion, in an iterative manner. Xilinx Vivado high-level synthesis(HLS) is introduced to design the digital logic more efficiently. The real-time signal processing is realized by applying dataflow architecture allowing functions and loops to execute concurrently. Compared with the prior works, the proposed design requires 2.5 times more DSP resources, but 10 times less signal reconstruction time of $1.024{\mu}s$ with a vector of length 48 with 2 non-zero elements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1700-1721
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• 2017

The problem of blocking artifacts is very common in block-based image and video compression, especially at very low bit rates. In this paper, we propose a post-processing method for JPEG-coded image deblocking via sparse representation and adaptive residual threshold. This method includes three steps. First, we obtain the dictionary by online dictionary learning and the compressed images. The dictionary is then modified by the histogram of oriented gradient (HOG) feature descriptor and K-means cluster. Second, an adaptive residual threshold for orthogonal matching pursuit (OMP) is proposed and used for sparse coding by combining blind image blocking assessment. At last, to take advantage of human visual system (HVS), the edge regions of the obtained deblocked image can be further modified by the edge regions of the compressed image. The experimental results show that our proposed method can keep the image more texture and edge information while reducing the image blocking artifacts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.2346-2362
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• 2016

As one of the most important issues in computer vision and image processing, online object tracking plays a key role in numerous areas of research and in many real applications. In this study, we present a novel tracking method based on the proposed structured sparse representation model, in which the tracked object is assumed to be sparsely represented by a set of object and background templates. The contributions of this work are threefold. First, the structure information of all the candidate samples is utilized by a joint sparse representation model, where the representation coefficients of these candidates are promoted to share the same sparse patterns. This representation model can be effectively solved by the simultaneous orthogonal matching pursuit method. In addition, we develop a tracking algorithm based on the proposed representation model, a discriminative candidate selection scheme, and a simple model updating method. Finally, we conduct numerous experiments on several challenging video clips to evaluate the proposed tracker in comparison with various state-of-the-art tracking algorithms. Both qualitative and quantitative evaluations on a number of challenging video clips show that our tracker achieves better performance than the other state-of-the-art methods.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.360-369
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• 2017

In this paper, a new iterative algorithm for reconstructing block sparse signals, called block backtracking-based adaptive orthogonal matching pursuit (BBAOMP) method, is proposed. Compared with existing methods, the BBAOMP method can bring some flexibility between computational complexity and reconstruction property by using the backtracking step. Another outstanding advantage of BBAOMP algorithm is that it can be done without another information of signal sparsity. Several experiments illustrate that the BBAOMP algorithm occupies certain superiority in terms of probability of exact reconstruction and running time.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2004년도 정기총회 및 학술대회
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• pp.175-178
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• 2004

본 논문에서는 직교 주파수 분한 다중 접속 (orthogonal frequency division multiplexing, OFDM) 시스템에서 matching pursuit (MP) 알고리듬을 이용하는 이동 채널 추정 법을 제안한다. 기존의 OFDM 시스템에서 채널추정 알고리즘으로 쓰이는 zero-forcing (ZF) 알고리듬은 잡음의 영향으로 채널 추정 오류의 가능성을 가지고 있다. 제안한 알고리듬에서는 MP 알고리듬을 이용하여 스파스(sparse)형태의 채널을 추정함으로써 다중경로가 없다고 가정되는 시간영역의 채널구간에서 발생될 수 있는 잡음에 의한 영향을 줄인다. 또한 연속적으로 전송되는 파일럿 정보를 이용하여 실시간으로 채널의 변화를 추정한다. 제안한 알고리듬으로 채널을 추정하고 등화를 했을 경우 ZF 알고리듬보다 우수한 성능을 보임을 실험에서 확인한다.

• 한국산학기술학회논문지
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• 제16권3호
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• pp.2141-2145
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• 2015

본 논문에서는, 압축센싱 기법을 이용하여, 방송 네트워크 시스템의 멀티미디어 신호 전송 대역폭 효율성을 극대화할 수 있는 기법을 제안하였다. 멀티미디어 이미지의 sparisity를 높이기 위해서 2차원 이산 웨이블렛 변환 기법을 적용하는 샘플링 기법과, orthogonal matching pursuit기반 L1 최소화기법을 이용하여 복원하는 기법을 본 논문에서 제안하였다. 다양한 멀티미디어 신호가 압축센싱 기술에 의해 압축되어지기 때문에, 다양한 멀티미디어 데이터가 전송 시 점유하는 대역폭을 감소시킬 수 있다. 10Gs/s로 샘플링 되어진, 20% 압축률을 갖는 $256{\times}256$ 흑백스케일 이미지가 20km 광전송되어진 후에, Sparse한 방송신호를 복원하는, L1 최소화 기법을 이용하여 복원되었다(비트 에러오류율: $10^{-12}$).

• 한국통신학회논문지
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• 제39A권7호
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• pp.424-430
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• 2014

본 논문에서는 다중사용자 (Multiuser, MU)환경의 상향링크 공간변조 (Spatial Modulation, SM)시스템(MU-SM)에서 병렬직교매칭퍼슛 (Parallel OMP, POMP)검출 기법을 적용하여 신호 복원 성능을 개선하는 기법을 제안하고 그 성능분석을 한다. MU-SM시스템의 전송신호는 사용자당 $N_t$개의 안테나중 1개의 안테나만을 사용하여 변조심벌을 전송하는 특성이 있으므로 수신단에서 신호복원 시 이러한 특성을 고려한다. MU-OMP기법은 첫번째 반복과정을 수행 후 두 번째 이후의 인덱스를 찾을 때는 이전의 인덱스에 해당하는 안테나를 가진 사용자의 모든 안테나 인덱스를 제외하고 다음 인덱스를 찾는다. 이것은 한명의 사용자 안테나들 중 2개 이상의 인덱스가 선택되는 것을 방지하여 오류 확률을 줄일 수 있다. 시뮬레이션을 통해 제안한 MU-OMP와 MU-POMP 검출 기법이 기존의 압축센싱기반의 신호복원기술보다 성능이 월등함을 확인하였다.

• 한국전자파학회논문지
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• 제28권8호
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• pp.636-645
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• 2017

실 개구(real-aperture)를 사용하는 스캐닝 레이다(scanning radar)는 지상을 감시하거나 재난 구조를 하는 등 폭 넓게 이용 가능하다. 그러나 스캐닝 레이다의 특성상 거리 방향의 분해능은 송신하는 신호의 대역폭에 의해 제한되며, 거리방향에 수직한 방향의 분해능은 빔 폭에 의해 결정된다. 본 논문에서는 초해상도(super-resolution) 레이다 영상 기법을 제안한다. 산란체가 스캔 영역에 드문드문 존재한다면 반사율의 분포를 sparse 신호로 간주할 수 있게 되고, '압축 감지(compressive sensing)' 문제로 수식화하는 것이 가능하다. 본 논문에서는 '재가중치 ${\ell}_1$-최소화'를 통해 2차원 레이다 이미지를 얻는다. 모의실험 결과에서는 제안하는 기법으로 얻은 이미지와 더불어 기존에 널리 쓰이는 Orthogonal Matching Pursuit(OMP), 합성 개구 레이다(Synthetic Aperture Radar : SAR)의 결과와 비교하였다.