• 한국통신학회논문지
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• 제36권6C호
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• pp.376-383
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• 2011

UWB(Ultra Wide Band) 다중경로 채널에서 첫번째 경로를 통해 수신되는 신호가 가장 큰 신호가 아닐 경우가 종종 있으며, 이러한 경우 ToA(Time-of-Arrival) 추정의 정밀도를 유지하는 것은 매우 어려운 문제가 된다. 또한 UWB 신호의 초광대역 특성상 동기식 시스템을 구현할 경우 수신기는 매우 높은 표본화율을 이용해 신호를 수신해야 하기 때문에 복잡도가 증가되는데, 압축센싱(Compressed Sensing) 이론을 이용함으로써 시스템의 복잡도를 효율적으로 낮출 수 있다. 이에 본 논문은 압축센싱 기반의 UWB 수신기의 장점을 이용하면서도 정밀 추정성능을 제공할 수 있는 개선된 ToA 추정 기법을 제안한다. 모의실험 결과를 통해 광범위한 신호대잡음비 환경에서 제안된 기법이 다른 저복잡도 기법들의 성능보다 우수함을 확인하였다.

• 한국멀티미디어학회논문지
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• 제20권5호
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• pp.731-739
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• 2017

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low complexity video sampling. In DCVS schemes, motion estimation & motion compensation is employed at the decoder side, similarly to distributed video coding (DVC), for a low-complex encoder. However, since a simple BCS-SPL algorithm is applied to a residual arising from motion estimation and compensation in conventional MC-BCS-SPL (motion compensated block compressed sensing with smoothed projected Landweber) scheme, the reconstructed visual qualities are severly degraded in Wyner-Ziv (WZ) frames. Furthermore, the scheme takes lots of iteration to reconstruct WZ frames. In this paper, the conventional MC-BCS-SPL algorithm is improved to be operated in more effective way in WZ frames. That is, first, the proposed algorithm calculates a correlation coefficient between two reference key frames and, then, by selecting adaptively the reference frame, the residual reconstruction in pixel domain is performed to the conventional BCS-SPL scheme. Experimental results show that the proposed algorithm achieves significantly better visual qualities than conventional MC-BCS-SPL algorithm, while resulting in the significant reduction of the decoding time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1287-1300
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• 2018

Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2012년도 추계학술대회
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• pp.188-190
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• 2012

Compressed Sensing (CS) has been developed for several years. Among many CS algorithms for image, the Block-based Compressed Sensing with Smoothed Projected Landweber (BCS-SPL) demonstrates its excellent performance in low-complexity and near-optimal reconstruction. Several noise filtering algorithms of image reconstruction have been introduced such as the Wiener or the median filters, etc. In general, each filter has its own advantages and disadvantages depending on specific coding scheme. In this paper, we show that reconstruction performance can be varied according to the choice of filter. When a sub-rate value is changed, different filter causes different effect as well. Concerning the sub-rate, an inner filter can be chosen to improve the reconstructed image quality.

• 한국통신학회논문지
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• 제40권5호
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• pp.806-808
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• 2015

본 논문은 최근 주목받고 있는 압축 센싱(compressed sensing) 기반으로 직교 주파수 분할 다중화 (OFDM; orthogonal frequency division multiplexing) 신호의 파일럿 톤을 효율적으로 설계하여 최대 전력대 평균 전력 비율 (PAPR; peak to average power ratio)을 감소시키는 방법을 제안한다.

• 전기전자학회논문지
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• 제25권1호
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• pp.76-82
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• 2021

In this paper, the compressed sensing basic pursuit denoise algorithm adopted to synthetic aperture radar imaging is investigated to improve the object recognition. From the incomplete data sets for image processing, the compressed sensing algorithm had been integrated to recover the data before the conventional back- projection algorithm was involved to obtain the synthetic aperture radar images. This method can lead to the reduction of measurement events while scanning the objects. An ultra-wideband radar scheme using a stripmap synthetic aperture radar algorithm was utilized to detect objects hidden behind the box. The Ultra-Wideband radar system with 3.1~4.8 GHz broadband and UWB antenna were implemented to transmit and receive signal data of two conductive cylinders located inside the paper box. The results confirmed that the images can be reconstructed by using a 30% randomly selected dataset without noticeable distortion compared to the images generated by full data using the conventional back-projection algorithm.

• Korean Journal of Radiology
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• 제24권12호
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• pp.1293-1297
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• 2023

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권6호
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• pp.2497-2517
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• 2020

For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

• 지구물리와물리탐사
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• 제14권4호
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• pp.335-341
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• 2011

탐사 시스템을 포함하여 대부분의 센싱 및 계측 시스템은 중요한 정보를 놓치지 않기 위하여 필요한 정보 보다 높은 샘플주기로 정보를 수집 한다. 이는 경우에 따라 센싱 및 계측 시스템이 비효율적일 수 있음을 의미한다. 본 논문에서는 적은 샘플자료로부터 높은 정밀도의 정보 취득에 관한 새로운 두 가지 연구분야를 소개하고자 한다. 하나는 가능한 적은 샘플로 원래의 정보를 복원하는 압축센싱(Compressed Sensing)기술이며, 또 다른 하나는 이미 얻어진 한정된 샘플로부터 높은 해상도의 정보를 추정하는 초고해상도(Super-Resolution)기술이다. 본 논문에서는 압축센싱 기술의 기본이론과 복원기술에 대해 설명하고, 탐사분야의 적용 사례, 초고해상도 기술의 배경 및 최근의 기술인 FRI (Finite Rate of Innovation) 개념과 LIMS (Least-squares based Iterative Multipath Super-resolution)기술의 적용사례를 소개한다. 결론으로는 이러한 새로운 기술들이 지구물리 탐사분야에 어떻게 활용될 수 있는지 논의한다.

• Smart Structures and Systems
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• 제25권3호
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• pp.369-384
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• 2020

A wavefield sparse reconstruction technique based on compressed sensing is developed in this work to dramatically reduce the number of measurements. Firstly, a severely underdetermined representation of guided wavefield at a snapshot is established in the spatial domain. Secondly, an optimal compressed sensing model of guided wavefield sparse reconstruction is established based on l₁-norm penalty, where a suite of discrete cosine functions is selected as the dictionary to promote the sparsity. The regular, random and jittered undersampling schemes are compared and selected as the undersampling matrix of compressed sensing. Thirdly, a gradient projection method is employed to solve the compressed sensing model of wavefield sparse reconstruction from highly incomplete measurements. Finally, experiments with different excitation frequencies are conducted on an aluminum plate to verify the effectiveness of the proposed sparse reconstruction method, where a scanning laser Doppler vibrometer as the true benchmark is used to measure the original wavefield in a given inspection region. Experiments demonstrate that the missing wavefield data can be accurately reconstructed from less than 12% of the original measurements; The reconstruction accuracy of the jittered undersampling scheme is slightly higher than that of the random undersampling scheme in high probability, but the regular undersampling scheme fails to reconstruct the wavefield image; A quantified mapping relationship between the sparsity ratio and the recovery error over a special interval is established with respect to statistical modeling and analysis.