• ETRI Journal
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• v.32 no.2
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• pp.333-335
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• 2010

This letter proposes a non-coherent blind time-of-arrival (TOA) estimation scheme for impulse radio ultra-wideband systems. The TOA estimation is performed in two consecutive phases: the Rayleigh-quotient theorem-based coarse-signal acquisition (CSA) and the iterative-threshold-test-based fine time estimation (FTE). The proposed scheme serves in a blind manner without demanding any a priori knowledge of the channel and the noise. Analysis and simulations demonstrate that the proposed scheme significantly increases the signal detection probability in CSA and ameliorates the TOA estimation accuracy in FTE.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.7
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• pp.1-5
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• 2012

At the present time when the limits of the magnetic storage systems appear, the holographic data storage (HDS) devices with high data transfer rate and high recording density are emerging as attractive candidates for next-generation optical storage devices. In this paper, to effectively improve the detection performance that is degraded by the two-dimensional inter-symbol interference under the HDS channel environment and the pixel misalignment, an iterative two-dimensional equalization scheme is proposed based on the contraction mapping theorem. In order to evaluate the performance of the proposed scheme, for various holographic channel environments we measure the BER performance using computer simulation and compare the proposed one with the conventional threshold detection scheme, which verifies the superiority of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.535-544
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• 2012

Multi-Input Multi-Output (MIMO) transmission is now considered as one of essential techniques enabling high rate data transmissions in wireless communication systems. In addition, severe channel impairments in wireless systems should be compensated by using highly efficient forward error correction (FEC) codes. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection information (SDDI), are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of SDDI from the MIMO detection process. In this paper, we propose a soft MIMO detection scheme using QR decomposition of channel matrices as an efficient means to provide accurate SDDI to the iterative decoder. The proposed method employed a two sequential soft MIMO detection process in order to reduce computational complexity. Compared to the soft ZF method calculating the direct inverse of the channel matrix, the complexity of the proposed method can be further reduced as the number of antennas is increased, without any performance degradation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.4
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• pp.524-532
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• 2012

In this paper, we used MOM-based BIM(Born Iterative Method) algorithm to implement the inverse scattering for the detection of cancer. We adopted two-dimensional breast structure, integral equations and two-dimensional Green's function is solved with MoM(Method of Moment) to analyzing electromagnetic scattering phenomena. In addition, verifying the calculation of developed inverse scattering algorithm and analyzing medical applicability and limitations of the algorithm.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.258-269
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• 2020

This paper proposes Snapping Shrimp Noise (SSN) detection and corrupted Orthogonal Frequency Division Multiplexing (OFDM) reconstruction methods to increase Bit Error Rate (BER) performance when OFDM transmitted signal is corrupted by impulsive SSNs in underwater acoustic communications. The proposed detection method utilizes multilayer wavelet packet decomposition for detecting impulsive and irregularly concentrated and SSN energy in specific frequency bands of SSN, and the proposed reconstruction scheme uses iterative decision directed-subcarrier reconstruction to recover corrupted OFDM signals using multiple carrier characteristics. Computer simulations were executed to show receiver operating characteristics curve for the detection performance and BER for the reconstruction. The practical ocean experiment of SAVEX 15 demonstrated that the proposed method exhibits a better detection performance compared with conventional detection method and improves BER by 250% and 1230% for uncoded and coded data, respectively, compared with the conventional reconstruction scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6A
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• pp.577-586
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• 2011

Modem digital communication systems are required to use forward error correction (FEC) codes to combat inevitable channel impairment. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection (SDD) information, are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of soft decision detection information. In order to use FEC codes with iterative decoding for Multi-Input Multi-Output (MIMO) system, reliable soft decision channel gain should be provided. In this paper, we investigate efficient SDD methods for turbo-coded MIMO system, and derive the corresponding formulas of SDD for various MIMO detection schemes. We present simulation results of the derived SDD schemes for turbo-coded MIMO systems, and show that the presented results almost approximate to maximum likelihood detection performance with much less computational load.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.6
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• pp.950-956
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• 2013

This paper describes a sensitivity-coefficient-based iterative method for detecting cracks in a structure. The sensitivity coefficients of a cracked structure are obtained by changing its eigenvectors. The proposed method is applied to a cracked cantilever. The crack is modeled as a rotational stiffness. The predicted cracks are in good agreement with those from a structural reanalysis of the cracked structure.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.2
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• pp.100-105
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• 2022

This paper applies the arc detection algorithm to prevent the false detection in photo voltaic series arc detection circuit, which is required not only to detect the series arc quickly, but also not falsely detect the arc for the non-arc noise. For this purpose, this study proposes a rapid and preventive false detection method of single peak noise and short noise signals. First, to prevent false detection by single peak noise, Discrete wavelet transform (DWT)-based characteristic parameters are applied to determine the shape and the amplitude of the noise. In addition, arc fault detection within a few milliseconds is performed with the DWT iterative algorithm to quickly prevent false detection for short noise signals, considering the continuity of serial arc noise. Thus, the method operates not only to detect series arc, but also to avoid false arc detection for peak and short noises. The proposed algorithm is applied to real-time serial arc detection circuit based on the TMS320F28335 DSP. The serial arc detection and peak noise filtering performances are verified in the built simulated arc test facility. Furthermore, the filtering performance of short noise generated through DC switch operation is confirmed.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.193-196
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• 1995

An algorithm using topological mapping has been developed for a real-time detection of the QRS complexes of ECG signals. As a measurement of QRS complex energy, we used topological mapping from one dimensional sampled ECG signals to two dimensional vectors. These vectors are reconstructed with the sampled ECG signals and the delayed ones. In this method, the detection rates of CRS complex vary with the parameters such as R-R interval average and peak detection threshold coefficient. We use mean, median, and iterative method to determint R-R interval average and peak estimation. We experiment on various value of search back coefficient and peak detection threshold coefficient to find optimal rule.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1233-1242
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• 2017

In this study, we tried to analyze deforestation due to forest fire by using KOMPSAT satellite imagery. For deforestation analysis, unsupervised change detection algorithm is applied to multitemporal images. Through ITPCA (ITerative Principal Component Analysis) of NDVI (Normalized Difference Vegetation Index) generated from multitemporal satellite images before and after forest fire, changed areas due to deforestation are extracted. In addition, a post-processing method using SRTM (Shuttle Radar Topographic Mission) data is involved in order to minimize the error of change detection. As a result of the experiment using KOMPSAT-2 and 3 images, it was confirmed that changed areas due to deforestation can be efficiently extracted.