• Journal of Industrial Technology
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• v.31 no.A
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• pp.39-43
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• 2011

Coherent interferences can be rejected using the weighted spatial smoothing (WSS) technique that allows us to be able to completely decorrrelate coherent signals with their arrival angles known. Its effective array aperture, however, can be greatly decreased, in particular when there exist many interferences, thereby degrading the rejection capability. In this paper, we propose an improved spatial smoothing (IWSS) which, with an increased effective array aperture, provides better performance than the existing WSS. Moreover, the proposed beamformer employs multiple constraints so that the coherent interferences are completely cancelled. Simulation shows the superiority of the IWSS in comparison with the conventional WSS.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.545-548
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• 2000

Adaptive array systems are hard to remove all the interferences when incident signals are coherent with a desired signal. In this paper, we propose a modified Duvall beamformer, which performs spatial smoothing using spatial interpolation technique to maintain the degree of freedom. The propose algorithm can minimize the loss on the degree of freedom due to spatial smoothing by forming subarrays with interpolated signals. Simulation results show that the proposed algorithm can remove all the interferences while conventional beamformer cannot.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.54-58
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• 2002

Mean curvature diffusion (MCD) is a selective smoothing technique that promotes smoothing within a region instead of smoothing across boundaries. By using mean curvature diffusion, noise is eliminated and edges are preserved. In this paper, we propose methods of automatic parameter selection and implementation for the MCD model coupled to min/max flow. The algorithm has been applied to high resolution aerial images and the results show that noise is eliminated and edges are preserved after removal of noise.

• Ocean and Polar Research
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• v.39 no.2
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• pp.73-84
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• 2017

The probability distribution of ichthyoplankton is important for enhancing the precision of sampling while reducing unnecessary surveys. To estimate the ichthyoplankton detection proportion (IDP) and its margin of error (ME), the monitoring information of the chub mackerel's (Scomber japonicus) ichthyoplankton presence-absence sampling data has been were collected over approximately 30 years (from 1982 to 2011) in the Korean coastal seas. Based on the computed spatial distributions of the mackerel's IDP and ME, the confidence interval (CI) range, defined as 2 ME, decreases from approximately 80% to 40% as the sample size n increases from 4 to 24 and the ME is approximately 40% in the typical (seasonal survey) case n = 4 per year. The IDP and ME off Jeju Island are relatively high at the 0.5-degree smoothing level. After increasing the spatial smoothing level to 1.0-degree, the ME decreased, and the spatial distribution pattern also changed due to the over-smoothing effects. In this study, the 0.5-degree smoothing is more suitable for the distribution pattern than the 1.0-degree smoothing level. The area of the high IDP and the low ME on the mackerel's ichthyoplankton was similar to the estimated spawning ground in the Korean peninsula. This information could contribute to enhancing for the spawning ecology surveys.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.77-86
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• 2002

This paper proposes a modified Duvall beamformer performing spatial smoothing with spatial interpolation. In the proposed beamformer, virtual array signals are generated by spatial interpolation between each neighbor array elements, then all signals are used to perform spatial smoothing. The proposed beamformer overcomes the loss of degrees of freedom caused by spatial smoothing by forming subarrays with interpolated signals. Mathematical description shows that the proposed beamformer can restore the rank of away covariance matrix. Accordingly, the proposed beamformer can minimize the loss of degrees of freedom. Simulation results show that the proposed beamformer can remove all coherent interferences while conventional beamformers cannot.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.187-192
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• 2006

Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.370.1-370
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• 2002

A method using beamforming has been developed to measure absorption coefncient of oblique incidence. MUSIC(Multiple Signal Classification) method detects the angle of incidence and reflection. And beamforming method separates the incident and reflected wave. And spatial smoothing technique is used to reduce the coherence between the incident and reflected wave. The test material were modeled as a locally reacting surface. Numerical and experiment results are performed to verify the performance of proposed method.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.85-94
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• 2006

Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

• Journal of Navigation and Port Research
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• v.29 no.5 s.101
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• pp.403-408
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• 2005

The techniques of estimating angle of arrival(AOA) have played a key role for enhancement of wireless communications using array antennas. Among those techniques, the superresolution algorithms, such as MUSIC and ESPRIT, calculate the covariance matrix of the array output vectors which are observed at the array antennas, and then by using eigen-decomposition of the covariance matrix, they estimate AOAs of the received signals with high accuracy. However, superresolution algorithms based eigenvalue decomposition fails to estimate AOAs under multipath environments. Under multipath environments, it is difficult to estimate AOAs of the received signals due to coherency and high-correlation. To resolve coherent signals, the covariance matrix is calculated by using the conventional spatial smoothing technique, and then the techniques based on eigen-descomposition is applied. The result of the conventional spatial smoothing technique, however, is obtained at the cost of losing effective spatial aperture. Moreover, the conventional technique ignores any information in the cross-correlations of the array outputs the subarrays. As the result, the performance for AOA estimation is degraded. In this paper, we propose a new spatial smoothing technique, which consider the cross-correlation for subarrays. By computer simulation, the AOA estimation performance of the proposed method is compared with the conventional method and evaluated.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.227-236
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• 2001

This paper proposes a frequency-domain partially adaptive algorithm, called a censoring algorithm, to reduce the computational complexity of the frequency domain adaptive array. The proposed censoring algorithm determines the existence of interferences in the frequency-domain at each frequency bin using a constant false alarm rate (CFAR) processor. The censoring algorithm adapts only those parts of the weights that correspond to the frequency bins expected to contain interferences. The censoring algorithm is also expanded to overcome the signal cancellation phenomenon caused by smart jammers. Accordingly, a censoring spatial smoothing, which combines the censoring algorithm with spatial smoothing, is proposed. Simulation results show that the proposed algorithms are effective in removing interferences with only part of the computational complexity of conventional algorithms yet with the same level of performance.