• Title/Summary/Keyword: Equi-interval

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A Design of the Double Circular Array Patch Antenna Minimized the Side Lobe (부엽준위를 극소화한 이중 원형 배열 패치 안테나의 설계)

  • 진경수;이원석;한정세;박병우;정치현
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.9B
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    • pp.1676-1682
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    • 1999
  • In this paper, the double circular array microstrip patch antenna was designed to minimize the side lobe in which a cooperate feeding network was used to supply the same amplitude and equi-phase to each antenna element. Eight microstirip patch antenna(MPA) elements were arrayed with $45^{\circ}$ interval in the inner circle and the outer circle respectively. The simulation results showed that when the radii of the inner circle and the outer circle were 0.7 $\lambda$0 and 1.45 $\lambda$0, the side lobes of beam pattern were minimized. As the results of the measurements, the return loss of the designed antenna was -14.5[dB] at 11.75[GHz] in the input terminal. When the level of the main lobe was normalized at 0[dB], those of the first and the second side lobe were -18[dB] and -26[dB] respectively. The radiation patterns agree well with the simulated patterns.

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Efficient Rotation-Invariant Boundary Image Matching Using the Envelope-based Lower Bound (엔빌로프 기반 하한을 사용한 효율적인 회전-불변 윤곽선 이미지 매칭)

  • Kim, Sang-Pil;Moon, Yang-Sae;Hong, Sun-Kyong
    • The KIPS Transactions:PartD
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    • v.18D no.1
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    • pp.9-22
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    • 2011
  • In this paper we present an efficient solution to rotation?invariant boundary image matching. Computing the rotation-invariant distance between image time-series is a time-consuming process since it requires a lot of Euclidean distance computations for all possible rotations. In this paper we propose a novel solution that significantly reduces the number of distance computations using the envelope-based lower bound. To this end, we first present how to construct a single envelope from a query sequence and how to obtain a lower bound of the rotation-invariant distance using the envelope. We then show that the single envelope-based lower bound can reduce a number of distance computations. This approach, however, may cause bad performance since it may incur a larger lower bound by considering all possible rotated sequences in a single envelope. To solve this problem, we present a concept of rotation interval, and using the rotation interval we generalize the envelope-based lower bound by exploiting multiple envelopes rather than a single envelope. We also propose equi-width and envelope minimization divisions as the method of determining rotation intervals in the multiple envelope approach. Experimental results show that our envelope-based solutions outperform existing solutions by one or two orders of magnitude.

Surficial Sediment Classification using Backscattered Amplitude Imagery of Multibeam Echo Sounder(300 kHz) (다중빔 음향 탐사시스템(300 kHz)의 후방산란 자료를 이용한 해저면 퇴적상 분류에 관한 연구)

  • Park, Yo-Sup;Lee, Sin-Je;Seo, Won-Jin;Gong, Gee-Soo;Han, Hyuk-Soo;Park, Soo-Chul
    • Economic and Environmental Geology
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    • v.41 no.6
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    • pp.747-761
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    • 2008
  • In order to experiment the acoustic remote classification of seabed sediment, we achieved ground-truth data(i.e. video and grab samples, etc.) and developed post-processing for automatic classification procedure on the basis of 300 kHz MultiBeam Echo Sounder(MBES) backscattering data, which was acquired using KONGBERG Simrad EM3000 at Sock-Cho Port, East Sea of South Korea. Sonar signal and its classification performance were identified with geo-referenced video imagery with the aid of GIS (Geographic Information System). The depth range of research site was from 5 m to 22.7 m, and the backscattering amplitude showed from -36dB to -15dB. The mean grain sizes of sediment from equi-distanced sampling site(50 m interval) varied from 2.86$(\phi)$ to 0.88(\phi). To acquire the main feature for the seabed classification from backscattering amplitude of MBES, we evaluated the correlation factors between the backscattering amplitude and properties of sediment samples. The performance of seabed remote classification proposed was evaluated with comparing the correlation of human expert segmentation to automatic algorithm results. The cross-model perception error ratio on automatic classification algorithm shows 8.95% at rocky bottoms, and 2.06% at the area representing low mean grain size.