• Title/Summary/Keyword: Decorrelation

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Underwater Navigation of AUVs Using Uncorrelated Measurement Error Model of USBL

  • Lee, Pan-Mook;Park, Jin-Yeong;Baek, Hyuk;Kim, Sea-Moon;Jun, Bong-Huan;Kim, Ho-Sung;Lee, Phil-Yeob
    • Journal of Ocean Engineering and Technology
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    • v.36 no.5
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    • pp.340-352
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    • 2022
  • This article presents a modeling method for the uncorrelated measurement error of the ultra-short baseline (USBL) acoustic positioning system for aiding navigation of underwater vehicles. The Mahalanobis distance (MD) and principal component analysis are applied to decorrelate the errors of USBL measurements, which are correlated in the x- and y-directions and vary according to the relative direction and distance between a reference station and the underwater vehicles. The proposed method can decouple the radial-direction error and angular direction error from each USBL measurement, where the former and latter are independent and dependent, respectively, of the distance between the reference station and the vehicle. With the decorrelation of the USBL errors along the trajectory of the vehicles in every time step, the proposed method can reduce the threshold of the outlier decision level. To demonstrate the effectiveness of the proposed method, simulation studies were performed with motion data obtained from a field experiment involving an autonomous underwater vehicle and USBL signals generated numerically by matching the specifications of a specific USBL with the data of a global positioning system. The simulations indicated that the navigation system is more robust in rejecting outliers of the USBL measurements than conventional ones. In addition, it was shown that the erroneous estimation of the navigation system after a long USBL blackout can converge to the true states using the MD of the USBL measurements. The navigation systems using the uncorrelated error model of the USBL, therefore, can effectively eliminate USBL outliers without loss of uncontaminated signals.

Detection of Surface Changes by the 6th North Korea Nuclear Test Using High-resolution Satellite Imagery (고해상도 위성영상을 활용한 북한 6차 핵실험 이후 지표변화 관측)

  • Lee, Won-Jin;Sun, Jongsun;Jung, Hyung-Sup;Park, Sun-Cheon;Lee, Duk Kee;Oh, Kwan-Young
    • Korean Journal of Remote Sensing
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    • v.34 no.6_4
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    • pp.1479-1488
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    • 2018
  • On September 3rd 2017, strong artificial seismic signals from North Korea were detected in KMA (Korea Meteorological Administration) seismic network. The location of the epicenter was estimated to be Punggye-ri nuclear test site and it was the most powerful to date. The event was not studied well due to accessibility and geodetic measurements. Therefore, we used remote sensing data to analyze surface changes around Mt. Mantap area. First of all, we tried to detect surface deformation using InSAR method with Advanced Land Observation Satellite-2 (ALOS-2). Even though ALOS-2 data used L-band long wavelength, it was not working well for this particular case because of decorrelation on interferogram. The main reason would be large deformation near the Mt. Mantap area. To overcome this limitation of decorrelation, we applied offset tracking method to measure deformation. However, this method is affected by window kernel size. So we applied various window sizes from 32 to 224 in 16 steps. We could retrieve 2D surface deformation of about 3 m in maximum in the west side of Mt. Mantap. Second, we used Pleiadas-A/B high resolution satellite optical images which were acquired before and after the 6th nuclear test. We detected widespread surface damage around the top of Mt. Mantap such as landslide and suspected collapse area. This phenomenon may be caused by a very strong underground nuclear explosion test. High-resolution satellite images could be used to analyze non-accessible area.

On the Trade-off Between Composition and XOR of Random Permutations (랜덤 순열의 직렬 합성과 병렬 합성 사이의 트래이드오프에 관한 연구)

  • Lee Eon-Kyung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.3C
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    • pp.286-292
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    • 2006
  • Both composition and XOR are operations widely used to enhance security of cryptographic schemes. The more number of random permutations we compose (resp. XOR), the more secure random permutation (resp. random function) we get. Combining the two methods, we consider a generalized form of random function: $SUM^s - CMP^c = ({\pi}_{sc} ... {\pi}_{(s-1)c+1}){\oplus}...{\oplus}({\pi}_c...{\pi}_1)$ where ${\pi}_1...{\pi}_{sc}$ are random permutations. Given a fixed number of random permutations, there seems to be a trade-off between composition and XOR for security of $SUM^s - CMP^c$. We analyze this trade-off based on some upper bound of insecurity of $SUM^s - CMP^c$, and investigate what the optimal number of each operation is, in order to lower the upper bound.

Interferometric coherence analysis using space-borne synthetic aperture radar with respect to spatial resolution (공간해상도에 따른 위성 영상레이더 위상간섭기법 긴밀도 분석)

  • Hong, Sang-Hoon;Wdowinski, Shimon
    • Korean Journal of Remote Sensing
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    • v.29 no.4
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    • pp.389-397
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    • 2013
  • Recently high spatial resolution space-borne Synthetic Aperture Radar (SAR) systems have launched and have been operated successfully. Interferometric SAR (InSAR) processing with the space-based high resolution observations acquired by these systems can provide more detail information for various geodetic applications. Coherence is regarded as a critical parameter in the evaluating the quality of an InSAR pair. In this study, we evaluate the coherence characteristics of high-resolution data acquired by TerraSAR-X (X-band) and ALOS PALSAR (L-band) and intermediate-resolution data acquired by Envisat ASAR (C-band) over western Texas, U.S.A. Our coherence analysis reveals that the high-resolution X-band TSX (3.1 cm) data has a high coherence level (0.3-0.6), similar to that of the L-band ALOS PALSAR data (23.5 cm) in short temporal baselines. Further more, the TSX coherence values are significantly higher than those of the C-band (5.6 cm) Envisat ASAR data. The higher coherence of the TSX dataset is a surprising result, because common scattering theories suggest that the longer wavelength SAR data maintain better coherence. In vegetated areas the shorter wavelength radar pulse interacts mostly with upper sections of the vegetation and, hence, does not provide good correlation over time in InSAR pairs. Thus, we suggest that the higher coherence values of the TSX data reflect the data's high-resolution, in which stable and coherent scatters are better maintained. Although, however, the TSX data show a very good coherence with short temporal baseline (11-33 days), the coherences are significantly degraded as the temporal baselines are increased. This result confirms previous studies showing that the coherence has a strong dependency on the temporal baseline.

Analysis of Annual Variability of Landfast Sea Ice near Jangbogo Antarctic Station Using InSAR Coherence Images (InSAR 긴밀도 영상을 이용한 남극 장보고기지 인근 정착해빙의 연간 변화 분석)

  • Han, Hyangsun;Kim, Yeonchun;Jin, Hyorim;Lee, Hoonyol
    • Korean Journal of Remote Sensing
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    • v.31 no.6
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    • pp.501-512
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    • 2015
  • Landfast sea ice (LFI) in Terra Nova Bay, East Antarctica where the Jangbogo Antarctic Research Station is located, has significant influences on marine ecosystem and the sailing of an icebreaker. Therefore, it is essential to analyze the spatio-temporal variation of the LFI in Terra Nova Bay. In this study, we chose interferometric pairs with the temporal baseline from 1 to 9 days out of a total of 62 COSMO-SkyMed synthetic aperture radar (SAR) images over Terra Nova Bay obtained from December 2010 to January 2012, and then constructed the coherence image of each pair. The LFI showed coherence values higher than 0.3 even in the interferometric SAR (InSAR) pairs of up to 9-days of temporal baseline. This was because the LFI was fixed at coastline and thus showed low temporal phase decorrelation. Based on the characteristics of the coherence on LFI, We defined the areas of LFI that show spatially homogeneous coherence values higher than 0.5. Pack ice (PI) and open water showed low coherence values due to large temporal phase decorreation caused by current and wind. Distinguishing PI from open water in the coherence images was difficult due to their similarly low coherence values. PI was identified in SAR amplitude images by investigating cracks on the ice. The extents of the LFI and PI were estimated from the coherence and SAR amplitude images and their temporal variations were analyzed. The extent of the LFI increased from March to July (maximum extent of $170.7km^2$) and decreased from October. The extent of the PI increased from February to May and decreased from May to July when the LFI increases dramatically. The extent of the LFI and air temperature showed an inverse correlation with a time lag of about 2 months, i.e., the extent of the LFI decreases after 2 months of the increase in the air temperature. Meanwhile the correlation between wind speed and the extent of the LFI was very low. This represents that the extent of LFI in Terra Nova Bay are influenced more by the air temperature than wind speed.