• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.431-439
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• 2010

Cross-interferometic synthetic aperture radar (CInSAR) technique from ERS-2 and Envisat images is capable of generating submeter-accuracy digital elevation model (DEM). However, it is very difficult to produce high-quality CInSAR-derived DEM due to the difference in the azimuth and range pixel size between ERS-2 and Envisat images as well as the small height ambiguity of CInSAR interferogram. In this study, we have proposed an efficient method to overcome the problems, produced a high-quality DEM over northern Alaska, and compared the CInSAR-derived DEM with the national elevation dataset (NED) DEM from U.S. Geological Survey. In the proposed method, azimuth common band filtering is applied in the radar raw data processing to mitigate the mis-registation due to the difference in the azimuth and range pixel size, and differential SAR interferogram (DInSAR) is used for reducing the unwrapping error occurred by the high fringe rate of CInSAR interferogram. Using the CInSAR DEM, we have identified and corrected man-made artifacts in the NED DEM. The wave number analysis further confirms that the CInSAR DEM has valid Signal in the high frequency of more than 0.08 radians/m (about 40m) while the NED DEM does not. Our results indicate that the CInSAR DEM is superior to the NED DEM in terms of both height precision and ground resolution.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.287-302
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• 2005

Digital Elevation Models (DEMs) were generated by ERS-l/2 and JERS-1 SAR interferometry in Daejon area, Korea. The quality of the DEM's was evaluated by the Ground Control Points (GCPs) in city area where GCPs were determined by GPS surveys, while in the mountain area with no GCPs, a 1:25,000 digital map was used. In order to minimize errors due to the inaccurate satellite orbit information and the phase unwrapping procedure, a Differential InSAR (DInSAR) was implemented in addition to the traditional InSAR analysis for DEM generation. In addition, DEMs from GTOPO30, SRTM-3, and 1:25,000 digital map were used for assessment the resolution of the DEM generated from DInSAR. 5-6 meters of elevation errors were found in the flat area regardless of the usage and the resolution of DEM, as a result of InSAR analyzing with a pair of ERS tandem and 6 pairs of JERS-1 interferograms. In the mountain area, however, DInSAR with DEMs from SRTM-3 and the digital map was found to be very effective to reduce errors due to phase unwrapping procedure. Also errors due to low signal-to-noise ratio of radar images and atmospheric effect were attenuated in the DEMs generated from the stacking of 6 pairs of JERS-1. SAR interferometry with multiple pairs of SAR interferogram with low resolution DEM can be effectively used to enhance the resolution of DEM in terms of data processing time and cost.

• Journal of IKEEE
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• v.24 no.3
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• pp.797-802
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• 2020

In this paper, we presents the design and implementation results of the FFT processor, which supports 4096 points of operation with less memory by sharing several memory used in the base-4 systolic array FFT processor into one memory. Sharing memory provides the advantage of reducing the area, and also simplifies the flow of data as I/O of the data progresses in one memory. The presented FFT processor was implemented and verified on the FPGA device. The implementation resulted in 51,855 CLB LUTs, 29,712 CLB registers, 8 block RAM tiles and 450 DSPs, and confirmed that the memory area could be reduced by 65% compared to the existing base-4 systolic array structure.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.87-91
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas. However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. The other problem of MUSIC and ESRPIT is to require calibrated antennas with uniform features, and are sensitive to the manufacturing facult and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected hopfield neural model. Computer simulations show the validity of the proposed algorithm. The proposed method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.

• Journal of Navigation and Port Research
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• v.27 no.4
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• pp.465-469
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas, However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. the other problem of MUSIC and ESPRIT is to require calibrated antennas with uniform features, and are sensitive ti the manufacturing fault and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those methods require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected Hopfield neural model. Computer simulations show the validity of the proposed algorithm. It follows that the proposed method yields better AOA estimates than MUSIC. Moreover, out method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.389-398
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• 2019

In this paper, we propose a method to detect small unmanned aerial vehicles(UAVs) flying in a real-world environment. Small UAV signals are frequently obscured by clutter signals because UAVs usually fly at low altitudes over urban or mountainous terrain. Therefore, to obtain a desirable detection performance, clutter signals must be considered in addition to noise, and thus, a performance analysis of each clutter removal technique is required. The proposed detection process uses clutter removal and pulse integration methods to suppress clutter and noise signals, and then detects small UAVs by utilizing a constant false alarm rate detector. After applying three clutter removal techniques, we analyzed the performance of each technique in detecting small UAVs. Based on experimental data acquired in a real-world outdoor environment, we found it was possible to derive a clutter removal method suitable for the detection of small UAVs.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.801-810
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• 2018

Ship monitoring using satellite synthetic aperture radar (SAR) images consists of ship detection, ship discrimination, and ship classification. A large number of methods have been proposed to improve the detection and discrimination capabilities, while only a few studies exist for ship classification. Thus, many studies for the ship classification are needed to construct ship monitoring system having high performance. Note that constructing database (DB), which contains both SAR images and labels of various ships, is important for research on the ship classification. In the airborne SAR classification, many methods have been developed using moving and stationary target acquisition and recognition (MSTAR) DB. However, there has been no publicly available DB for research on the ship classification using satellite SAR images. Recently, Shanghai Key Laboratory has constructed OpenSARShip DB using both SAR images of various ships generated from Sentinel-1 satellite of European Space Agency (ESA) and automatic identification system (AIS) information. Thus, the applicability of OpenSARShip DB for ship classification should be investigated by using the concepts of airborne SAR classification which have shown high performances. In this study, ship classification using satellite SAR images are conducted by applying the concepts of airborne SAR classification to OpenSARShip DB, and then the applicability of OpenSARShip DB is investigated by analyzing the classification performances.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.148-153
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• 1999

Baikdu-san was a very active volcano during the Cenozoic era and is believed to be formed in late Cenozoic era. Recently it was also reported that there was a major eruption in or around 1002 A.D. and there are evidences which indicate that it is still an active volcano and a potential volcanic hazard. Remote sensing techniques have been widely used to monitor various natural hazards, including volcanic hazards. However, during an active volcanic eruption, volcanic ash can basically cover the sky and often blocks the solar radiation preventing any use of optical sensors. Synthetic aperture radar(SAR) is an ideal tool to monitor the volcanic activities and lava flows, because the wavelength of the microwave signal is considerably longer that the average volcanic ash particle size. In this study we have utilized several sets of SAR data to evaluate the utility of the space-borne SAR system. The data sets include JERS-1(L-band) SAR, and RADARSAT(C-band) data which included both standard mode and the ScanSAR mode data sets. We also utilized several sets of auxiliary data such as local geological maps and JERS-1 OPS data. The routine preprocessing and image processing steps were applied to these data sets before any attempts of classifying and mapping surface geological features. Although we computed sigma nought ($\sigma$$^{0}$) values far the standard mode RADARSAT data, the utility of sigma nought image was minimal in this study. Application of various types of classification algorithms to identify and map several stages of volcanic flows was not very successful. Although this research is still in progress, the following preliminary conclusions could be made: (1) sigma nought (RADARSAT standard mode data) and DN (JERS-1 SAR and RADARSAT ScanSAR data) have limited usefulness for distinguishing early basalt lava flows from late trachyte flows or later trachyte flows from the old basement granitic rocks around Baikdu-san volcano, (2) surface geological structure features such as several faults and volcanic lava flow channels can easily be identified and mapped, and (3) routine application of unsupervised classification methods cannot be used for mapping any types of surface lava flow patterns.