• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.634-636
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• 2003

Satrec Initiative (Si) is developing a ground processing system for Synthetic Aperture Radar (SAR) data. SAR provides its own illumination and is not dependent on the light from sun, thus permitting continuous day/night operation and all-weather imaging. The system is capable of producing standard level products from SAR signal. Hence, the system should be able to perform matched filtering, range compression, azimuth compression, multi-look image generation, and geocoded image generation. This paper will describe the processing steps including algorithms, design, and accuracy of the Si's SAR processing system by comparing with commercial software.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.463-471
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• 2008

The quality of orthoimages mainly depends on the elevation information and exterior orientation (EO) parameters. Since LiDAR data directly provides the elevation information over the earth's surface including buildings and trees, the concept of true orthorectification has been rapidly developed and implemented. If a LiDAR-driven digital surface model (DSM) is used for orthorectification, the displacements caused by trees and buildings are effectively removed when compared with the conventional orthoimages processed with a digital elevation model (DEM). This study utilized LiDAR data to generate orthorectified digital aerial images. Experimental orthoimages were produced using digital terrain model (DTM) and DSM. For the preparation of orthorectification, EO components, one of the inputs for orthorectification, were adjusted with the ground control points (GCPs) collected from the LiDAR point data, and the ground points were extracted by a filtering method used in a previous research. The orthoimage generated by DSM corresponded more closely to non-ground LiDAR points than the orthoimage produced by DTM.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.251-258
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• 2007

Airborne Lidar (light detection and ranging) can be an effective alternative in forest inventory to overcome the limitations of conventional field survey and aerial photo interpretation. In this study, we attempt to develop methodologies to identify individual trees and to estimate tree height from airborne Lidar data. Initially, digital elevation model (DEM) data representing the exact ground surface were generated by removing non-ground returns from the multiple-return laser point clouds, obtained over the coniferous forest site of rugged terrain. Based on the canopy height model (CHM) data representing non-ground layer, individual tree heights are extracted through pseudo-grid method and moving window filtering algorithm. Comparing with field survey data and aerial photo interpretation on sample plots, the number of trees extracted from Lidar data show over 90% accuracy and tree heights were underestimated within 1.1m in average at two plantation stands of pine (Pinus koraiensis) and larch (Larix leptolepis).

• Journal of IKEEE
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• v.26 no.4
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• pp.524-530
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• 2022

When radar return contains strong jammers along with ground clutter echo, a STAP(space-time adaptive processing) algorithms tend to suppress jammer components more severely than it does the clutter. This hinders moving target detection in that the target echo is apt to be buried by clutter echo. This paper presents a two-step STAP algorithm in which the pre-suppression of jammer by the spatial filtering is applied, prior to applying the STAP algorithm. We propose how to find the coefficients of the spatial filter and show that the spatial filtering barely alter the spectra of the target and the clutter echo, having only to suppress the jammers. Finally, we simulate a STAP scenario with strong jammers and show the proposed algorithm can improve STAP performance.

• Journal of Astronomy and Space Sciences
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• v.24 no.4
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• pp.261-268
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• 2007

We have studied the temporal variation in the North-South asymmetry of the sunspot area during the period from 1874 to 2007. Though the 9-year periodicity is commonly reported, shorter periodicities is still under study. We employ the cepstrum analysis method to analyze the noisy power spectrum of the North-South asymmetry. We demonstrate that the cleaned power spectrum shows reduction of the spurious back-ground noise level. Some of short period peaks in the power spectrum disappear after deconvolution. It should be, however, pointed out that power spectrum might look less noisy because of a filtering process during deconvolution. We conclude by pointing out that a more sophisticate filtering algorithm is required to produce a precise and reliable periodicity estimate.

• Computational Structural Engineering
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• v.2 no.2
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• pp.113-119
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• 1989

Methods for identification of modal properties of linear structures are presented. The extended Kalman filtering technique is employed. The state equation is formulated by two different ways, namely by the time domain and frequency domain approaches. Verifications are carried out by using the simulated records of ground acceleration and structural response. Then the techniques are applied to the estimation of modal parameters of a scaled model for a 3-story building which is installed on a shaking table.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.4
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• pp.440-443
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• 2010

This paper deals with the method of vibration measurement of a gun barrel structure using mechanical filter. When a bullet with high speed is moving within a gun barrel type structure with low bending vibration frequencies, it is difficult to measure the bending vibration signals of the structure. For example, noncontact type sensors such as displacement or velocity sensor are not appropriate for the measurement of vibrational signals because of the movement effect of the equipment frame through the moving structures or effect of the ground vibration. One of contact type sensors such as accelerometer is profitable for measurement of vibrational signals because of its wide measurement ranges. In the case of a gun barrel structure including high vibrational signals like shock waves, however, it is necessary to propose vibration measurement method filtering high frequencies. The purpose of the paper is to propose the proper vibrational measurement technique filtering high frequencies of a gun barrel type structure.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.77-84
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• 2009

Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is applied to synthetic and field GPR data acquired over a buried pipe. The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a reference signal for pulse compression. For a pulse-compression filter, reference signal selection is an important issue, because as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is low. Analysis of the results obtained from simulated and field GPR data indicates a significant improvement in the GPR image, good discrimination between the target reflection and the ground surface reflection, and better performance with reliable separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.04a
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• pp.66-70
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• 1989

Methods for identification of modal properties of linear structures are presented. The extended Kalman filtering technique is empolyed. The state equation is formulated by two different ways, namely by the time domain and frequency domain approaches. Verifications are carried out by using simulated records of ground acceleration and structural response. Then the techniques are applied to the estimation of modal parameters of a scaled model for a 3-story building which is installed on a shaking table.