• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.1-6
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• 2003

It is difficult to detect and to track the moving targets like tanks and diesel vehicles due to the variety of terrain and moving of targets. It is possible to be happened the aliasing conditions as the difficulty of antenna deployment in the complex environment like the battle fields. In this paper, we study the problem of detecting and tracking of moving targets which are emitting wideband signals under severe spatial aliasing conditions because of the sparse arrays. We developed a direction of arrival(DOA) estimation algorithm based on subband MUSIC(Multiple Signal Classification) method which produces high-resolution estimation. In this algorithm, the true bearings are invariant regardless of changes of frequency bands while the aliased false bearings vary. As a result, the proposed algorithm overcomes the aliasing effects and improves the localization performance in sparse passive arrays.

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.325-331
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• 2017

As a GPS stability problem arises, MLAT system is spotlighted as an alternative technology of ADS-B. MLAT system has a high position accuracy as much as ADS-B. Also, MLAT receives the mode A,C,S, and 1090ES(ADS-B) signals from the mounted aircraft transponder. MLAT receives signals from several receiver units and calculates aircraft positions. MLAT has ADS-B level positioning accurarcy using GPS and can calculate the position information with objects independently. According to global environment changes, Local area multiltilateration(LAM) surveillance system is under development for moving vehicles and aircraft detection in airport. These are still under testing in Tae-an Airfield. In the paper, we analyzed the performance by comparing the calculated position data from MLAT to RTK. In order to confirm the position accuracy of MLAT and the deviation of position data between fixed target and moving target on the ground during the field test in Tae-an Airfield.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.30-44
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• 2022

The advent of deep learning-based algorithms has facilitated researches on target detection from synthetic aperture radar(SAR) imagery. While most of them concentrate on detection tasks for ships with open SAR ship datasets and for aircraft from SAR scenes of airports, there is relatively scarce researches on the detection of SAR ground vehicle targets where several adverse factors such as high false alarm rates, low signal-to-clutter ratios, and multiple targets in close proximity are predicted to degrade the performances. In this paper, a dataset of ground vehicle targets acquired from TerraSAR-X(TSX) satellite SAR images is presented. Then, both detection and instance segmentation are simultaneously carried out on this dataset based on the deep learning-based Mask R-CNN. Finally, this paper shows the future research directions to further improve the performances of detecting the SAR ground vehicle targets.

• Korean Journal of Computational Design and Engineering
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• v.20 no.3
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• pp.238-245
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• 2015

Vulnerability assessment is a process to calculate the damage degree of a combat vehicle when the combat vehicle is attacked by an enemy. When the vehicle is hit, it is necessary to analyze the shot line to calculate which components are damaged and judge whether the armor of the vehicle is penetrated by enemy's warhead. To analyze the shot line efficiently, this paper presents the target modeling and the shot line analysis system to assess vulnerability of the ground combat vehicle. This system is easily able to do several functions: 1) the program reads STL files converted from CAD model which is designed by commercial CAD software. 2) It calculates the intersection between triangle of STL mesh and the shot line, and check if the components of the model are penetrated. 3) This program can visualize the results using OpenGL. The vulnerability assessment using the shot line analysis can be used to model the armor of the combat vehicle and arrange the inner components effectively in the early stage of development of the combat vehicle.