• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.60-67
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• 2022

An Electro-Optical Tracking System (EOTS) is an electric optical system with EO/IR cameras, laser sensors, and an IMU. The EOTS calculates coordinates of targets, using attitude and acceleration measured by the IMU. In particular for an armed aircraft, the performance of the weapon system depends on how quickly and accurately it acquires the target coordinates. The IMU should be operated after alignment is complete, to meet the coordinate accuracy required by the weapon system so the initial stabilization time of the IMU should be reduced, by quickly measuring the attitude and acceleration. Alignment is the process of determining the initial attitude by resolving the attitude error of the IMU, and the IMU of mission equipment such as an airborne EOTS, uses velocity matching based on the velocity from GPS/INS for aircraft navigation. In this paper, a method is presented to improve the transfer alignment performance of the airborne EOTS, by maneuvering aircraft and the mission equipment. First, the performance factor of the alignment was identified, as a heading error through the velocity matching model and simulation results. Then acceleration maneuvers and attitude changes were necessary, to correct the error. As a result of flight tests applied to an EOTS on a OOO aircraft system, the transfer alignment performance was improved as the duration time was decreased, by more than five times when the aircraft accelerated by more than 0.2g and the EOTS was moving until 6.7deg/s.

• Spatial Information Research
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• v.16 no.3
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• pp.373-383
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• 2008

LiDAR, unlike satellite imagery and aerial photographs, which provides irregularly distributed three-dimensional coordinates of ground surface, enables three-dimensional modeling. In this study, urban area was classified based on 3D information collected by LiDAR. Morphological and spatial properties are determined by the ratio of ground and non-ground point that are estimated with the number of ground reflected point data of LiDAR raw data. With this information, the residential and forest area could be classified in terms of height and density of trees. The intensity of the signal is distinguished by a statistical method, Jenk's Natural Break. Vegetative area (high or low density) and non-vegetative area (high or low density) are classified with reflective ratio of ground surface.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1121-1126
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• 2017

Various studies such as INS(: Inertial Navigation System) are conducting to estimate the position of UAV, because the GPS information of UAV is at risk like the GPS jamming. The position estimation using DoA and RTT are used to apply many radar systems, and that process can be applied in datalink of UAV. The general monopulse feed in UAV datalink is Multi-horn, because of the wide BW(: Band Width) and frequency range. And it needs wide SNR range of tracking because of the limited transmit power of airborne unit. The estimation error of position increase at low SNR, and the DoA is valid in only 3dB beam width but high SNR causes false of mainlobe detection because of large sidelobe. In this paper, We propose the method to achieve higher accuracy of DoA estimation on low SNR and review some idea that able to detect mainlobe.