• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.15-26
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• 2004

The calibration for systematic error in LiDAR is crucial for the accuracy of airborne laser scanning. The main error is the misalignment of platforms between INS(Inertial Navigation System) and Laser scanner For planimetrical calibration of LiDAR, the building is good feature which has great changes in height and continuous flat area in the top. The planimetry error(pitch, roll) is corrected by adjustment of height which is calculated from comparing ground control points(GCP) of building to laser scanning data. We can know scale correction of laser range by the comparison of LiDAR data and GCP is arranged at the end of scan angle where maximize the height error. The area for scale calibration have to be large flat and have almost same elevation. At 1000m for average flying height, The Accuracy of laser scanning data using LiDAR is within 110cm in height and ${\pm}$50cm in planmetry so we can use laser scanning data for generating 3D terrain surface, expecically digital surface model(DSM) which is difficult to measure by aerial photogrammetry in forest, coast, urban area of high buildings

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.2
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• pp.169-176
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• 2012

GPS(Global Positioning System) is widely used for the position estimation of an aerial vehicle. However, GPS may not be available due to hostile jamming or strategic reasons. A vision-based position estimation method can be effective if GPS does not work properly. In mountainous areas without any man-made landmark, a horizon is a good feature for estimating the position of an aerial vehicle. In this paper, we present a new method to estimate the position of the aerial vehicle equipped with a forward-looking infrared camera. It is assumed that INS(Inertial Navigation System) provides the attitudes of an aerial vehicle and a camera. The horizon extracted from an infrared image is compared with horizon models generated from DEM(Digital Elevation Map). Because of a narrow field of view of the camera, two images with a different camera view are utilized to estimate a position. The algorithm is tested using real infrared images acquired on the ground. The experimental results show that the method can be used for estimating the position of an aerial vehicle.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.4
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• pp.285-293
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• 2020

In this paper, to improve Synthetic Aperture Radar (SAR) image quality, the effect of time synchronization error in the EGI/IMU (Embedded GPS/INS, Inertial Measurement Unit) integrated system is analyzed and state augmentation is applied to compensate it. EGI/IMU integrated system is widely used as a SAR motion measurement algorithm, which consists of EGI mounted to obtain the trajectory and IMU mounted on the SAR antenna. In an EGI/IMU integrated system, a time synchronization error occurs when the clocks of the sensors are not synchronized. Analysis of the effect of time synchronization error on navigation solutions and SAR images confirmed that the time synchronization error deteriorates SAR image quality. The state augmentation is applied to compensate for this and as a result, the SAR image quality does not decrease. In addition, by analyzing the performance and the observability of the time synchronization error according to the maneuver, it was confirmed that the time-variant maneuver such as rotational motion is necessary to estimate the time synchronization error adequately. In order to reduce the influence of the time synchronization error on the SAR image, the time synchronization error must be compensated by performing maneuver changing over time such as a rotation before SAR operation.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.21-29
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• 2017

For the efficient and stable operation of autonomous vehicles or advanced driver assistance systems being actively studied nowadays, it is important to determine the positions of the vehicle accurately and economically. A satellite based navigation system is mainly used for positioning, but it has a limitation in signal blockage areas. To overcome this limitation, sensor fusion methods including additional sensors such as an inertial navigation system have been mainly proposed but the high sensor cost has been a problem. In this work, we develop a vehicle position estimation algorithm using in-vehicle sensors and a low-cost imaging sensor without any expensive additional sensor. We determine the vehicle positions using the velocity and yaw-rate of a car from the in-vehicle sensors and the position and attitude of the camera based on the single photo resection process. For the evaluation, we built a prototype system, acquired test data using the system, and estimated the trajectory. The proposed algorithm shows the accuracy of about 40% higher than an in-vehicle sensor only method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.23-28
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• 2019

A track type underwater construction robot(URI-R) which can trench on seabed is being developed by Korea Institute of Ocean Science & Technology. During the underwater trenching work, the robot is exposed high intensive noise and vibration so the underwater localization signal may not be obtained properly by the acoustic tracking system. Therefore it is necessary to research about continuous localization even though the measured position signal comes in intermittently. In this paper, the experiments were carried out on land to simulated the underwater operating environment characteristics. To estimate its position, inertial navigation system and global navigation satellite system are used. The effects of the period variation while localizing is investigated by the experiments, and the application for URI-R is proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.342-351
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• 2010

UAV (Unmanned Aerial Vehicle) have an INS(Inertial Navigation System) equipment and also have an electro-optical Equipment for mission. This paper proposes the vision based attitude estimation algorithm using Kalman Filter and Optical flow for UAV. Optical flow is acquired from the movie of camera which is equipped on UAV and UAV's attitude is measured from optical flow. In this paper, Kalman Filter has been used for the settlement of the low reliability and estimation of UAV's attitude. Algorithm verification was performed through experiments. The experiment has been used rate table and real flight video. Then, this paper shows the verification result of UAV's attitude estimation algorithm. When the rate table was tested, the error was in 2 degree and the tendency was similar with AHRS measurement states. However, on the experiment of real flight movie, maximum yaw error was 21 degree and Maximum pitch error was 7.8 degree.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.276-284
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• 2013

This paper considers the transfer alignment in the inertial navigation system and the observability analysis is performed for velocity matching. The state variable of the Kalman filter is modeled including the lever arm error and the measurement equation is obtained. The SOM(Stripped Observability Matrix) method is used for the observability analysis for various maneuvering conditions of the vehicle, which gives the full state observability condition as a specific maneuver sequence of the vehicle. While the observability analysis of a lever arm effect in the existing papers is mainly performed by simulations, we performed it analytically by the observability analysis method. The analysis result is verified using the computer simulations.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.4
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• pp.531-536
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• 2014

There are trapping and stripping methods as the technique to remove the dither motion from RLG(Ring Laser Gyro) output. V/F converter output of angular sensor to measure the dither motion is used in stripping method. But bias and scale factor error is always included in V/F converter output and is a critical limiting factor for the wide application of stripping method to RLG. Therefore there have been many researches to solve this problem. The method to accurately estimate the bias and scale factor error of V/F converter using measurements of the angular sensor acquired at data sampling rate of INS is presented in this paper. To this end, stripping technique based on model of dither motion is newly applied.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.593-599
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• 2013

In this paper, the GPS cycle-slip detection for carrier-phase based positioning of land vehicle is presented. For the carrier phase based positioning, cycle-slip detection is necessary to get the reliability of positioning result. There exists many cycle-slip detection algorithms, but we detect the cycle-slip by using the monitoring value which is defined as residual between the carrier phase measurement and estimated value from low-cost inertial sensor. To achieve goal of paper, low-cost cycle-slip detection system, permissible specification region of inertial sensor is derived. By using the result of permissible region, appropriate inertial sensor of cycle-slip detection can be decided, proper cost and proper specification. To verify the result of this paper, we conduct the rate table test. As a result, required cycle-slip detection performance is satisfied conservatively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1196-1206
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• 2013

In this paper, based on the information about navigation system of UAV with PTZ camera and 3D topography, algorithm able to show us in real-time UAV's geographical shooting location and automatically calculate superficial measure of the shooting area is proposed. And the method that can automatically estimate whether UAV is allowed to shoot a specific area is shown. In case of an UAV's shooting attempt at the specific area, obtainability of valid image depends on not only UAV's location but also information of 3D topography. As a result of the study, Ground Control Center will have real-time information about whether UAV can shoot the needed topography. Therefore, accurate remote flight control will be possible in real-time. Furthermore, the algorithm and the method of estimating shooting probability can be applied to pre-flight simulation and set of flight route.