• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.397-408
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• 2008

A wide variety of applications of imaging spectrometer have been proved using data from airborne systems. The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the airborne hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems are to be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS has to be calibrated and validated with the calibration equipments such as the integrating sphere and spectral lamps. To improve data quality and its availability, it is the most important to understand the mechanism of imaging spectrometer system and the radiometric and spectral characteristics. The several performance tests of the CAISS were conducted in the camera system level. This paper presents the major characteristics of the CAISS, and summarizes the results of performance tests in the camera system level.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.593-603
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• 2010

Most spatial data acquisition systems employing a set of frame cameras may have suffered from their small fields of view and poor base-distance ratio. These limitations can be significantly reduced by employing an omni-directional camera that is capable of acquiring images in every direction. Bundle Block Adjustment (BBA) is one of the existing georeferencing methods to determine the exterior orientation parameters of two or more images. In this study, by extending the concept of the traditional BBA method, we attempt to develop a mathematical model of BBA for omni-directional images. The proposed mathematical model includes three main parts; observation equations based on the collinearity equations newly derived for omni-directional images, stochastic constraints imposed from GPS/INS data and GCPs. We also report the experimental results from the application of our proposed BBA to the real data obtained mainly in urban areas. With the different combinations of the constraints, we applied four different types of mathematical models. With the type where only GCPs are used as the constraints, the proposed BBA can provide the most accurate results, ${\pm}5cm$ of RMSE in the estimated ground point coordinates. In future, we plan to perform more sophisticated lens calibration for the omni-directional camera to improve the georeferencing accuracy of omni-directional images. These georeferenced omni-directional images can be effectively utilized for city modelling, particularly autonomous texture mapping for realistic street view.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.39-46
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• 2010

Sounding data is the essential source for the safety of ships navigation system, and fundamental to the reasonable usage and maintenance of the ocean as well. As IT tech, positioning equipment such as GPS and INS, echo sounder are developed, recently, the precise submarine topography database bas been built by Multi-Beam Echo Sounder. However, MBES data includes some inevitable error caused by several factor, and some data have errors where the terrain is wobble. The error, which causes the $moir\acute{e}$ pattern error is the main factor hindering the accuracy of MBES data results, and therefore it is necessary to figure out the main cause of the error for the improvement of the accuracy by removing error data. On this research, the main cause of the error data is studied by analyzing motion sensor value of data including the $moir\acute{e}$ pattern error. Thus, as the result of examination, it turns out that the $moir\acute{e}$ pattern error is related to the standard deviation of Roll, and error data values are results of the non-correspondence between Swath data and Roll values caused by the drastic change of Roll values. Accordingly, the error data is removed by comparing between the gradient of Swath data and Roll values. Finally, as the result of removing error data, it is expected to be able to estimate the quality of MBES using the standard deviation of Motion sensor's Roll value, and calculate the additive error factor, which minimize non-corresponding data, and also this research must be contributed to improve the accuracy of sounding for small vessels with lots of motion in the bad circumstance for navigation.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.393-406
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• 2018

Every year in the ocean, various accidents occur frequently and illegal fishing is rampant. Moreover, their size and frequency are also increasing. In order to reduce losses of life or property caused by these, it is necessary to have a means to perform remote monitoring quickly. As an effective platform of such monitoring means, an Unmanned Aerial Vehicle (UAV) is receiving the spotlight. In these situations where marine accidents or illegal fishing occur, main targets of monitoring are ships. In this study, we propose a UAV based ship monitoring system and suggest a method of determining ship positions using UAV multi-sensory data. In the proposed method, firstly, the position and attitude of individual images are determined by using the pre-performed system calibration results and GPS/INS data obtained at the time when images were acquired. In addition, after the ship being detected automatically or semi-automatically from the individual images, the absolute coordinates of the detected ships are determined. The proposed method was applied to actual data measured at 200 m, 350 m, and 500 m altitude, the ship position can be determined with accuracy of 4.068 m, 8.916 m, and 13.734 m, respectively. According to the minimum standard of a hydrographical survey, the ship positioning results of 200 m and 350 m data satisfy grade S and the results of 500 m data do grade 1a, where the accuracy is required for positioning the coastline and topography less significant to navigation order. Therefore, it is expected that the proposed method can be effectively used for various purposes of marine monitoring or surveying.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.5
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• pp.373-381
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• 2021

This paper details the result of flight experiment that examines performance of roll angle estimation algorithm of slowly rolling munition taking time delay of measurement into account when measurement comes in delayed fashion. As the measurement is passed through low pass filter for numerical stabilization and de-noising purpose which induces time delay, we design augmented state Kalman filter that incorporates distribution models of stochastic delay over time. Flight experiment was conducted to verify the algorithm at around 250m high AGL(Above Ground Level) conveying velocity of 28m/s from fixed-wing mother plane to the munition. Munition was made spun with respect to its roll axis using internal reaction wheel afterward. Numerical comparison of proposing method's roll estimation performance with that of commercial aerospace graded GPS/INS shows that proposed filter design can effectively compensate time delay of measurement.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.577-589
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• 2021

Drone mapping systems can be applied to many fields such as disaster damage investigation, environmental monitoring, and construction process monitoring. To integrate individual sensors attached to a drone, it was essential to undergo complicated procedures including time synchronization. Recently, a variety of composite sensors are released which consist of visual sensors and GPS/INS. Composite sensors integrate multi-sensory data internally, and they provide geotagged image files to users. Therefore, to use composite sensors in drone mapping systems, mapping accuracies from composite sensors should be examined. In this study, we analyzed the mapping accuracies of a composite sensor, focusing on the data acquisition area and pre-calibration effect. In the first experiment, we analyzed how mapping accuracy varies with the number of ground control points. When 2 GCPs were used for mapping, the total RMSE has been reduced by 40 cm from more than 1 m to about 60 cm. In the second experiment, we assessed mapping accuracies based on whether pre-calibration is conducted or not. Using a few ground control points showed the pre-calibration does not affect mapping accuracies. The formation of weak geometry of the image sequences has resulted that pre-calibration can be essential to decrease possible mapping errors. In the absence of ground control points, pre-calibration also can improve mapping errors. Based on this study, we expect future drone mapping systems using composite sensors will contribute to streamlining a survey and calibration process depending on the data acquisition circumstances.

• 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.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.3
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• pp.313-322
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• 2005

Rapid advances in technology and changes in human and cultural activities bring about changes to the earth surface in terms of spatial extension as well as time frame of the changes. Such advances introduce shorter updating frequency of maps and geospatial database. To satisfy these requirements, recent research efforts in the geoinformatics field have been focused on the automation and speeding up of the mapping processes which resulted in products such as the digital photogrammetric workstation, GPSIINS, applications of satellite imagery, automatic feature extraction and the LiDAR system. The possibility of automatically extracting buildings and generating contours from airborne LiDAR data has received much attention because LiDAR data produce promising results. However, compared with the manually derived building footprints using traditional photogrammetric process, more investigation and analysis need to be carried out in terms of accuracy and efficiency. On the other hand, generation of the contours with LiDAR data is more efficient and economical in terms of the quality and accuracy. In this study, the effects of various conditions of the pre-processing phase and the subsequent building extraction and contour generation phases for digital mapping have on the accuracy were investigated.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.859-866
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• 2009

The article discusses an issue of estimating the airspeed of an autonomous flying vehicle. Airspeed is the difference between ground speed and wind speed. It is desirable to know any two among the three speeds for navigation, guidance and control of an autonomous vehicle. For example, ground speed and position are used to guide a vehicle to a target point and wind speed and airspeed are used to maximize flight performance such as a gliding range. However, the target vehicle has not an airspeed sensor but a ground speed sensor (GPS/INS). So airspeed or wind speed has to be estimated. Here, airspeed is to be estimated. A vehicle's dynamics and its dynamic parameters are used to estimate airspeed with attitude and angular speed measurements. Kalman filter is used for the estimation. There are also two major sources arousing a robust estimation problem; wind speed and altitude. Wind speed and direction depend on weather conditions. Altitude changes as a vehicle glides down to the ground. For one reference altitude, multiple model Kalman filters are pre-designed based on several reference airspeeds. We call this group of filters as a cluster. Filters of a cluster are activated simultaneously and probabilities are calculated for each filter. The probability indicates how much a filter matches with measurements. The final airspeed estimate is calculated by summing all estimates multiplied by probabilities. As a vehicle glides down to the ground, other clusters that have been designed based on other reference altitudes are activated. Some numerical simulations verify that the proposed method is effective to estimate airspeed.