• International Journal of Automotive Technology
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• v.8 no.6
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• pp.753-760
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• 2007

In this paper, a roll and pitch estimation algorithm using a set of accelerometers and wireless sensor networks(S/N) is presented for use in a passenger vehicle. While an inertial measurement unit(IMU) is generally used for roll/pitch estimation, performance may be degraded in the presence of longitudinal acceleration and yaw motion. To compensate for this performance degradation, a new roll and pitch estimation algorithm is proposed that uses an accelerometer array, global positioning system(GPS) and in-vehicle networks to get information from yaw rate and roll rate sensors. Angular acceleration and roll and pitch approximation are first calculated based on vehicle kinematics. A discrete Kalman filter is then applied to estimate both roll and pitch more precisely by reducing noise from the running engine and from road disturbance. Finally, the feasibility of the proposed algorithm is shown by comparing its performance experimentally with that of an IMU in the framework of an indoor test platform as well as a test vehicle.

• Annual Conference of KIPS
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• 2018.10a
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• pp.430-433
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• 2018

This paper proposes the Kalman filter (KF) with optical flow method to estimate the position and the velocity of unmanned aerial vehicles (UAVs) in the absence of global positioning system (GPS). A downward-looking camera, a gyroscope and an ultrasonic sensor are fused to compensate the measurement from optical-flow method. To overcome the problem of dealing with noise in onboard sensors, the KF is incorporated to efficiently predict the velocity and estimate the position. Basic mechanisms of optical flow and the KF are introduced and experiments are conducted to show how the techniques involved improve the estimations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.62-72
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• 2022

In this study, a miniaturized GPS band(L₁ : 1.575 GHz) antenna that can be mounted on a small drone is proposed. The miniaturization was designed by applying the perturbation method based on the λ/4 microstrip antenna and lengthening the current path at the edge of the patch. The miniaturized antenna was fabricatred such that it could be attached to the surface of styrofoam(ε_r=1.06, t=10 mm) having a size of 10 mm × 9 mm × 10 mm (0.05 λ × 0.05 λ × 0.05 λ). The thickness and length of the feeding line and the spacing between short stubs were adjusted for impedance matching. S₁₁ was found to be -18.8 dB at the center frequency of the fabricated antenna, 1.575 GHz. The radiation pattern measurement results show that the maximum gain of E_θ is 1.87 dBi in 0 directions in the xz-plane, and that E_θ is an omnidirectional characteristic with an average gain of -1.7 dBi in the yz-plane. It was found that the antenna can be used as an ultra-small microstrip antenna, which can be mounted on a small dron for GPS, and is capable of preserving a reduction ratio of 98.8% as compared to a λ/2 microstrip patch antenna.

• Journal of IKEEE
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• v.13 no.3
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• pp.72-79
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• 2009

This paper describes a compact microstrip active antenna with dual polarization. The antenna, receiving both a left-hand circularly polarized wave and a right-hand circularly polarized wave, has a function of polarization diversity. A square-shaped empty room is located on the inside of the microstrip radiator so that the size has been reduced. And slots are added around feeding point to improve input matching. Also, amplifier and switching circuitry are placed at the empty room to increase antenna gain and to select one of the circular polarizations, respectively. The proposed antenna has been applied to GPS(global positioning system). The measurement results show that it has 10dB-impedance bandwidth, 3dB axial bandwidth of about 50MHz, 3dB beamwidth of 90degree, and gain of 13dBi, respectively, for RHCP. Also, it has 3dB axial bandwidth of about 50MHz, 3dB beamwidth of 84 degree, and gain of 12dBi, respectively, for LHCP.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.43-49
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• 2017

Generally, loop filter based scalar tracking loops (LF-STL) have been used for global positioning system (GPS) signal tracking algorithm. This paper introduces the accuracy and robustness of linear-quadratic-Gaussian based vector tracking loop (LQG-VTL) algorithm instead of LF-STL. To verify the accuracy of LQG-VTL, we confirm that the measurements estimation errors of the LQG based scalar tracking loops (LQG-STL) are improved by more than 60 % compared to LF-STL. Also, when LQG-VTL is used, measurements estimation errors decrease compared to LQG-STL, and position/velocity estimation errors also decrease as the number of satellites increases. To verify the robustness of LQG-VTL, we confirm that LQG-VTL can estimate position/velocity and measurements successively compared to LF-STL in temporal signal attenuation of 30 dB-Hz during 4 seconds.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.797-807
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• 2014

The Sea Surface Temperature (SST) is one of the most important oceanic environmental factors in determining the change of marine environments and ecological activities. Satellite thermal infrared images can be effective for understanding the global trend of sea surface temperature due to large scale. However, their low spatial resolution caused some limitations in some areas where complicated and refined coastal shapes due to many islands are present as in the Korean Peninsula. The coastal ocean is also very important because human activities interact with the environmental change of coastal area and most aqua farming is distributed in the coastal ocean. Thus, low-cost airborne thermal infrared remote sensing with high resolution capability is considered for verifying its possibility to extract SST and to monitor the changes of coastal environment. In this study, an airborne thermal infrared system was implemented using a low-cost and ground-based thermal infrared camera (FLIR), and more than 8 airborne acquisitions were carried out in the western coast of the Korean Peninsula during the periods between May 23, 2012 and December 7, 2013. The acquired thermal infrared images were radiometrically calibrated using an atmospheric radiative transfer model with a support from a temperature-humidity sensor, and geometrically calibrated using GPS and IMU sensors. In particular, the airborne sea surface temperature acquired in June 25, 2013 was compared and verified with satellite SST as well as ship-borne thermal infrared and in-situ SST data. As a result, the airborne thermal infrared sensor extracted SST with an accuracy of $1^{\circ}C$.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

• Geophysics and Geophysical Exploration
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• v.23 no.4
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• pp.243-252
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• 2020

To share an understanding of trajectory measurement in surveys using borehole, this tutorial summarizes the relevant mathematical principles of the borehole deviation survey based on coordinate transform. For uncased or open holes, calculations of the azimuth-deviation-tool face rotation using three-component accelerometer and magnetometer measurements are summarized. For the steel-cased holes, calculations are based on the time-derivative formula of the coordinate transform matrix; yaw-pitch-roll angles through time are mathematically determined by integrating the threecomponent angular velocity measurements from the gyroscope while also removing the Earth's rotation effect. Sensor and data fusion to increase the accuracy of borehole deviation survey is explained with an example of the method. These principles of borehole deviation surveys can be adapted for attitude estimation in air-borne surveys or for positioning in tunnels where global positioning system (GPS) signals cannot be accessed. Information on the optimization filter that must be incorporated in sensor fusion is introduced to help future research.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.183-190
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• 2012

Conventional physical activity monitoring systems, which use accelerometers, global positioning system (GPS), heartbeats, or body temperature information, showed limited performances due to their own restrictions on measurement environment and measurable activity types. To overcome these limitations, we developed a portable exercise analysis system that can analyze aerobic exercises as well as isotonic exercises. For bioelectric signal acquisition during exercise, waist belt with two body contact electrodes was used. For exercise analysis, the measured signals were firstly divided into two signal groups with different frequency ranges which can represent respiration related signal and muscular motion related signal, respectively. After then, power values, differential of power values, and median frequency values were selected for feature values. Selected features were used as inputs of support vector machine (SVM) to classify the exercise types. For verification of statistical significance, ANOVA and multiple comparison test were performed. The experimental results showed 100% accuracy for classification of aerobic exercise and isotonic resistance exercise. Also, classification of aerobic exercise, isotonic resistance exercise, and hybrid types of exercise revealed 92.7% of accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.545-553
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• 2009

Digital Elevation Models (DEM) is widely used in establishing the topographic profile in nation spatial information. Aerial Light Detection And Ranging (LiDAR) system is one of the well-known means to produce DEM. The system has fast data acquisition procedures and less weather-dependent restrictions compared to photogrammetric approaches. In this regards, LiDAR has been widely utilized and accepted in the process of nation spatial information generation due to its sufficient positional accuracy. However, the investigation of the accuracy of aerial LiDAR data over the area of forestation with various kinds of vegetations has been barely implemented in Korea. Hence, this research focuses on the investigation of the accuracy of aerial LiDAR data over the area of forestation and the evaluation of the acquired accuracy according to the characteristics of the vegetations. The study areas include land with shrubs and its adjacent forest area with mixed tree species. The spots for the investigation have been selected to be well-distributed over the whole study areas and their coordinates are surveyed by Global Positioning Systems (GPS). Then, the surveyed information and aerial LiDAR data have been compared with each other and the result accuracy has been evaluated. Conclusively, it is recommended that LiDAR data collection to be conducted after defoliation period, especially over the areas with broadleaf trees due to the possibility of significant outliers.