• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.569-575
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• 2013

This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2321-2330
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• 2015

A variety of studies for indoor positioning are now being in progress due to the limit of GPS that becomes obsolete in the room. However, most of them are based on private wireless networks and the situation is difficult to commercialize them since they are expensive in terms of installation and maintenance costs, non-real-time, and not accurate. This paper applies the mark recognition algorithm used in existing augmented reality applications to the indoor vehicle positioning application. It installs floor marks on the ground, performs the perspective transformation on it and decodes the internal data of the mark and, as a result, it obtains an absolute coordinate. Through the geometric analysis, it obtains current position (relative coordinates) of a vehicle away from the mark and the heading direction of the vehicle. The experiment results show that when installing the marks every 5 meter, an error under about 30 cm occurred. In addition, it is also shown that the mark recognition rate is 43.2% of 20 frames per second at the vehicle speed of 20km/h. Thus, it is thought that this idea is commercially valuable.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.153-159
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• 2016

Rivers refer to either natural or artificial structures whose primary functions are flood control and water conservation. Due to recent localized torrential downpours led by climate change, large amounts of eroded soil have been carried away, forming deposits downstream, which in turn degrades the capacity to fulfill these functions. To manage rivers more effectively, we need data on riverbed erosion and deposition. However, environmental factors make it challenging to take measurements in rivers, and data errors tend to prevent researchers from grasping the current state of erosions and deposits. In this context, the aim of the present study is to provide basic data required for river management. To this end, the author made annual measurements with a Real-time Kinematic-Global Positioning System (RTK-GPS) and a total station in Pats Cabin Canyon, Oregon, United States, and also prepared thematic maps of erosion and deposition thickness as well as water depth profiles based on a GIS spatial analysis. Furthermore, the author statistically analyzed the accuracy of three dimensional (3D) measurement points and only used the data that falls within two standard deviations (i.e. ±2σ). In addition, the author determined a threshold for a DEM of Difference (DoD) by installing measurement points in the rivers and taking measurements, and then estimated erosion and deposition thickness within a confidence interval of ±0.1m. Based on the results, the author established reliable data on river depth profiles and thematic maps of erosion and deposition thickness using pre-determined work flows. It is anticipated that the riverbed data can be utilized for effective river management.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.103-109
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• 2012

Digital speedometer which is supposed to provide the basic data for analyzing human factors of drivers has a limitation for human behavior studies of drivers, because it records limited driving information including GPS velocities. Besides, Black Box, which is currently being actively commercialized in the market, records mostly vehicles' risky patterns rather than drivers' behaviors. As a result, it also shows a limit to analyze dangerous driving patterns. This study performed a risky driving study for human factor analysis. This study conducted before and after comparisons for real time warning study using a risky driving judgment device. The analysis was conducted based on Longitudinal acceleration, Lateral acceleration, and Yaw rate of vehicles.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.3
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• pp.367-374
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• 2009

Every year there are great socio-economic loss and damage caused by landslides in steep slopes. According to recent statistics, the percentage of casualty due to breakdown in steep slopes was 27.3% of all natural disasters occurring over the past decade($1998{\sim}2007$). Therefore, the nationwide scale survey on the landslide susceptibility was made to recognize the status quo for appropriate troubleshooting measure against the collapse of steep slopes. Nevertheless, few dent that the data collected is not sufficient to grasp the overall understanding of the onsite situation due to lack of spatial information. As a result, the study aims to develop a program enabling to send on site topological data and prefixed data-gather criteria directly to the central management server in real-time basis. It will be conducted through mobile devices and portable GPS system, accordingly. This program is expected to be implemented as an efficient application tool of slope spatial information acquisition.

• Journal of KIISE:Information Networking
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• v.29 no.3
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• pp.224-232
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• 2002

The routing protocols designed for wired networks can hardly be used for mobile ad-hoc networks due to limited bandwidth of wireless transmission and unpredictable topological change. Recently, several routing protocols for mobile ad-hoc networks have been proposed. However, when these protocols are applied to support real time services like multimedia transmission, they still have problems in ad-hoe networks, where the topology changes drastically. In this paper, we propose a new route selection algorithm which selects the most reliable rouse that is impervious to route failures by topological changes by mobile hosts. For reliable route selection, the concept of virtual zone (stable lone and caution zone) is proposed. The lone is located in a mobile node's transmission range and determined by mobile node's mobility information received by Global Positioning System (GPS). The proposed algorithm is applied to the route discovery procedure of the existing on-demand routing protocol, AODV, and evaluated by simulation in various traffic conditions and mobility patterns.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.55-62
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• 2013

This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.232-239
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• 2016

Recently, in order to increase the efficiency and mission success rate of UAVs (Unmanned Aerial Vehicles), the necessity for formation flights is increased. In general, GPS (Global Positioning System) is used to obtain the relative position of leader with respect to follower in formation flight. However, it can't be utilized in environment where GPS jamming may occur or communication is impossible. Therefore, in this study, monocular vision is used for measuring relative position. General PC-based vision processing systems has larger size than embedded systems and is hard to install on small vehicles. Thus FPGA-based processing board is used to make our system small and compact. The processing system is divided into two blocks, PL(Programmable Logic) and PS(Processing system). PL is consisted of many parallel logic arrays and it can handle large amount of data fast, and it is designed in hardware-wise. PS is consisted of conventional processing unit like ARM processor in hardware-wise and sequential processing algorithm is installed on it. Consequentially HW/SW co-designed FPGA system is used for processing input images and measuring a relative 3D position of the leader, and this system showed RMSE accuracy of 0.42 cm ~ 0.51 cm.

• Journal of KIISE
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• v.42 no.2
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• pp.190-202
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• 2015

Much research has been conducted on location-based intelligent personal assistants that can understand a user's intention by learning the user's route model and then inferring the user's destinations and routes using data of GPS and other sensors in a smartphone. The intelligence of the location-based personal assistant is contingent on the accuracy and efficiency of the real-time predictions of the user's intended destinations and routes by processing movement information based on uncertain sensor data. We propose a robust particle filter based on Dynamic Bayesian Network model to infer the user's routes. The proposed robust particle filter includes a particle generator to supplement the incorrect and incomplete sensor information, an efficient switching function and an weight function to reduce the computation complexity as well as a resampler to enhance the accuracy of the particles. The proposed method improves the accuracy and efficiency of determining a user's routes and destinations.

• Journal of Korean Society for Geospatial Information Science
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• v.3 no.2 s.6
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• pp.131-136
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• 1995

In this paper, We explain the development of helicopter avation information system which provides the current location and other pre-saved informations in order to guarantee the safe aviation. The system we developed has the functions such as displaying digital map data and current location, route planning, displaying the rate of deviation, calculating and displaying the cross sectional view through the route and providing a real-time speed, heading and other informations. In this system, we use GPS to get the current location, made the 1:250,000 digital map to display the current location and made the cross sectional view from the DEM(Digital Elevation Mode)) data to help safe aviation. This system provides many kinds of route setting methods by using UTM coordinates, Lati. Longi, coordinates, database of heliport location, scanned map, etc., and displaying the heading and distance. Moreover, it also has a characteristic of providing a consistent user interface.