• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.528-533
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• 2005

The purpose of the study is to develop ship's bearing sensor using GPS receiver which can play a role as a ship's secondary compass. In this research, two GPS receivers are used to determine the bearing in real time. Then we investigated the bearing accuracy associated with the error pattern of two GPS receivers. Especially, the results are as follows the investigation on the system design of GPS-Compass, the modeling to compute heading of sailing, the analysis on bearing accuracy with the error pattern, the defining possibility to play a role as a ship's secondary compass.

• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.35-43
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• 2012

The UGV is one of the special field robot developed for mine detection, surveillance and transportation. To achieve successfully the missions of the UGV, the accurate and reliable navigation data should be provided. This paper presents design and implementation of multi-sensor-based open architecture integrated navigation for localization of UGV. The presented architecture hierarchically classifies the integrated system into four layers and data communications between layers are based on the distributed object oriented middleware. The navigation manager determines the navigation mode with the QoS information of each navigation sensor and the integrated filter performs the navigation mode-based data fusion in the filtering process. Also, all navigation variables including the filter parameters and QoS of navigation data can be modified in GUI and consequently, the user can operate the integrated navigation system more usefully. The conventional GPS/INS integrated system does not guarantee the long-term reliability of localization when GPS solution is not available by signal blockage and intentional jamming in outdoor environment. The presented integration algorithm, however, based on the adaptive federated filter structure with FDI algorithm can integrate effectively the output of multi-sensor such as 3D LADAR, vision, odometer, magnetic compass and zero velocity to enhance the accuracy of localization result in the case that GPS is unavailable. The field test was carried out with the UGV and the test results show that the presented integrated navigation system can provide more robust and accurate localization performance than the conventional GPS/INS integrated system in outdoor environments.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.250-256
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• 2012

Unmanned ground vehicles may be operated by remote control unit through the wireless communication or autonomously. However, the autonomous technology is still challenging and not perfectly developed. For some reason or other, the wireless communication is not always available. If wireless communication is abruptly disconnected, the UGV will be nothing but a lump of junk. What was worse, the UGV can be captured by enemy. This paper suggests a method, autonomous return technology with which the UGV can autonomously go back to a safer position along the reverse path. The suggested autonomous return technology for UGV is based on multi-correlated information based DB creation and matching. While SUGV moves by remote-control, the multi-correlated information based DB is created with the multi-sensor information; the absolute position of the trajectory is stored in DB if GPS is available and the hybrid MAP based on the fusion of VISION and LADAR is stored with the corresponding relative position if GPS is unavailable. In multi-correlated information based autonomous return, SUGV returns autonomously based on DB; SUGV returns along the trajectory based on GPS-based absolute position if GPS is available. Otherwise, the current position of SUGV is first estimated by the relative position using multi-sensor fusion followed by the matching between the query and DB. Then, the return path is created in MAP and SUGV returns automatically based on the MAP. Experimental results on the pre-built trajectory show the possibility of the successful autonomous return.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.709-718
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• 2021

In this paper, it can be seen that the number of abandoned dogs increases every year through the statistics on the occurrence of abandoned animals. With the goal of reducing the number of stray dogs, a smart pet dog shoulder strap is implemented based on a real-time location tracking system using the ESP32 module and GPS sensor. It is an ESP32 module with a built-in Bluetooth module. It is input to the MCU using various sensors, and finally outputs to a smart-phone application, and communicates through the built-in blue-tooth module. In addition, it uses Neopixels to compensate the weaknesses at night through LED light emission, and automatically sets the warning distance to design a music playback system through the LED flashing effect and MP3 module. In addition, a smart pet dog shoulder strap was designed to help pet dog health care by measuring the moving distance according to the amount of activity through the gyro sensor.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.99-106
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• 2024

In this paper, we design and implement the HealthSchedule app, which records exercise data based on the GPS sensor embedded in smartphones. This app utilizes the smartphone's GPS sensor to collect real-time location information of the user and displays the movement path to the designated destination. It records the user's actual path using latitude and longitude coordinates. Users register exercise activities and destination points when scheduling, and initiate the exercise. When measuring the current location, a lime green departure marker is generated, and the movement path is displayed in blue, with the destination marker and a surrounding 25-meter radius circle shown in sky blue. Using the coordinates of the starting point or the previous location and the current GPS sensor-transmitted location coordinates, it measures the distance traveled, time taken, and calculates the speed. Furthermore, it accumulates measurement data to provide information on the total distance traveled, movement path, and overall average speed. Even when reaching the destination during exercise, the movement path continues to accumulate until the completion button is clicked. The completion button is activated when the user moves into the sky blue circular area with a radius of 25 meters, centered around the initially set destination. This means that the user must reach the designated destination, and if they wish to continue exercising without clicking the completion button, they can do so. Depending on the selected exercise type, the app displays the calories burned, aiming to increase user engagement and a sense of accomplishment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.96-116
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• 2016

Sensing coverage is a fundamental issue for Wireless Sensor Networks (WSNs). Several coverage configuration protocols have been developed; most of them presume the availability of precise knowledge about each node location via GPS receivers. However, equipping each sensor node with a GPS is very expensive in terms of both energy and cost. On the other hand, several GPS-less localization algorithms that aim at obtaining nodes locations with a low cost have been proposed. Although their deep correlation, sensing coverage and localization have long been treated separately. In this paper, we analyze, design and evaluate a novel integrated framework providing both localization and coverage guarantees for WSNs. We integrate the well-known Coverage Configuration Protocol CCP with an improved version of the localization algorithm AT-Dist. We enhanced the original specification of AT-Dist in order to guarantee the necessary localization accuracy required by CCP. In our proposed framework, a few number of nodes are assumed to know their exact positions and dynamically vary their transmission ranges. The remaining sensors positions are derived, as accurately as possible, using this little initial location information. All nodes positions (exact and derived) are then used as an input for the coverage module. Extensive simulation results show that, even with a very low anchor density, our proposal reaches the same performance and efficiency as the ideal CCP based on complete and precise knowledge of sensors coordinates.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.454-456
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• 2010

The demands for (a) individual vehicle has been gradually increasing recently due to increase of personal income and spare time. In 2009, the quantities of registered vehicles exceeds over 17,325,210 millions pieces, and the risks of traffic accidents and traffic jam are increasing days by days. It has some limitations to solve the problem of traffic jam by transportation facilities and causes lots of time and costs. For a possible solution, ITS(Intelligent Transport System) has been introduced, but it is an insufficient way for abrupt incidents or risks on roads. The riskiest matter on driving a vehicle is unforeseen situation. In this paper, the most efficient and economical system that communicates with a driver about unexpected accident by sensor network and GPS information, is introduced rather than a traditional method associated with lots of time and costs.

• Journal of KIBIM
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• v.12 no.4
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• pp.61-69
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• 2022

Earthmoving operations account for approximately 25% of construction cost, generally executed prior to the construction of buildings and structures with heavy equipment. For the successful completion of earthwork projects, it is crucial to constantly monitor earthwork equipment (e.g., trucks), estimate productivity, and optimize the construction process and equipment on a construction site. Traditional methods however require time-consuming and painstaking tasks for the manual observations of the ongoing field operations. This study proposed the use of a GPS sensor embedded in a smartphone for the tracking and visualization of equipment locations, which are in turn used for the estimation and simulation of cycle times and production rates of ongoing earthwork. This approach is implemented into a digital platform enabling real-time data collection and simulation, particularly in a 2D (e.g., maps) or 3D (e.g., point clouds) virtual environment where the spatial and temporal flows of trucks are visualized. In the case study, the digital platform is applied for an earthmoving operation at the site development work of commercial factories. The results demonstrate that the production rates of various equipment usage scenarios (e.g., the different numbers of trucks) can be estimated through simulation, and then, the optimal number of tucks for the equipment fleet can be determined, thus supporting the practical potential of real-time sensing and simulation for onsite equipment management.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.267-275
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• 2013

EKF has been widely used for GPS/INS integration as standard method but EKF has one well-known drawback. if the errors are not within the bounded region, the filter may be divergent. The particle filter has the advantage of the nonlinear and non-gaussian system. This paper proposes a method for compensating the GPS position errors based on the particle filter and presents loosely-coupled GPS/INS integration using proposed algorithm. We used GPS position pattern with particle filter and added attitude kalman filter for improving attitude accuracy. To verify the performance, the proposed method is compared with high cost GPS as reference. In the experimental result, we verified that the accuracy and robust were well improved by the proposed method filter effectively and robustness than by original loosely-coupled integration when vehicle turns at corner.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.15-31
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• 2005

Nowadays, the road safety is an important research field. One of the principal research topics in this field is the vehicle localization in the road network. This article presents an approach of multi sensor fusion able to locate a vehicle with a decimeter precision. The different informations used in this method come from the following sensors: a low cost GPS, a numeric camera, an odometer and a steer angle sensor. Taking into account a complete model of errors on GPS data (bias on position and nonwhite errors) as well as the data provided by an original approach coupling a vision algorithm with a precise numerical map allow us to get this precision.