• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.55-63
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• 2010

This paper describes performance improvement of GPS/DR Integration system using area decision algorithm and vehicle movement information. In GPS signal blockage area, i.e., tunnel and underground parking area, DR sensor errors are accumulated and navigation solution is gradually diverged. We use the car movement information according to moving area to correct the DR sensor error. Also, vehicle movement is decided as stop, straight line, turn and movement changing region through DR sensor data analysis. The car experiment is performed to verify the supposed method. The results show that supposed method provides small position and heading error than previous method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7424-7429
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• 2014

GPS (Global Positioning System) is currently used widely in the ground section, such as surveying, mapping, geodesy, geophysics, the aviation section, such as aerial navigation and aerial photography, the sea section, including ship navigation and bathymetry, and space section, such as the satellite orbit and Earth's orbit. On the other hand, its use is limited due to the professional knowledge and expense to process the data for precise analysis. As a result, a web-based data processing solution for precise point positioning using GPS data was developed by c# for non-specialized people to process easily. In addition, the crustal movement speed of Korea after an earthquake was calculated to be an average of 30mm/year for each CORS, suggesting that it is possible to monitor crustal movement.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.1
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• pp.1-10
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• 2015

In urban area, since multipath and signal attenuations frequently occur due to street trees, street lights and buildings, it is difficult to obtain accurate navigation solution using GPS. As these problems also impact negatively on the INS/GPS coupled system, implementing advanced transportation systems such as autonomous navigation system and Intelligent Transportation System (ITS) become quite hard. For this reason, to alleviate deterioration of navigation system performance in urban area, direction information extraction algorithm using vision system is proposed in this paper. 2D Finite Rate of Innovation (FRI) technique is applied to extract lane edges. The proposed technique is simulated using road images and feasibility of proposed technique is analyzed through the simulation results.

• Bulletin of the Korean Space Science Society
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• 1998.10a
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• pp.63.1-63
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• 1998

• Journal of Satellite, Information and Communications
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• v.6 no.1
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• pp.80-85
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• 2011

In this paper, a software-based real-time GPS L1 receiver is proposed for the block correlation techniques. Recently various navigation satellite navigation receivers in the environment for the development of more efficient software-based real-time receiver need to be developed. It is composed of components such as signal supplier, signal acquisition, signal tracking, navigation data processing, and navigation solution. They are designed and implemented as component based software for enhancing reusability and modifiability for user to have more flexibility during development of receiver. This paper will describe design, implementation, and verification of the developed realtime software GNSS receiver.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.377-382
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• 2006

Precision approach and landing of aircraft in a remote landing zone autonomously present several challenges. Firstly, the exact location, orientation and elevation of the landing zone are not always known; secondly, the accuracy of the navigation solution is not always sufficient for this type of precision maneuver if there is no DGPS availability within close proximity. This paper explores an alternative approach for estimating the navigation parameters of the aircraft to the landing area using only time-differenced GPS carrier phase measurement and range measurements from a vision system. Distinct ground landmarks are marked before the landing zone. The positions of these landmarks are extracted from the vision system then the ranges relative to these locations are used as measurements for the extended Kalman filter (EKF) in addition to the precise time-differenced GPS carrier phase measurements. The performance of this navigation algorithm is demonstrated using simulation.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.1
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• pp.27-33
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• 2017

GPS provides the positioning solution in most areas of the world. However, the position error largely occurs in the urban area due to signal attenuation, signal blockage, and multipath. Although many studies have been carried out to solve this problem, a definite solution has not yet been proposed. Therefore, research is being conducted to solve the vehicle localization problem in the urban environment by converging sensors such as cameras and Light Detection and Ranging (LIDAR). In this paper, the precise vehicle localization using 3D LIDAR (Velodyne HDL-32E) is performed in the urban area. As there are many tall buildings in the urban area and the outer walls of urban buildings consist of planes generally perpendicular to the earth's surface, the outer wall of the building meets at a vertical corner and this vertical corner can be accurately extracted using 3D LIDAR. In this paper, we describe the vertical corner extraction method using 3D LIDAR and perform the precise localization by combining the extracted corner position and GPS/DR information. The driving test was carried out in an about 4.5 km-long section near Teheran-ro, Gangnam. The lateral and longitudinal RMS position errors were 0.146 m and 0.286 m, respectively and showed very accurate localization performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.11
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• pp.1044-1050
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• 2013

This paper analyzes what is mitigated as spoofing attack using the U-Blox Receiver and GPS RF signal generator developed at ETRI. Generally the spoofing attack made the target receiver to be wrong navigation solution by providing false measurement of code and carrier. So we analyzed the impact of spoofing attack through the signal strength and navigation solution. In oder to test of effect of anti-spoofing signal, we consider the signal with antiphase code to spoofing signal and generated GPS normal signal and spoofing signal and anti-spoofing signal using GPS RF signal generator. This paper analyzed that the GPS receiver was responded to the spoofing attack according to code phase difference between spoofing and anti-spoofing signal. We confirmed that the spoofing signal was disappeared by anti-spoofing signal if code phase is an exact match.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.93-95
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• 2013

The conventional assistive tool for visually impaired people provide Simple service using a ultrasound, or an RFID tag to identify the obstacles. It is impossible to clear guide and has a vulnerability to unforeseen circumstances because of short recognition distance, The ARM Cortex-A9 Platform based implementation of the Portable Navigation System and Service Center will help the visually impaired gait. The Service Center will also provide solution for the lack of jobs due to the increase of the aging population. Navigation System that the visually impaired can carry possessing devices such as a camera, GPS, Audio, Ethernet transmit Image shown at the location of the visually impaired, GPS information and Sound Via TCP / IP. The staff of the service center receives information and can provide directions by communicating with them. So, the system can provide effective guidance to the visually impaired.