• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.379-388
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• 2019

Recently, a technique for acquiring spatial information data using UAV (Unmanned Aerial Vehicle) has been greatly developed. It is a very crucial issue of the GIS (Geographic Information System) mapping system that passes way point in the unmanned airframe and finally measures the accurate image and stable localization to the desired destination. Though positioning using DGPS (Differential Global Navigation System) or RTK-GPS (Real Time Kinematic-GPS) guarantee highly accurate, they are more expensive than the construction of a single positioning system using a single GPS. In the case of a low-priced single GPS system, the stability of the positioning data deteriorates. Therefore, it is necessary to supplement the uncertainty of the absolute position data of the UAV and to improve the accuracy of the current position data economically in the operating state of the UAV. The aim of this study was to present an algorithm enhancing the stability of position data in a single GPS mode of UAV with multiple GPS. First, the arrangement of multiple GPS receivers through the center of gravity of the UAV were examined. Next, MD (Mahalanobis Distance) is applied to detect instantaneous errors of GPS data in advance and eliminate outliers to increase the accuracy of previously collected multiple GPS data. Processing procedure for multiple GPS reception data by applying the center of the triangular method were presented to improve the position accuracy. Second, UAV navigation systems integrated multiple GPS through configuration of the UAV specifications were implemented. Using the unmanned airframe equipped with multiple GPS receivers, GPS data is measured with the TCM (Triangular Center Method). In addition, UAV equipped with multiple GPS were operated in study area and locational accuracy of multiple GPS of UAV with VRS (Virtual Reference Station) GNSS surveying were compared. The result showed that the error factors are compensated, and the error range are reduced, resulting in the reliability of the corrected value. In conclusion, the result in this paper is expected to realize high-precision position estimation at low cost in UAV using multiple low-cost GPS receivers.

• The Journal of the Korea institute of electronic communication sciences
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• v.4 no.4
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• pp.274-280
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• 2009

In order to estimate the accurate location of a user, Global Positioning system (GPS) requires at least four satellites. Since a conventional despreader operate for an GPS signal of interest, we need multiple despreaders for detecting multiple GPS signals. In this paper, we introduce the extension of the recently proposed system consisting of a null despreader, a conventional despreader, multi-stage CM (constant modulus) array, for the multiple GPS signals, and present the mathematical expression of the signal-to-interference-and-noise ratio (SINR). The extended system does not require the exact information of the direction of arrival (DOA) to suppress the directional interferences. We present the computer simulation to demonstrate the interference suppression performance of the proposed system for multiple GPS signals.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.93-102
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• 2007

It is essential to estimating positions of multiple robots in order to perform cooperative task in common workspace. Accordingly, we propose a new approach of cooperative localization for multiple robots utilizing correlation among GPS errors in common workspace. Assuming that GPS data of individual robot are correlated strongly as the distance among robots are close, it is confirmed that the proposed method provides improved localization accuracy. In addition, we define two operational parameters to apply proposed method in multiple robot system. With mentioned two parameters, we present a practical solution to accumulated position error in traveling long distance.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.255-261
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• 2007

We propose a optimal fusion method for localization of multiple robots utilizing correlation between GPS on each robot in common workspace. Each mobile robot in group collects position data from each odometer and GPS receiver and shares the position data with other robots. Then each robot utilizes position data of other robot for obtaining more precise estimation of own position. Because GPS data errors in common workspace have a close correlation, they contribute to improve localization accuracy of all robots in group. In this paper, we simulate proposed optimal fusion method of odometer and GPS through virtual robots and position data.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.603-607
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• 2008

This paper proposes a fast acquisition method using INS velocity and multiple correlators for high speed vehicles. In order to reduce acquisition time in GPS receiver, the method utilizes inertial velocity information and multiple correlators. Search range of the Doppler frequency is reduced by using INS velocity and the number of cells at one search can be increased by using multiple correlators. By using both multiple correlators and the INS velocity in the acquisition, search space can be greatly reduced. Experimental results show that the method gives faster signal acquisition performance than the conventional method.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.47-55
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• 2019

As the damage caused by GPS jamming has been increased, researches for detecting and preventing GPS jamming is being actively studied. This paper deals with a GPS jamming detection method using multiple GPS receiving channels and three-types machine learning techniques. Proposed multiple GPS channels consist of commercial GPS receiver with no anti-jamming function, receiver with just anti-noise jamming function and receiver with anti-noise and anti-spoofing jamming function. This system enables user to identify the characteristics of the jamming signals by comparing the coordinates received at each receiver. In this paper, The five types of jamming signals with different signal characteristics were entered to the system and three kinds of machine learning methods(AB: Adaptive Boosting, SVM: Support Vector Machine, DT: Decision Tree) were applied to perform jamming detection test. The results showed that the DT technique has the best performance with a detection rate of 96.9% when the single machine learning technique was applied. And it is confirmed that DT technique is more effective for GPS jamming detection than the binary classifier techniques because it has low ambiguity and simple hardware. It was also confirmed that SVM could be used only if additional solutions to ambiguity problem are applied.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.129-135
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• 2013

In this paper, a high precision outdoor positioning system is newly proposed using multiple GPS receivers based on the Extended Kalman Filter (EKF). Typically, the GPS signal has the instantaneous errors that degrade the positioning seriously. Using the multiple GPS receivers instead of an expensive DGPS receiver, the positioning reliability and accuracy are improved in this research as a low cost solution. To incorporate the small displacement, an INS data have been tightly coupled to the GPS data, which has the inherit disadvantage of the cumulative error occurring over time. To achieve a stabilized and accurate positioning system, the multiple GPS receiver data are fused with the INS data through the EKF process. Through real navigation experiments of an outdoor mobile robot, the performance of the proposed system has been verified to be accurate comparable to DGPS system with a lower cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.121-123
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• 2011

The accuracy of GPS varies depending on the number of GPS satellites and is declined in GPS interfering spot such as around forest or buildings. This paper proposes a localization improvement algorithm in GPS interfering spot by integrating information of multiple sensors in smartphone. The proposed algorithm is implemented in smartphone and the performance is evaluated in campus area.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.190-196
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• 2015

In this paper, we propose multiple location error compensation algorithm for GPS/INS fusion using kalman filter and introduce the way to reduce location error in 9-axis navigation devices for implementing inertial navigation technique. When evaluating location, there is an increase of location error. So navigation systems need robust algorithms to compensate location error in GPS/INS fusion. In order to improve robustness of 9-axis inertial sensor(mpu-9150) over its disturbance, we used tilt compensation method using compensation algorithm of acceleration sensor and Yaw angle compensation to have exact azimuth information of the object. And it shows improved location result using these methods combined with kalman filter.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.55-60
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• 2003

As the distance between GPS rover station and GPS base station increases, more decorrelated positioning errors limit the ability for PDGPS(Precise Differential GPS). The objective of this paper is to present the improvement of using VRS(virtual reference station) based on multiple GPS reference station network to single reference station for static positioning in post-processing mode. For this, the VRS observations from GPS observations of real reference stations are derived by using Web service in post-mode. The coordinates of check point post-processed by 27 kind of VRS observations compared with the known ones.