• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.8
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• pp.781-789
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• 2010

In the GPS/INS integrated system fault detection, algorithm based on a chi-square distribution is commonly used. In this paper, it has been proposed simplified GPS/INS fault detection algorithm that is combined conventional RAIM (Receiver Autonomous Integrity Monitor) and algorithm based on chi-square distribution for UAV using row-grade processor. It use a fault model to verify the proposed algorithm and produced the result.

• Journal of Korea Spatial Information System Society
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• v.4 no.1 s.7
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• pp.27-37
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• 2002

Ideas providing an optimal car route using current traffic condition, maintaining the current location and the history of driven route of a car in the main central office, in where GPS signals transmitted from the driving cars are received, have been proposed. Since GPS signals occurred in certain time interval instead of all GPS signals are transmitted from the car due to the cost of transmission, an algorithm that is able to recover the missing GPS signals is required. In this paper, an efficient algorithm, which finds the driven route and the current location of a car fast, is proposed. To verify the efficiency of the proposed algorithm, it is applied to the various real GIS map and it turns out to be very effective.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.649-656
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• 2012

The Global Positioning System (GPS) is widely utilized for commercial and military applications to estimate the location of the user or object. The GPS suffers from various intentional or unintentional interferers and it requires estimating the accurate angle-of-arrival (AOA) of the GPS signal to suppress interference signals and to efficiently detect GPS data. Since the power of GPS signal is very low comparing with the noise and interference signals, it is extremely difficult to estimate GPS AOA before despreading. Although AOA of GPS signal is usually estimated after despreading, it requires choosing the GPS AOA among results of AOA estimation because they include AOAs of interference and GPS signals when existing high-power interferers. In this paper, we propose the efficient choosing algorithm of the GPS signal among the estimated AOAs. The proposed algorithm compares the estimated results before despreading and after despreading for choosing AOA of GPS signal. Computer simulation examples are presented to illustrate the performance of the proposed algorithm.

• Journal of Advanced Navigation Technology
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• v.4 no.1
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• pp.45-49
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• 2000

A GPS measurement solution, in general, is obtained as a least squares solution since the measurement includes errors such as clock errors, ionospheric and tropospheric delays, multipath effect etc. Because of the nonlinearity of the measurement equation, we utilize the nonlinear Newton algorithm to obtain a least squares solution, or mostly, use its linearized algorithm which is more convenient and effective. In this study we developed a fixed point algorithm and proved its availability to replace the nonlinear Newton algorithm and the linearized algorithm. A nonlinear Newton algorithm and a linearized algorithm have the advantage of fast convergence, while their initial values have to be near the unknown solution. On the contrary, the fixed point algorithm provides more reliable but slower convergence even if the initial values are quite far from the solution. Therefore, two types of algorithms may be combined to achieve better performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.531-537
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• 2010

Real-time Aerial Monitoring System performs the rapid mapping in an emergency situation so that the geoinformation could be constructed in near real time. In this system, the position and attitude information from GPS/INS integration algorithm is used to perform the aerial triangulation(AT) without GCPs. Therefore, if we obtain Exterior Orientation(EO) estimates from AT sequentially, EO are used as the measurements in the Kalman filter. In this study, we simulate the GPS/IMS/Image data for an UAV-based aerial monitoring system and compare the GPS/INS/AT with and without from AT. Comparative analysis showed that result from the GPS/INS/AT with EO update is more accurate than without the update. However, when the vehicle turns, the position error significantly increases which need more analysis in the future.

• International Journal of Highway Engineering
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• v.13 no.2
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• pp.175-185
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• 2011

Geometric information is a key element for evaluating traffic safety and road maintenance. This study developed an algorithm to identify horizontal alignment using global positioning system(GPS) and inertial navigation system(INS) data. Roll and heading information extracted from GPS/INS were utilized to classify horizontal alignment into tangent, circular curve, and transition curve. The proposed algorithm consists of two components including smoothing for eliminating outlier and a heuristic classification algorithm. A genetic algorithm(GA) was adopted to calibrate parameters associated with the algorithm. Both freeway and rural highway data were used to evaluate the performance of the proposed algorithm. Promising results, which 90.48% and 88.24% of classification accuracy were obtainable for freeway and rural highway respectively, demonstrated the technical feasibility of the algorithm for the implementation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.163-171
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• 2014

Based on the GPS/IMU integration, the car navigation has unstable conditions as well as drastically reduces accuracies in urban region. Nowadays, many cars mounted the camera to record driving states. If the ground coordinates of street furniture are known, the position and attitude of camera can be determined through SPR(Single Photo Resection). Therefore, an estimated position and attitude from SPR can be applied measurements in Kalman filter for updating errors of navigation solutions from GPS/IMU integration. In this study, the GPS/IMU/SPR integration algorithm was developed in loosely coupled modes through extended Kalman filters. Also, in order to analyze performances of GPS/IMU/SPR, simulation tests were conducted in GPS signal reception environments and the GCPs (Ground Control Points) distributions. In fact, the position and attitude gathered from GPS/IMU/SPR integration are more precise than the position and attitude from GPS/IMU integration. When IPs (image points), corresponded to GCPs, were concentrated in the center of image, the position error in the optical axis respectively increased. To understand effects from SPR, we plan to carry additional test on the magnitude of GCP, IP and initial exterior orientation errors.

• 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.

• Journal of IKEEE
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• v.17 no.4
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• pp.440-445
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• 2013

This paper proposes a local estimation system which combines Cell Divide Algorithm with low-cost GPS/INS fused by Extended Kalman Filter(EKF) for localization of Quad-rotor when it returns to the departure point. In the research, the low-cost GPS and INS are fused by EKF to reduce the local error of low-cost GPS and the accumulative error of INS due to continuous integration of sensor error values. When the Quad-rotor returns to the departure point in the fastest path, a moving path can be known because it moves straight, where Cell Divide Algorithm is used to divide moving route into the cells. Then it determines the closest position of data of GPS/INS system fused by EKF to obtain the improved local data. The proposed system was verified through comparing experimental localization results obtained by using GPS, GPS/INS and GPS/INS with Cell Divide Algorithm respectively.

• Journal of Satellite, Information and Communications
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• v.8 no.2
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• pp.29-35
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• 2013

In this paper, we investigate the type and detection methode of spoofing attack, and then analyze the performance of spoofing detection algorithm in GPS L1 signal through the simulation. Generally spoofer is different from the jammer, because the receiver can be operated and not. In case of spoofing the GPS receiver is hard to recognize the spoofing attack and can be operated normally without stopping because the spoofing signal is the mimic GPS signal. To evaluate the performance of spoofing detection algorithm, both the software based spoofing and GPS signal generator and the software based GPS receiver are implemented. In paper, we can check that spoofing signal can affect to the DLL and PLL tracking loop because code delay and doppler frequency of spoofing. The spoofing detection algorithm has been implemented using the pseudorange, signal strength and navigation solution of GPS receiver and proposed algorithm can effectively detect the spoofing signal.