• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.739-745
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• 2006

This paper presents performance improvement of the INS velocity-adided GPS carier tracking loop. To this end, INS velocity-aided GPS carrier tracking loop was modeled as a feedfoward and a feedback loop system. In the phase tracking loop, it was shown that the tracking error caused by the dynamic motion of the vehicle can be compensated with the aiding of the INS information irrespective of the loop order and bandwidth. However, the signal trcking error increases as the INS error increases. It was also shown that in order to remove the tracking error caused by INS bias error, more than or equal to 2nd order PLL should be used. Experiments were carried out and the experimental results were compared with the analysis results.

• Journal of Aerospace System Engineering
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• v.4 no.3
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• pp.17-23
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• 2010

GPS sensors provide accurate position and velocity of moving vehicles. However, GPS is weak at intermittent signal loss and large position error. Combination with INS improves the GPS position accuracy during the GPS signal loss. In this paper, a fusion filter using GPS and INS is developed and its perfomance is analyzed with RC car and RC airplane experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.702-710
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• 2008

In this paper, the observability of the INS/GPS integrated system for a land vehicle is analyzed on measurements and different filters with respect to the measurements are designed. In the stationary case, it is shown that horizontal accelerometer biases and vertical attitude errors and gyro biases are unobservable. An 8-state filter is designed based on the observability analysis. When GPS signal is available, a 15-state filter is used with position and velocity measurements. To estimate the INS errors even in the case that GPS signal is blocked a filter is designed in consideration of the non-holonomic constraints of a land vehicle. In this case, the horizontal position and velocity errors and vertical attitude error are unobservable. However, a 12-state filter including the velocity states is designed to estimate the accelerometer biases. When GPS signal recovers, a 9-state filter is used excluding the sensor biases. This paper presents a multi-dimensional filter that switches the four filters according to the usable measurements and maneuver environments. A simulation is carried out to verify the performance of the proposed filter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.4
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• pp.362-369
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• 2011

In this paper, vSLAM aided integrated navigation system is implemented and performance analysis of the system is completed via flight test. The system can suppress divergence of position error of INS only system by updating vSLAM correction information when temporary GPS signal outage occurs in bad radio condition. In the flight test, integrated hardware containing GPS, IMU and camera is loaded under RC electric helicopter. Performance of the integrated navigation system is verified by comparing estimated position of INS/vSLAM system with that of INS only system.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2075-2077
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• 2001

For precise positioning, GPS carrier measurements are often used. In this case, accurate position having mm${\sim}$cm error can be obtained. For 3D positioning, in CDGPS, more than five carrier phase measurements are required. When GPS signals are blocked or carrier phase measurements are insufficient, it cannot provide positioning solution. By integrating CDGPS with INS, continuity of positioning solution can be guaranteed. However, when a vehicle moves in low speed or in stationary, the CDGPS/INS integrated system is difficult to compensate INS attitude errors because GPS velocity error become relatively lange. In this paper, we used the 3D attitude GPS receiver to compensate the INS attitude error. By field experiments, it is shown that the proposed integration system maintains the navigation performance even when a vehicle is in low speed or GPS signal is blocked for a period of time.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.8
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• pp.767-773
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• 2009

This research have introduced wavelet signal processing technic for improving navigation signals. INS signals can be distorted with conventional pre-filtering method such as low-pass filtering by unwanted smoothing on real signals. But in this paper, wavelet thresholding method is implemented to INS signal to denoise for INS-GPS integrated system. This method reduces signal noise but not distorts the rapid varing signal. And this paper applied thresholding to INS-GPS integrated navigation system and improved navigation performance.

• 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 Institute of Electronics Engineers of Korea SC
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• v.46 no.3
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• pp.22-30
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• 2009

GPS and INS integrated systems are expected to become commonly available as a result of low cost Micro-Electro-Mechanical Sensor (MEMS) technology. However, the current performance achieved by low cost sensors is still relatively poor due to the large inertial sensor errors. This is particularly prevalent in the urban environment where there are significant periods of restricted sky view. To reduce the inertial sensor error, GPS and low cost INS are integrated using a Loosely Coupled Kalman Filter architecture which is appropriate in most applications where there is good satellite availability. In this paper, we present the GPS/INS sensor Integration using Loosely Coupled Kalman Filter approach. We also compare the simulation results of Wander Azimuth Strapdown Mechanization Scheme with the reference values generated by the ZH35C trajectory simulator that is describe mathematically either by the geometry of the path, or as the position of the object over time.

• Journal of Astronomy and Space Sciences
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• v.19 no.4
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• pp.351-366
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• 2002

In this study, we developed low cost INS and (D)GPS integration for continuous attitude and position and utilized it for the determination of exterior orientation parameters of image sensors which are equipped in 4S-Van. During initial alignment process, the heading information was extracted from twin GPS and fine alignment with Kalman filter was performed for the determination of roll and pitch. Simulation and van test were performed for the performance analysis. Based on simulation result, roll and pitch error is around 0.01-0.03 degrees and yaw error around 0.1 degrees. Based on van test, position error in linear road is around 10 cm and curve around 1 m. Using direct georeferencing method, the image sensor's orientation and position information can be acquired directly from (D)GPS/INS integration. 4S-Van achieved 3D spatial data using (D)GPS/INS and image data can be applied to the spatial data integration and application such as contemporary digital map update, road facility management and Video GIS DB.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.785-791
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• 2008

Ultra-tightly coupled GPS/INS integration has been reported to show better navigation performance than that of other integration methods such as loosely coupled and tightly coupled integration. This paper uses the particle filter for ultra-tightly coupled GPS/INS integration and analyzes the navigation performance according to vehicle trajectory and the number of particles. The navigation performance of particle filter is compared with those of EKF and UKF.