• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.33.1-33
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• 2002

The INS provides high rate position, velocity and attitude data with good short-term stability while the GPS provides position and velocity data with long-term stability. By integrating the INS with GPS, a navigation system can be achieved to provide highly accurate navigation performance. For the best performance, time synchronization of GPS and INS data is very important in GPS/INS integrated system. But, it is impossible to synchronize them exactly due to the communication and computation time-delay. In this paper, to reduce the error caused by the measurement time-delay in GPS/INS integrated systems, error compensation methods using separate bias Kalman filter are suggested for both the...

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.55-55
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• 2000

This paper presents a fault detection and isolation(FDI) method based on Ceneralized Likelihood Ratio(GLR) test for the tightly coupled INS/GPS. State and measurement GLR tests detect INS or GPS fault. Once the fault is detected, Multi-hypothesized GLR scheme performs the fault isolation between INS and GPS and find which satellite malfunctions. Simulation results show that the GLR method is effective enough to detect and isolate a fault of the integrated navigation system.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.944-952
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• 2001

Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.982-988
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• 2006

The errors of INS (Inertial Navigation System) are known to grow in time. To compensate the accumulated errors, measurements of external or onboard sensors are extensively utilized to form an integrated navigation system. Recently, INS/GPS integrated navigation systems have become popular since exact position and velocity information can be utilized by low cost GPS receivers. Unfortunately, this configuration cannot be trusted at all times especially when there are intentional or unexpected jammings and interruptions. To aid INS irrespectively of these cases, an INS/Image sensor integrated navigation system configuration is designed only based on the information of image sensor gimble angles. The performance of the INS/Image sensor integrated navigation system is evaluated by Monte Carlo simulation.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.197-198
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• 2008

A software platform which is able to evaluate the performances of a GPS/INS integrated system has been developed in this paper. And it consists of four parts including GUI(Graphic User Interface) part, GPS part, INS part and integrated filter part. It basically offers the loosely, tightly and deeply coupled GPS/INS algorithms, and many design parameters can be changed by users via GUI. Each functions of the platform has been confirmed with GPS signals and IMU data from commercial simulators.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.599-606
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• 2014

Since the accuracy of Global Positioning System (GPS)-based vehicle positioning system is significantly degraded or does not work appropriately in the urban canyon, the integration techniques of GPS with Inertial Navigation System (INS) have intensively been developed to improve the continuity and reliability of positioning. However, its accuracy is degraded as INS errors are not properly corrected due to the GPS signal blockage. Recently, the image-based positioning techniques have been started to apply for the vehicle positioning for the advanced in processing techniques as well as the increased the number of cars installing the camera. In this study, Single Photo Resection (SPR), which calculates the camera exterior orientation parameters using the Ground Control Points (GCPs,) has been integrated with the INS/GPS for continuous and stable positioning. The INS/GPS/SPR integration was implemented in both of a loosely and a tightly coupled modes, based on the Extended Kalman Filter (EKF). In order to analyze the performance of INS/SPR integration during the GPS outage, the simulation tests were conducted with a consideration of factors affecting SPR performance. The results demonstrate that the accuracy of INS/SPR integration is depended on magnitudes of the GCP errors and SPR processing intervals. Additionally, the simulation results suggest some required conditions to achieve accurate and continuous positioning, used the INS/SPR integration.

• ETRI Journal
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• v.35 no.5
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• pp.943-946
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• 2013

Instead of the extended Kalman filter, the unscented Kalman filter (UKF) has been used in nonlinear systems without initial accurate state estimates over the last decade because the UKF is robust against large initial estimation errors. However, in a multirate integrated system, such as an inertial navigation system (INS)/Global Positioning System (GPS) integrated navigation system, it is difficult to implement a UKF-based navigation algorithm in a low-grade or mid-grade microcontroller, owing to a large computational burden. To overcome this problem, this letter proposes a modified UKF that has a reduced computational burden based on the basic idea that the change of probability distribution for the state variables between measurement updates is small in a multirate INS/GPS integrated navigation filter. The performance of the modified UKF is verified through numerical simulations.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2433-2435
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• 2000

Inertial Navigation System(INS) provides short-term accurate navigation solution but its error grows with time due to integration characteristics. Meanwhile, Global Positioning System(GPS) provides long-term stable solution but it has poor error characteristics in high dynamic region. So for its synergistic relationship, an integrated INS/GPS systems has been widely used as an advanced navigation system. Generally, two kinds of integration method are used. One is loosely coupled mode which uses GPS-derived position and velocity as measurements in an integrated Kalman filter. The other is tightly coupled one which uses pseudorange and pseudorange rate as Kalman filter measurements. In this paper the system error models and observation models for two kinds of integrated systems are derived, respectively, and their performance are compared through Monte-Carlo simulations.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.387-395
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• 2020

Accuracy of an integrated Global Positioning System (GPS) / Inertial Navigation System (INS) relies heavily on the visibility of GPS satellites. Especially, its accuracy is dramatically degraded in urban canyon due to signal obstructions due to large structures. In this paper, we propose a new integrated positioning system that effectively combines INS, GPS, ultrasonic sensor, and barometer in GPS-denied environments. In the proposed system, the ultrasonic sensor provides velocity information along the forward direction of moving vehicle. The barometer output provides height information compensated for the pressure variation due to fast vehicle movements. To evaluate the performance of the proposed system, an experiment was carried out by mounting the proposed system on a test car. By the experiment result, it was confirmed that the proposed system bears good potential to maintain positioning accuracy in harsh urban environments.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.1
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• pp.67-77
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• 2001

In recent navigation system, the profitable solution is to integrate the GPS and Stapdwon INS (SDINS) system and its integration allows compensation for shortcomings of each system. This paper describes the hardware preparation and presents the test results obtained from the automobile test of the developed system. The automobile tests was conducted with two kinds of inertial sensors and GPS receivers : short range and middle range test, to verify and evaluate the performance of the integrated navigation system. The reference of position is given by the Differential GPS(DGPS) which has cm-level accuracy to compare the accuracy of system. Kalman filtering is used for integrating GPS and SDINS and this filter effectively allows the long-term stability of GPS to correct and decrease the time deviation error of SDINS.