• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.201-210
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• 1998

Inertial Navigation System(INS) can provide the vehicle position and velocity information using inertial sensor outputs without the use of external aids. Unfortunately INS navigation error increases with time due to inertial sensor errors, and therefore it is desirable to combine INS with external aids such as GPS, TACAN, OMEGA, and etc.. In this paper we propose an integration algorithm of commercial GPS/GLONASS and INS where an adaptive filter for signal processing of GPS/GLONASS receiver and the 12th order Kalman filter for aided strapdown INS(SDINS) we employed. Simulation results show that the proposed adaptive filter can effectively remove a randomly occurring abrupt jump due to sudden corruption of the received satellite signal and that the Kalman filter performs satisfactorily.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.493-495
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• 2004

In this paper, shows a research in accordance with the design the implementation of the localization system for mobile robot using INS(Inertial Navigation System) and GPS(Global Positioning System). First, a Strapdown Inertial Navigation System : SDINS is designed and implemented for low speed walking robot, by modifying Inertial Navigation System which is widely used for rocket, airplane, ship and so on. In addition, thesis proposes the localization of robot with the method of loosely coupled method by using Kalman Filter with INS/GPS integrated system to utilize assumed position and steed data from GPS.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.6
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• pp.373-379
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• 2015

A hybrid navigation system is implemented to apply for a mobile robot. The hybrid navigation system consists of an inertial navigation system and a global positioning system. The inertial navigation system quickly calculates the position and the attitude of the robot by integrating directional accelerations, angular speed, and heading angle from a strap-down inertial measurement unit, but the results are available for a short time since it tends to diverge quickly. Global positioning system delivers position, heading angle, and traveling speed stably, but it has large deviation with slow update. Therefore, a hybrid navigation system uses the result from an inertial navigation system and corrects the result with the help of the global positioning system where an indirect feedback Kalman filter is used. We implement and confirm the performance of the hybrid navigation system through driving a car attaching it.

• Journal of Advanced Navigation Technology
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• v.23 no.3
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• pp.228-236
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• 2019

Recently, multi-sensor integration techniques have been actively studied to obtain reliable and accurate navigation solution in GPS (Global Positioning System)-denied harsh environments such as urban canyons, tunnels, and underground roads. In this paper, we propose a low-cost ultrasonic-speedometer utilizing the characteristics of the ultrasonic propagation. An efficient integrated INS (inertial navigation system)/ultrasonic-speedometer navigation system is also proposed to improve the accuracy of positioning in GPS-denied environments. To evaluate the proposed system, car experiments with field-collected measurements were performed. By the experiment results, it was confirmed that the proposed INS/ultrasonic-speedometer system bounds the positioning error growth effectively even though GPS signal is blocked more than 10 seconds and a low-cost MEMS IMU (micro electro mechanical systems inertial measurement unit) is utilized.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.10 no.1
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• pp.35-44
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• 2002

Inertial Navigation System(INS) has been used in the field of air navigation for a long time but is not popular in general aviation due to high price. Recently low-price GPS is available but vulnerable to radio interference. As an alternative on these problems, GPS/INS integrated navigation system has been considered. GPS/INS is capable of implementing navigation with low-price inertial sensors but its accuracy is dependent upon how much drift of INS may be calibrated by using GPS. In order to apply GPS/INS to air navigation, it must be investigated how long drift of INS in case of no GPS aiding will be bounded within requirements for safe flight. From the above motivation, the flight test for GPS/INS navigation system was conducted in order to make sense its performance in air navigation and its result was shown.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1450-1455
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• 2005

This paper describes a DR construction for land navigation and the sigma point based receding horizon Kalman FIR (SPRHKF) filter for DR/GPS hybrid navigation system. A simple DR construction is adopted to improve the performance both of the pure land DR navigation and the DR/GSP hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system for land navigation seamlessly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.293-294
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• 2011

• Journal of Biosystems Engineering
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• v.33 no.6
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• pp.423-429
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• 2008

This study was performed to investigate the effects of inertial navigation system (INS) / global positioning system (GPS) sensor fusion for agricultural vehicle navigation. An extended Kalman filter algorithm was adopted for INS/GPS sensor fusion in an integrated mode, and the vehicle dynamic model was used instead of the navigation state error model. The INS/GPS system was consisted of a low-cost gyroscope, an odometer and a GPS receiver, and its performance was tested through computer simulations. When measurement noises of GPS receiver were 10, 1.0, 0.5, and 0.2 m ($1{\sigma}$), RMS position and heading errors of INS/GPS system at 5 m/s straight path were remarkably reduced with 10%, 35%, 40%, and 60% of those obtained from the GPS receiver, respectively. The decrease of position and heading errors by using INS/GPS rather than stand-alone GPS can provide more stable steering of agricultural equipments. Therefore, the low-cost INS/GPS system using the extended Kalman filter algorithm may enable the self-autonomous navigation to meet required performance like stable steering or more less position errors even in slow-speed operation.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.3
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• pp.155-163
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• 2018

This study examined methods to enhance navigation performance and reduce the divergence of navigation solutions that may occur in the event of global positioning system (GPS) failure by integrating the GPS/inertial navigation system (INS) with the three-dimensional (3D) magnetic vector measurements of a magnetometer. A magnetic heading aiding method that employs a magnetometer has been widely used to enhance the heading performance in low-cost GPS/INS navigation systems with insufficient observability. However, in the case of GPS failure, wrong heading information may further accelerate the divergence of the navigation solution. In this study, a method of integrating the 3D magnetic vector measurements of a magnetometer is proposed as a countermeasure for the case where the GPS fails. As the proposed method does not require attitude information for integration unlike the existing magnetic heading aiding method, it is applicable even in case of GPS failure. In addition, the existing magnetic heading aiding method utilizes only one-dimensional information in the heading direction, whereas the proposed method uses the two-dimensional attitude information of the magnetic vector, thus improving the observability of the system. To confirm the effect of the proposed method, simulation was performed for the normal operation and failure situation of GPS. The result confirmed that the proposed method improved the accuracy of the navigation solution and reduced the divergence speed of the navigation solution in the case of GPS failure, as compared with that of the existing method.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.174-185
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• 2006

This paper describes a DR construction for land navigation and the sigma point based receding horizon Kalman FIR (SPRHKF) filter for DR/GPS hybrid navigation system. A simple DR construction is adopted to improve the performance both of the pure DR navigation and the DR/GSP hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system for land navigation seamlessly.