• International Journal of Aeronautical and Space Sciences
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• v.2 no.1
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• pp.55-66
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• 2001

The Global Positioning System(GPS) and the Strapdown Inertial Navigation System(SDINS) techniques have been widely utilized in many applications. However each system has its own weak point when used in a stand-alone mode. SDINS suffers from fast error accumulation dependent on an operating time while GPS has problem of cycle slips and just provides low update rate. The best solution is to integrate the GPS and SDINS system and its integration allows compensation for each shortcomings. This paper, first, is to define and derive error equations of integrated SDINS/GPS system before it will be applied on a real hardware system with gyro, accelerometer and GPS receiver. Second, the accuracy, availability and performance of this mechanization are verified on the simulation study.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.817-823
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• 2007

GPS and INS can be integrated in 3 ways of loose, tight, and ultra-tight configuration. This paper investigates the performance of GPS/INS ultra-tightly integrated system when unscented Kalman filter(UKF) is adopted as well as extended Kalman filter(EKF). Covariance analysis is performed using UFK and EKF for tightly coupled and ultra-tightly coupled systems. Various trajectories such as straight, circle, S-shape, spiral are considered for the simulations of covariance analysis.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.247-254
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• 2006

For more accurate navigation, lever arm compensation is considered. The compensation method for GPS and an odometer is introduced and new compensation methods are proposed for an odometer to consider the effect of coordinate transformation errors and the scale factor error. The methods are applied to a GPS/INS/odometer integrated system and the simulation and experimental results show its effectiveness.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.2
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• pp.59-70
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• 2017

Since GPS signals are vulnerable to interference and obstruction, many alternate aiding systems have been proposed to integrate with an inertial navigation system. Among these alternate systems, the vision-aided method has become more attractive due to its benefits in weight, cost and power consumption. This paper proposes a loosely-coupled vision/INS integrated navigation method which can work in GPS-denied environments. The proposed method improves the navigation accuracy by correcting INS navigation and sensor errors using position and attitude outputs of a landmark based vision navigation system. Furthermore, it has advantage to provide redundant navigation output regardless of INS output. Computer simulations and the van tests have been carried out in order to show validity of the proposed method. The results show that the proposed method works well and gives reliable navigation outputs with better performance.

• Journal of Advanced Navigation Technology
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• v.8 no.2
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• pp.112-119
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• 2004

This paper proposes an attitude determination GPS/INS integrated system scheme for a UAV and presents experimental flight test results. The proposed system is designed as a part of an autopilot system and comprises a GPS attitude determination receiver, an off-the-shelf inertial measurement unit (IMU), and a navigation computer unit (NCU). UAV requires accurate attitude information for stable automatic flight control. The proposed system can provide accurate attitude information for the flight control computer (FCC) so that stable automatic flight control can be achieved. In order to verify the performance of the proposed scheme, an integrated navigation system has been developed. In order to evaluate the developed navigation system, the flight test has been performed. In the flight test, the developed system was shown to provide the position, the velocity and the attitude satisfactorily enough for stable flight control. The accuracy of the attitude information of the developed system was confirmed by comparing attitude of vertical gyro.

• Journal of Advanced Navigation Technology
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• v.23 no.3
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• pp.221-227
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• 2019

In this paper, interacting multiple model (IMM) filter was designed that guarantees a stable navigation performance even in the unstable satellite navigation position. In order to design IMM filter in INS / GPS integrated navigation system, sub filter of the IMM filter is defined as Kalman filter. In the IMM filter configuration, two subfilters are determined. Each Kalman filter defines the six-teenth state composed of position, velocity, attitude, and sensor error from the INS error equation and the states additionally derived in case of the coloured measurement noise. In order to verify the performance of the proposed filter, we compared the performance how the filter works in the presence of arbitrary error in GPS navigation solution. The Monte Carlo simulation was performed 100 times and the results were compared with the root mean square(RMS). The results show that the proposed method is stable against errors and show fast convergence.

• 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 Advanced Navigation Technology
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• v.16 no.5
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• pp.738-743
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• 2012

Kalman filter is generally used in INS/GPS integrated navigation filter. However, the INS with low performance inertia sensor can not find accurate azimuth in initial alignment stage because sensor noise level is too large compare to Earth rotation rate, therefore the performance and stability of Kalman filter can not be guaranteed. In this paper, the extended Kalman filter and particle filter combined filter structure which can be overcome large initial azimuth error is proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.9
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• pp.891-897
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• 2008

GPS can provide precise relative navigation information. But it needs a reference station in a close range and is effected by satellite observation environment. In this paper, we propose INS and Vision sensor integrated system with a known landmark geometry. This system is supposed to overcome problems of GPS only system. Using the proposed method, a relative navigation is available without a GPS reference station. The only need for the proposed system is a landmark image which is drawn on the ground. We conduct simple simulation to check the performance of this method. As a result, we confirm that it can improve the relative navigation information.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.133-139
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• 2007

An unmanned ground vehicle can perform its mission automatically without human control in unknown environment. To move up to a destination in various surrounding situation, navigational information is indispensible. In order to be adopted for an unmanned vehicle, the navigation box is small, light weight and low power consumption. This paper suggests navigation system using a low grade MEMS IMU for supplying position, velocity, and attitude of an unmanned ground vehicle. This system consists of low cost and light weight MEMS sensors and a GPS receiver to meet unmanned vehicle requirements. The sensors are basically integrated by loosely coupled method using Kalman filter and internal algorithms are divided into initial alignment, sensor error compensation, and complex navigation algorithm. The performance of the designed navigation system has been analyzed by real time field test and compared to commercial tactical grade GPS/INS system.