• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.25-32
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• 2017

Most of weapon systems use aided navigation system which integrates inertial navigation and aiding sensors to compensate the INS errors increasing with the passage of time. Various aid sensors can be applied such as Global Navigation Satellite System (GNSS), radar, barometer, etc., but there might exist time delay caused by signal processing or transferring aid information. This time delay leads out-of-sequence measurements (OOSM) systems. Previously, optimal and suboptimal measurment update method for OOSM systems, where the time delay length are known, are proposed. However, previous algorithm does not guarantee the positive definite property of covariance matrix. In order to improve numerical stability for aided navigation using delayed-measurement, this paper proposes a new measurement covariance update algorithm be similar to Joseph-form in Kalman filter. Futhermore, we propose how to implement it in indirect feedback Kalman filter structure, which is commonly used in aided navigation systems, for time-delayed measurement systems. Simulation and vehicle test results show effectiveness of a proposed algorithm.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.4
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• pp.30-36
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• 2011

Inertial navigation systems requires gravity model to compute gravity acceleration and its trajectory accuracy depends on the gravity model accuracy especially for a long range flight. The gravity model accuracy is important for satellite orbit prediction as well. The precision gravity model requires a precision coordinate transformation between inertial and Earth fixed coordinates. Precision gravity acceleration algorithms with a coordinate transform are studied and a computer program is developed. The effects of individual model components on trajectory error are analyzed.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.68-77
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• 2021

In this paper, a GPS/MEMS IMU integrated navigation receiver module capable of operating in a high dynamic environment is designed and fabricated, and the results is confirmed. The designed module is composed of RF receiver unit, inertial measurement unit, signal processing unit, correlator, and navigation S/W. The RF receiver performs the functions of low noise amplification, frequency conversion, filtering, and automatic gain control. The inertial measurement unit collects measurement data from a MEMS class IMU applied with a 3-axis gyroscope, accelerometer, and geomagnetic sensor. In addition, it provides an interface to transmit to the navigation S/W. The signal processing unit and the correlator is implemented with FPGA logic to perform filtering and corrrelation value calculation. Navigation S/W is implemented using the internal CPU of the FPGA. The size of the manufactured module is 95.0×85.0×.12.5mm, the weight is 110g, and the navigation accuracy performance within the specification is confirmed in an environment of 1200m/s and acceleration of 10g.

• Spatial Information Research
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• v.11 no.1
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• pp.33-40
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• 2003

For effective management of information about establishment and repair of road and road facilities, we built GPS-Van mapping system that CCD Cameras, GPS receivers and INS are integrated and using it surveyed test area. Suggested a scheme that possible put acquired data into photo database systematically. Prototype of road facilities management system using the database shows us that extraction of qualitative information and management are possible through relation attribute information. And it raise cognitive faculty of user about objects using field photographs.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.35-42
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• 2007

This paper presents an INS(Inertial Navigation System) grade, surface micro-machined differential resonant accelerometer(DRXL) manufactured by an epitaxially grown thick poly silicon process. The proposed DRXL system generates a differential digital output upon an applied acceleration, in which frequency transition is measured due to gap dependent electrical stiffness change. To facilitate the resonance dynamics of the electromechanical system, the micromachined DRXL device is packaged by using the wafer level vacuum sealing process. To test the DRXL performance, a nonlinear self-oscillation loop is designed based on the extended describing function technique. The oscillation loop is implemented using discrete electronic elements including precision charge amplifier and hard feedback nonlinearity. The performance test of the DRXL system shows that the sensitivity of the accelerometer is 24 Hz/g and its long term bias stability is about 2 mg($1{\sigma}$) with dynamic range of ${\sigma}70g$.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.774-778
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• 2008

The inaccuracy of inertial sensors used in low cost IMU's limits the usage to ARS, at best. Sensor fusion technologies are widely used to overcome this problem. GPS is the most popular secondary sensor, but GPS alone cannot fully compensate the IMU errors in the initial alignment process and rectilinear flights. This paper presents a new concept of aiding the low cost IMU with the sun line of sight vector. The simulation and experimental results in this paper proves that aiding of INS/GPS with the sun line of sight vector increases the observability and improves accuracy remarkably.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.566-573
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• 2014

This paper presents the results of an integrated navigation performance analysis for selecting the sensor of an unmanned underwater vehicle (UUV) using Monte Carlo numerical simulation. An inertial measurement unit (IMU) and Doppler velocity log (DVL) are considered to build the integrated navigation system. The position error and price of the sensor are selected as performance indices to evaluate the volunteer integrated navigation systems. Monte-Carlo simulation is introduced to analyze the circular error probability (CEP) and its variance. Simulation results provide the proper sensor combination for integrated navigation in relation to the performance and price.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.94-106
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• 2020

Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.664-667
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• 1996

This paper presents the error parameter estimation technique for IMU(Inertial Measurement Unit) which is core sensor of INS(Inertial Navigation System) and verifies it via laboratory test. Firstly the error characteristic of gyroscope and accelerometer which is contained in IMU is examined and the error modelling is executed. The error of IMU can be divided into deterministic and random part, and the deterministic error can be divided into static and dynamic part. This paper consider the random part as constant. Secondly the error parameter estimation technique and following procedure for laboratory test is explained. Thirdly according to the test procedure the IMU test for static error is executed using 2-axis rate table and estimation result is presented with discussion about its validity.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1284-1289
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• 2014

In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.