• 한국군사과학기술학회지
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• 제16권2호
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• pp.95-100
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• 2013

Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.89-93
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• 2009

This paper deals with obstacle avoidance for unmanned vehicle using stereo system. The "DARPA Grand Challenge 2005" shows that the robot can move autonomously under given waypoint. RADAR, IMS (Inertial Measurement System), GPS, camera are used for autonomous navigation. In this paper, we focus on stereo system for autonomous navigation. Our approach is based on Singh et. al. [5]'s approach that is successfully used in an unmanned vehicle and a planetary robot. We propose an improved algorithm for obstacle avoidance by modifying the cost function of Singh et. al. [5]. Proposed algorithm gives more sharp contrast in choosing local path for obstacle avoidance and it is verified in experimental results.

• 제어로봇시스템학회논문지
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• 제11권4호
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• pp.369-377
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• 2005

This paper describes the realization of a coordinates tracking algorithm for an EOTS (Electro-Optical Tracking System). The EOTS stabilizes the image sensors, tracks targets automatically, and provides navigation capability for vehicles. The coordinates tracking algorithm calculates the azimuth and the elevation angle of an EOTS using the inertial navigation system and the attitude sensors of the vehicle, so that LOS designates the target coordinates which are generated by a Radar. In the error analysis, the unexpected behaviors of an EOTS due to the time delay and deadbeat of the digital signals of the vehicle equipments are anticipated and the countermeasures are suggested. The application of this algorithm to an EOTS will improve the operational capability by reducing the time which is required to find the target and support flight especially in the night time flight and the poor weather condition.

• ETRI Journal
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• 제35권5호
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.241-245
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• 2005

Strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) yields reliable mission capability and enhanced navigational accuracy for spacecrafts. The theory and characteristics of integrated system based on unscented Kalman filtering is investigated in this paper. This Kalman filter structure uses unscented transform to approximate the result of applying a specified nonlinear transformation to a given mean and covariance estimate. The filter implementation subsumed here is in a direct feedback mode. Axes misalignment angles of the SINS are observation to the filter. A simple approach for simulation of axes misalignment using stars observation is presented. The SINS error model required for the filtering algorithm is derived in space-stabilized mechanization. Simulation results of the integrated navigation system using a medium accuracy SINS demonstrates the validity of this method on improving the navigation system accuracy with the estimation and compensation for gyros drift, and the position and velocity errors that occur due to the axes misalignments.

• 한국군사과학기술학회지
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• 제12권5호
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• pp.636-643
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• 2009

NHC means that the velocity of the vehicle in the plane perpendicular to the forward direction is almost zero. The main error source of NHC is the mounting misalignment which is the difference between the body frame of a land vehicle and the sensor frame of an inertial measurement unit. This paper suggests new NHC algorithm that can reduce position errors by real-time estimation of mounting misalignment. Then NHC/ZUPT integrated land navigation system is designed and its performances are analyzed by simulations with van test data. Simulation results show that the proposed NHC/ZUPT land navigation system improves navigation accuracy regardless of misalignment angle and is very useful when SDINS operates stand-alone for land vehicle navigation with large mounting misalignment.

• 한국자동차공학회논문집
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• 제16권3호
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• pp.7-14
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• 2008

Unmanned vehicle has a performance for finding the path and the way point by itself, so called orientation and direction. For the more precise navigation performance, Extended kalman filter, which is integrated with inertial navigation system and global positioning system is proposed in this paper. Extended kalman filter's performance is evaluated by the simulation and applied to the unmanned vehicle. The test result shows the effectiveness of Extended kalman filter for the navigation.

• Journal of Positioning, Navigation, and Timing
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• 제4권3호
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• pp.141-150
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• 2015

In this study, a Global Navigation Satellite System (GNSS) / Inertial Navigation System (INS) / odometer / barometer integrated navigation system that uses a commercial navigation device including Micro Electro Mechanical Systems (MEMS) accelerometer and gyroscope in addition to GNSS, odometer information obtained from a vehicle, and a separate MEMS barometer sensor was implemented, and the performance was verified. In the case of GNSS and GNSS/INS integrated navigation system that are generally used in a navigation device, the performance would deteriorate in areas where GNSS signals are not available. Therefore, an integrated navigation system that calculates a better navigation solution in areas where GNSS signals are not available compared to general GNSS/INS by correcting the velocity error of GNSS/INS using an odometer and by correcting the cumulative altitude error of GNSS/INS using a barometer was suggested. To verify the performance of the navigation system, a commercial navigation device (Softman, Hyundai Mnsoft, http://www.hyundai-mnsoft.com) and a barometer sensor (ST Company) were installed at a vehicle, and an actual driving test was performed. To examine the performance of the algorithm, the navigation solutions of general GNSS/INS and the GNSS/INS/odometer/barometer integrated navigation system were compared in an area where GNSS signals are not available. As a result, a navigation solution that has a smaller position error than that of GNSS/INS could be obtained in the area where GNSS signals are not available.

• International Journal of Aeronautical and Space Sciences
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• 제18권1호
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• pp.118-128
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• 2017

In this study, we propose a real time inertial navigation system/global positioning system (INS/GPS) integrated smoothing algorithm based on an extended Kalman filter (EKF) and a position damping loop (PDL) for synthetic aperture radar (SAR). Integrated navigation algorithms usually induce discontinuities due to error correction update by the Kalman filter, which are as detrimental to the performance of SAR as the relative position error. The proposed smoothing algorithm suppresses these discontinuities and also reduces the relative position error in real time. An EKF estimates the navigation errors and sensor biases, and all the errors except for the position error are corrected directly and instantly. A PDL activated during SAR operation period imposes damping effects on the position error estimates, where the estimated position error is corrected smoothly and gradually, which contributes to the real time smoothing and small relative position errors. The residual errors are re-estimated by the EKF to maintain the estimation performance and the stability of the overall loop. The performance improvements were confirmed by Monte Carlo simulations. The simulation results showed that the discontinuities were reduced by 99.8% and the relative position error by 48% compared with a conventional EKF without a smoothing loop, thereby satisfying the basic performance requirements for SAR operation. The proposed algorithm may be applicable to low cost SAR systems which use a conventional INS/GPS without changing their hardware configurations.

• 한국항공우주학회지
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• 제41권6호
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• pp.481-487
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• 2013

GPS/INS 항법시스템의 설치에 있어서 대다수의 경우 GPS 수신기 안테나는 차량의 외부에 설치하게 되고 IMU는 내부에 설치하게 된다. Lever Arm 오차는 이와 같이 센서의 장착 위치 차이로 인하여 발생하는 구조적인 오차에 해당한다. Lever Arm 오차는 항법성능에 직접적으로 영향을 주기 때문에 적절한 보상이 반드시 필요하다. 본 논문에서는 GPS와 INS의 속도 측정치를 활용하여 임의의 위치에 장착된 두 센서의 Lever Arm 오차를 효과적으로 추정하고 보상하는 방식을 제안하였다. 실험을 통해 제안한 알고리즘의 타당성을 검증하였으며, 항체의 회전운동 구간에서 Lever Arm 오차 보상이 특히 중요함을 보였다.