• Journal of Positioning, Navigation, and Timing
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• v.3 no.2
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• pp.37-44
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• 2014

The most effective method to overcome GPS jamming problem is to use an adaptive array antenna which has the capability of beamforming or nulling to a certain direction. In this paper, Space Time Adaptive Processing (STAP) beamforming algorithm of four elements array antenna will be designed and the anti-jamming performance will be analyzed. According to the analysis, the signal to noise ratio (SNR) and anti-jamming performance can be enhanced by beamforming algorithm. Also, the time tap effect of STAP algorithm will be analyzed theoretically and verified with array antenna modeling and simulation. Specially, the cautious selection of reference time tap in STAP can prevent the degradation of position accuracy performance.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.161-164
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• 2010

The study on terrain referenced navigation has been proceeded from 1940s in advanced country with the object of military. In this study, the analysis regarding algorithm developed using cross-correlation matching algorithm and extended Kalman filter and simulation will be introduced. As a result, the standard deviation of position error from cross-correlation matching algorithm has been calculated 34.3m. It meant that the result has stable accuracy on the navigation. However, further study on terrain referenced navigation based on analysis of various topographic characteristics should be performed.

• ETRI Journal
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• v.43 no.4
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• pp.617-629
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• 2021

Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed-loop online dense RGB-D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two-wheel differential-drive robot. It exhibits lightweight three-dimensional mapping, room-scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on-the-fly navigation while mapping.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1781-1785
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• 2004

In existing factory, robot has less necessity that consider person. However, person should be considered at design and use of service robot. To service robot can be used in everyday life along with this, more functions are required. Specially, medical service robot needs function that is intelligence function. Especially, to help patient brain disease patient (cerebral hemorrhage, cerebral infarction, imbecility), gait assistance Mobile robot consider ergonomic element necessarily. In order to develop the medical support service robot, the ergonomic design should be considered. This robot ergonomic design parameters are treated in ("evelopment of Medical Support Service Robot Using Ergonomic Design" 2003, ICASS) Fig2 show this Robot. In this study, navigation algorithm of walk assistance robot is analyzed in ergonomic view. Navigation algorithm of Mobile robot can divide by two patterns. Traditional derivative method has shortcoming in dynamic environment. Reactive method is result that react excellently in dynamic environment. However, number of behavior function is limited. So hybrid navigation algorithm was proposed by the alternative way. We consider enough user specificity at navigation algorithm application of gait assistance robot.

• Journal of Astronomy and Space Sciences
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• v.32 no.4
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• pp.387-393
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• 2015

This study presents a precise relative navigation algorithm using both laser and Global Positioning System (GPS) measurements in real time. The measurement model of the navigation algorithm between two spacecraft is comprised of relative distances measured by laser instruments and single differences of GPS pseudo-range measurements in spherical coordinates. Based on the measurement model, the Extended Kalman Filter (EKF) is applied to smooth the pseudo-range measurements and to obtain the relative navigation solution. While the navigation algorithm using only laser measurements might become inaccurate because of the limited accuracy of spacecraft attitude estimation when the distance between spacecraft is rather large, the proposed approach is able to provide an accurate solution even in such cases by employing the smoothed GPS pseudo-range measurements. Numerical simulations demonstrate that the errors of the proposed algorithm are reduced by more than about 12% compared to those of an algorithm using only laser measurements, as the accuracy of angular measurements is greater than $0.001^{\circ}$ at relative distances greater than 30 km.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.7
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• pp.627-632
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• 2007

Dual quaternion is efficient methodology to express rotation and translation of the vehicle's movements in the unified frame work. Recently, a strapdown inertial navigation algorithm based on dual quaternion was introduced. By comparing and analyzing the classical and dual-quaternion algorithms, this paper proposes a new strapdown inertial navigation algorithm that maintains the accuracy benefit of the dual-quaternion algorithm with considerable computational reduction. Simulation results show the efficiency of the proposed hybrid strapdown navigation algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.373-382
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• 2016

In this study, an EKF (Extended Kalman Filter) based database reference navigation using both gravity gradient and terrain data was performed to complement the weakness of using only one type of geophysical DB (Database). Furthermore, a new algorithm which combines the EKF and profile matching was developed to improve the stability and accuracy of the positioning. On the basis of simulations, it was found that the overall navigation performance was improved by the combination of geophysical DBs except the two trajectories in which the divergence of TRN (Terrain Referenced Navigation) occurred. To solve the divergence problem, the profile matching algorithm using the terrain data is combined with the EKF. The results show that all trajectories generate the stable performance with positioning error ranges between 14m to 23m although not all trajectories positioning accuracy is improved. The average positioning error from the combined algorithm for all nine trajectories is about 18 m. For further study, a development of a switching geophysical DB or algorithm between the EKF and the profile matching to improve the navigation performance is suggested.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.49-56
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• 2023

As interest in autonomous ships continues to grow, researchers around the world are dedicating themselves to the development of relevant technologies. However, these technologies are not yet perfect. Several technical problems remain unresolved. To address these problems, this study presents the implementation of a ship trajectory algorithm for group navigation, where followers can navigate by following the trajectory of a leader. The algorithm works by storing the leader's trajectory as a follow-point and by calculating the azimuth using the line-of-sight guidance law to reach it. A course-keeping controller based on PD control is implemented to follow the target course and a speed control algorithm is designed to prevent collisions. Sea experiments were conducted using 1 m class small RC model boats to verify the proposed algorithm. The follower successfully navigated by following the leader's trajectory and maintained the designated distance to the forward boat. This study is significant in that it implements an algorithm for the follower to follow the trajectory of the leader rather than directly following it as in conventional methods, and verifies it through sea experiments.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.557-565
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• 2018

For GNSS navigation in urban environment, a novel short delay multipath mitigation algorithm is proposed in this paper. This algorithm detects which satellite's signal is the multipath signal by using the constraint that GNSS receiver is equipped in a ground vehicle, then estimate new position after separating the measurement of that satellite. A criterion for detecting and validating the multipath signal depends on the performance grade of the GNSS receiver and the dynamics of the vehicle. In order to evaluate the proposed algorithm, the real data had been collected at the multipath environment of 4 scenarios. By post-processing the real data with both of the multipath mitigation algorithm in the receiver and the proposed algorithm, it can be checked that the position errors were less than 5 meters except the case that the number of visible satellite is lower than 5.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1589-1597
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• 2021

Due to the low output rate and time delay of vehicle's navigation results, the electro-optical tracking system(EOTS) cannot estimate accurate target positions. If an inertial measurement unit(IMU) is additionally mounted into the EOTS and inertial navigation system(INS) is constructed, the high navigation output rate can be obtained. And the time-delay can be compensated by using the augmented Kalman filter. An accurate initial attitude is required in order to have accurate navigation outputs. In this paper, an attitude determination algorithm is proposed using the augmented Kalman filter in order to compensate measurement delay of the EOTS and have accurate initial attitude. The proposed initial attitude determination algorithm consists of an augmented Kalman filter, an INS, and an integrated Kalman filter. The augmented Kalman filter compensates the time-delay of the vehicle's navigation results and the integrated Kalman filter estimates the navigation error of the INS. In order to evaluate performance of the proposed algorithm, vehicle's navigation outputs and IMU measurements were generated using sensors' model-based measurement generator and initial attitude estimation errors of the proposed algorithm and the conventional algorithm without the augmented Kalman filter were compared for the generated measurements. The evaluation results show that the proposed algorithm has better accuracy.