• 제목/요약/키워드: Adaptive Navigation System

검색결과 130건 처리시간 0.018초

Analysis on Design Factors of the Optimal Adaptive Beamforming Algorithm for GNSS Anti-Jamming Receivers

  • Jang, Dong-Hoon;Kim, Hyeong-Pil;Won, Jong-Hoon
    • Journal of Positioning, Navigation, and Timing
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    • 제8권1호
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    • pp.19-29
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    • 2019
  • This paper analyzes the design factors for GNSS anti-jamming receiver system in which the adaptive beamforming algorithm is applied in GNSS receiver system. The design analysis factors used in this paper are divided into three: antenna, beamforming algorithm, and operation environment. This paper analyzes the above three factors and presents numerical simulation results on antenna and beamforming algorithm.

적응 이동 구간 칼만 필터를 이용한 무인 잠수정의 항법 시스템에 관한 연구 (A Study on the Underwater Navigation System with Adaptive Receding Horizon Kalman Filter)

  • 조경남;서동철;최항순
    • 대한조선학회논문집
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    • 제45권3호
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    • pp.269-279
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    • 2008
  • In this paper, an underwater navigation system with adaptive receding horizon Kalman filter (ARHKF) is studied. It is well known that incorrect statistical information and temporal disturbance invoke errors of any navigation systems with Kalman filter, which makes the autonomous navigation difficult in real underwater environment. In this context, two kinds of problems are herein considered. The first one is the development of an algorithm, which estimates the noise covariance of a linear discrete time-varying stochastic system. The second one is the implementation of ARHKF to underwater navigation systems. The performance of the derived estimation algorithm of noise covariance and the ARHKF are verified by simulation and experiment in the towing tank of Seoul National University.

Adaptive Beamformer Using Signal Location Information for Satellite

  • Kim, Se-Yen;Hwang, Suk-seung
    • Journal of Positioning, Navigation, and Timing
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    • 제9권4호
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    • pp.379-385
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    • 2020
  • The satellite employs an adaptive beamformer to efficiently detect various signals and to suppress multiple interference signals, simultaneously. Although the adaptive beamforming satellite system needs Angle-of-Arrival (AOA) information of the desired signal, it is difficult to estimate the signal AOAs on the satellite environment. However, the AOA estimation on the ground control tower is more efficient and accurate comparing to the satellite environment. In this paper, we propose an adaptive beamforming satellite system based on the signal location information on the ground, consisting on an angle estimator, an adaptive beamformer, and signal processing & D/B unit. The ground control tower estimates the accurate location of the signal source, and it sends the estimated coordinates of the desired signal to the satellite. The angle estimator mounted on the satellite calculates the desired signal AOA, based on the signal location information transmitted from the ground control center. The satellite beamformer detects the desired signal and suppresses unwanted signals based on the signal AOA calculated by the angle estimator. We provide computer simulation results to present the performance of the proposed satellite adaptive beamforming system based on the signal location information.

자동항해를 지원하는 적응형 웹 서핑 시스템 (An Adaptive Web Surfing System for Supporting Autonomous Navigation)

  • 국형준
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제31권4호
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    • pp.439-446
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    • 2004
  • 사용자 적응형 웹 서핑 시스템 설계를 위해 전체 시스템을 사용자 데이타 수집, 데이타 처리를 통한 사용자 프로파일 구축 및 개선, 그리고 사용자 프로파일의 적용을 통한 적응 등 세 단계로 나누어 접근할 수 있다. 본 연구가 설계한 세 부문의 에이전트들은 이들 각 단계에서 작업하며 상호 유기적인 협동을 통해 적응형 웹 서핑을 지원한다. 이들은 각각 대화식 인터페이스 에이전트(Interactive Interface Agent), 사용자 프로파일 에이전트(User Profile Agent), 그리고 자동항해 에이전트(Autonomous Navigation Agent)이다. 대화식 인터페이스 에이전트는 사용자 인터페이스를 제공하며 이를 통해 데이타를 수집하고 기계적 항해 지원을 수행한다. 사용자 프로파일 에이전트는 수집된 사용자 데이타를 처리하여 사용자 브라우징의 실시간에 사용자 프로파일을 동적으로 구축하고 갱신한다. 자동항해 지원 에이전트는 사용자 프로파일에 기초하여 사용자 관심과 가까운 웹 문서를 자동으로 선별하여 추천하는 자동 항해 모드를 제공한다. 본 연구가 제시하는 접근과 설계 방식은 향후 확장과 보완을 통해 실용 가능한 수준의 사용자 적응형 웹 서핑 시스템 구축에 활용될 수 있다.

GPS/GLONASS 보정 관성항법시스템의 적응필터 설계 (Design of an Adaptive Filter for GPS/GLONASS Aided Inertial Navigation System)

  • 박흥원;제창해;정태호;박찬빈
    • 한국군사과학기술학회지
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    • 제1권1호
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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.

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Design and Application of an Adaptive Neural Network to Dynamic Positioning Control of Ship

  • Nguyen, Phung-Hung;Jung, Yun-Chul
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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    • pp.285-290
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    • 2006
  • This paper presents an adaptive neural network based controller and its application to Dynamic Positioning (DP) control system of ship. The proposed neural network based controller is developed for station-keeping and low-speed maneuvering control of ship. At first, the DP system configuration is described. And then, to validate the proposed DP system, computer simulations of station-keeping and low-speed maneuvering performance of a multi-purpose supply ship are presented under the influence of measurement noise, external disturbances such as sea current, wave, and wind. The simulations have shown the feasibility of the DP system in various maneuvering situations.

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Automatic Berthing Control of Ship Using Adaptive Neural Networks

  • Nguyen, Phung-Hung;Jung, Yun-Chul
    • 한국항해항만학회지
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    • 제31권7호
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    • pp.563-568
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    • 2007
  • In this paper, an adaptive neural network controller and its application to automatic berthing control of ship is presented. The neural network controller is trained online using adaptive interaction technique without any teaching data and off-line training phase. Firstly, the neural networks used to control rudder and propeller during automatic berthing process are presented. Secondly, computer simulations of automatic ship berthing are carried out in Pusan bay to verify the proposed controller under the influence of wind disturbance and measurement noise. The results of simulation show good performance of the developed berthing control system.

Neural Network Based Rudder-Roll Damping Control System for Ship

  • Nguyen, Phung-Hung;Jung, Yun-Chul
    • 한국항해항만학회지
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    • 제31권4호
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    • pp.289-293
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    • 2007
  • In this paper, new application of adaptive neural network to design a ship's Rudder-Roll Damping(RRD) control system is presented Firstly, the ANNAI neural network controller is presented. Secondly, new RRD control system using this neural network approach is developed. It uses two neural network controllers for heading control and roll damping control separately. Finally, Computer simulation of this RRD control system is carried out to compare with a linear quadratic optimal RRD control system; discussions and conclusions are provided. The simulation results show the feasibility of using ANNAI controller for RRD. Also, the necessity of mathematical ship model in designing RRD control system is removed by using NN control technique.

Improvement of a Low Cost MEMS-based GPS/INS, Micro-GAIA

  • Fujiwara, Takeshi;Tsujii, Toshiaki;Tomita, Hiroshi;Harigae, Masatoshi
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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    • pp.265-270
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    • 2006
  • Recently, inertial sensors like gyros and accelerometers have been quite miniaturized by Micro Electro-Mechanical Systems (MEMS) technology. JAXA is developing a MEM-based GPS/INS hybrid navigation system named Micro-GAIA. The navigation performance of Micro-GAIA was evaluated through off-line analysis by using flight test data. The estimation errors of the roll, pitch, and azimuth were $0.03^{\circ}$, $0.05^{\circ}$, $0.05^{\circ}$ $(1{\sigma})$, respectively. he horizontal position errors after 60-second GPS outages were reduced to 25 m CEP. The attitude errors and position errors are nearly half of ones reported previously[2]. Furthermore, using the adaptive Kalman filters, the robustness against the uncertainty of the measurement noise was improved. Comparing the innovation-based and residual-based adaptive Kalman filters, it was confirmed that the latter is robuster than the former.

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Improved Adaptive Neural Network Autopilot for Track-keeping Control of Ships: Design and Simulation

  • Nguyen, Phung-Hung;Jung, Yun-Chul
    • 한국항해항만학회지
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    • 제30권4호
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    • pp.259-265
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    • 2006
  • This paper presents an improved adaptive neural network autopilot based on our previous study for track-keeping control of ships. The proposed optimal neural network controller can automatically adapt its learning rate and number of iterations. Firstly, the track-keeping control system of ships is described For the track-keeping control task, a way-point based guidance system is applied To improve the track-keeping ability, the off-track distance caused by external disturbances is considered in learning process of neural network controller. The simulations of track-keeping performance are presented under the influence of sea current and wind as well as measurement noise. The toolbox for track-keeping simulation on Mercator chart is also introduced.