• Title/Summary/Keyword: dead reckoning

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Dynamic Data Path Prediction use Extend EKF Movement Tracing in Net-VE (Net-VE에서 이동궤적을 이용한 동적데이터 경로예측)

  • Song, Sun-Hee;Oh, Haeng-Soo;Park, Kwang-Chae;Kim, Gwang-Jun;Ra, Sang-Dong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.1 no.2
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    • pp.81-89
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    • 2008
  • Improved EKF suggests variable path prediction to reduce the event traffic caused by the information sharing among multi-users in networked virtual environment. The three dimensional virtual space is maintained consistently by endless status information exchange among dispersed users, and periodic status transmission brings traffic overhead in network. By using the error between the measured movement trace of dynamic information and the EKF predicted, we propose the method applied to predict the mobile packet of dynamic data which is simultaneously changing. And, the simulation results of DIS dead reckoning algorithms and EKF path prediction is compared here. It followed the specific path and while moving, the proposed method which it proposes predicting with DIS dead reckoning algorithm and to compare to the mobile path of the actual object and it got near it predicts the possibility of knowing it was.

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Localization Algorithm in Wireless Sensor Networks using the Acceleration sensor (가속도 센서를 이용한 무선 센서 네트워크하에서의 위치 인식 알고리즘)

  • Hong, Sung-Hwa;Jung, Suk-Yong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.4
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    • pp.1294-1300
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    • 2010
  • In an environment where all nodes move, the sensor node receives anchor node's position information within communication radius and modifies the received anchor node's position information by one's traveled distance and direction in saving in one's memory, where if there at least 3, one's position is determined by performing localization through trilateration. The proposed localization mechanisms have been simulated in the Matlab. In an environment where certain distance is maintained and nodes move towards the same direction, the probability for the sensor node to meet at least 3 anchor nodes with absolute coordinates within 1 hub range is remote. Even if the sensor node has estimated its position with at least 3 beacon information, the angle ${\theta}$ error of accelerator and digital compass will continuously apply by the passage of time in enlarging the error tolerance and its estimated position not being relied. Dead reckoning technology is used as a supplementary position tracking navigation technology in places where GPS doesn't operate, where one's position can be estimated by knowing the distance and direction the node has traveled with acceleration sensor and digital compass. The localization algorithm to be explained is a localization technique that uses Dead reckoning where all nodes are loaded with omnidirectional antenna, and assumes that one's traveling distance and direction can be known with accelerator and digital compass. The simulation results show that our scheme performed better than other mechanisms (e.g. MCL, DV-distance).

Pedestrian Dead Reckoning based Position Estimation Scheme considering Pedestrian's Various Movement Type under Combat Environments (전장환경 하에서 보행자의 다양한 이동유형을 고려한 관성항법 기반의 위치인식 기법)

  • Park, SangHoon;Chae, Jongmok;Lee, Jang-Myung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.10
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    • pp.609-617
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    • 2016
  • In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

Enhanced Indoor Localization Scheme Based on Pedestrian Dead Reckoning and Kalman Filter Fusion with Smartphone Sensors (스마트폰 센서를 이용한 PDR과 칼만필터 기반 개선된 실내 위치 측위 기법)

  • Harun Jamil;Naeem Iqbal;Murad Ali Khan;Syed Shehryar Ali Naqvi;Do-Hyeun Kim
    • Journal of Internet of Things and Convergence
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    • v.10 no.4
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    • pp.101-108
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    • 2024
  • Indoor localization is a critical component for numerous applications, ranging from navigation in large buildings to emergency response. This paper presents an enhanced Pedestrian Dead Reckoning (PDR) scheme using smartphone sensors, integrating neural network-aided motion recognition, Kalman filter-based error correction, and multi-sensor data fusion. The proposed system leverages data from the accelerometer, magnetometer, gyroscope, and barometer to accurately estimate a user's position and orientation. A neural network processes sensor data to classify motion modes and provide real-time adjustments to stride length and heading calculations. The Kalman filter further refines these estimates, reducing cumulative errors and drift. Experimental results, collected using a smartphone across various floors of University, demonstrate the scheme's ability to accurately track vertical movements and changes in heading direction. Comparative analyses show that the proposed CNN-LSTM model outperforms conventional CNN and Deep CNN models in angle prediction. Additionally, the integration of barometric pressure data enables precise floor level detection, enhancing the system's robustness in multi-story environments. Proposed comprehensive approach significantly improves the accuracy and reliability of indoor localization, making it viable for real-world applications.

UTV localization from fusion of Dead -reckoning and LBL System

  • Woon, Jeon-Sang;Jung Sul;Cheol, Won-Moon;Hong Sup
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.64.4-64
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    • 2001
  • Localization is the key role in controlling the Mobile Robot. In this papers, a development of the sensor fusion algorithm for controling UTV(Unmanned Tracked Vehicle) is presented. The multi-sensocial dead-rocking subsystem is established based on the optimal filtering by first fusing heading angle reading from a magnetic compass, a rate-gyro and two encoders mouned on the robot wheels, thereby computing the deat-reckoned location. These data and the position data provoded by LBL system are fused together by means of an extended Kalman filter. This algorithm is proved by simulation studies.

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Development of a CSGPS/DR Integrated System for High-precision Trajectory Estimation for the Purpose of Vehicle Navigation

  • Yoo, Sang-Hoon;Lim, Jeong-Min;Oh, Jeong-Hun;Kim, Ho-Beom;Lee, Kwang-Eog;Sung, Tae-Kyung
    • Journal of Positioning, Navigation, and Timing
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    • v.4 no.3
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    • pp.123-130
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    • 2015
  • In this study, a carrier smoothed global positioning system / dead reckoning (CSGPS/DR) integrated system for high-precision trajectory estimation for the purpose of vehicle navigation was proposed. Existing code-based GPS has a low position accuracy, and carrier-phase differential global positioning system (CPDGPS) has a long waiting time for high-precision positioning and has a problem of high cost due to the establishment of infrastructure. To resolve this, the continuity of a trajectory was guaranteed by integrating CSGPS and DR. The results of the experiment indicated that the trajectory precision of the code-based GPS showed an error performance of more than 30cm, while that of the CSGPS/DR integrated system showed an error performance of less than 10cm. Based on this, it was found that the trajectory precision of the proposed CSGPS/DR integrated system is superior to that of the code-based GPS.

Map Building Using ICP Algorithm based a Robot Position Prediction (로봇 위치 예측에 기반을 둔 ICP 알고리즘을 이용한 지도 작성)

  • Noh, Sung-Woo;Kim, Tae-Gyun;Ko, Nak-Yong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.4
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    • pp.575-582
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    • 2013
  • This paper proposes a map building using the ICP algorithm based robot localization prediction. Proposed method predicts a robot location to dead reckoning, makes a map in the ICP algorithm. Existing method makes a map building and robot position using a sensor value of reference data and current data. In this case, a large interval of the difference of the reference data and the current data is difficult to compensate. The proposed method can map correction through practical experiments.