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Kenan Liu, Wuyun Zhao, Bugong Sun, Pute Wu, Delan Zhu and Peng Zhang
Autonomous navigation for agricultural machinery has broad and promising development prospects. Kalman filter technology, which can improve positioning accuracy, is widely used in navigation systems in different fields. However, there has not been much r...
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Bing Han, Zaiyu Duan, Zhouhua Peng and Yuhang Chen
A fuzzy control improvement method is proposed with an integral line-of-sight (ILOS) guidance principle to meet the needs of autonomous navigation and high-precision control of ship trajectories. Firstly, a three-degree-of-freedom ship motion model was e...
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Zhaoming Li, Xinyan Yang, Lei Li and Hang Chen
In order to increase a nonlinear system?s state estimate precision, an iterated orthogonal simplex cubature Kalman filter (IOSCKF) is presented in this study for target tracking. The Gaussian-weighted integral is decomposed into a spherical integral and ...
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Taehoon Lee, Byungjin Lee and Sangkyung Sung
This study proposes an enhanced integration algorithm that combines the magnetic field-based positioning system (MPS?Magnetic Pose Estimation System) with an inertial system with the advantage of an invariant filter structure. Specifically, to mitigate t...
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Haobin Wen, Long Zhang and Jyoti K. Sinha
On top of the condition-based maintenance (CBM) practice for rotating machinery, the robust estimation of remaining useful life (RUL) for rolling-element bearings (REB) is of particular interest. The failure of a single bearing often results in secondary...
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Marco Sabatini and Giovanni B. Palmerini
This paper investigates the performance of the forthcoming lunar navigation satellite systems for estimating not only the position of an onboard receiver in a lunar inertial reference frame but also, and with a consistent accuracy, the relative position ...
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Yoga Sasmita, Heri Kuswanto and Dedy Dwi Prastyo
Standard time-series modeling requires the stability of model parameters over time. The instability of model parameters is often caused by structural breaks, leading to the formation of nonlinear models. A state-dependent model (SDM) is a more general an...
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Rohit Mittal, Geeta Rani, Vibhakar Pathak, Sonam Chhikara, Vijaypal Singh Dhaka, Eugenio Vocaturo and Ester Zumpano
The automation industry faces the challenge of avoiding interference with obstacles, estimating the next move of a robot, and optimizing its path in various environments. Although researchers have predicted the next move of a robot in linear and non-line...
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Rongjun Mu, Yanfeng Chu, Hao Zhang and Hao Liang
This study is focused on addressing the problem of delayed measurements and contaminated Gaussian distributions in navigation systems, which both have a tremendous deleterious effect on the performance of the traditional Kalman filtering. We propose a no...
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Assefinew Wondosen, Yisak Debele, Seung-Ki Kim, Ha-Young Shi, Bedada Endale and Beom-Soo Kang
In various applications, the extended Kalman filter (EKF) has been vital in estimating a vehicle?s translational and angular motion in 3-dimensional (3D) space. It is also essential for the fusion of data from multiple sensors. However, for the EKF to pe...
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