Results 31 to 40 of about 1,983 (163)
Localization of passive UHF RFID Labels with Kalman Filter [PDF]
Advances in Radio Science, 2012 Localization via Radio Frequency Identification (RFID) is frequently used in different applications nowadays. It has the advantage that next to its ostensible purpose of identifying objects via their unique IDs it can simultaneously be used for the ...
T. Nick, J. Götze
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Passive Radar Tracking in Clutter Using Range and Range-Rate Measurements
Sensors, 2023 Passive bistatic radar research is essential for accurate 3D target tracking, especially in the presence of missing or low-quality bearing information. Traditional extended Kalman filter (EKF) methods often introduce bias in such scenarios.
Asma Asif +2 more
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IEEE Access, 2020 In this paper, an improved distributed unscented Kalman particle filter (DUKPF) is proposed for the problem of tracking a single moving acoustic source in noisy and reverberant environments with distributed microphone networks.
Qiaoling Zhang +3 more
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Fractal and Fractional, 2022 The accuracy of the state-of-charge (SOC) estimation of lithium batteries affects the battery life, driving performance, and the safety of electric vehicles.
Liping Chen +5 more
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UKF‐MOT: An unscented Kalman filter‐based 3D multi‐object tracker
CAAI Transactions on Intelligence TechnologyAbstract Multi‐object tracking in autonomous driving is a non‐linear problem. To better address the tracking problem, this paper leveraged an unscented Kalman filter to predict the object's state. In the association stage, the Mahalanobis distance was employed as an affinity metric, and a Non‐minimum Suppression method was designed ...
Meng Liu 0013 +2 more
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Global Energy InterconnectionAccurate estimation of the State of Charge (SOC), State of Health (SOH), and Terminal Resistance (TR) is crucial for the effective operation of Battery Management Systems (BMS) in lithium-ion batteries.
Ranagani Madhavi +1 more
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International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT This paper proposes a Machine Learning (ML)‐enabled estimator‐controller design framework, in which a parameterized Model Predictive Controller (MPC) and a parameterized Moving Horizon Estimator (MHE) are jointly refined using Bayesian Optimization (BO).
Hossein Nejatbakhsh Esfahani +1 more
wiley +1 more source
Accuracy Evaluation of Marginalized Unscented Kalman Filter
Space: Science & Technology, 2023 Compared with a conventional unscented Kalman filter (UKF), the recently proposed marginalized unscented Kalman filter (MUKF) uses a partially sampling strategy to achieve similar filter accuracy with fewer sigma points, demonstrating its powerful ...
Han Yan, Hanyu Liu, Xiucong Sun, Ming Xu
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Proceedings of the 21st International Conference on Informatics in Control, Automation and RoboticsAccepted in Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-717-7, SciTePress, pages 714-723.
Shuhao Bian +3 more
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Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning
Journal of Field Robotics, Volume 43, Issue 6, Page 3617-3632, September 2026.ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi +3 more
wiley +1 more source