Results 51 to 60 of about 792 (163)
IEEE Access, 2021 As a core technology of cooperative navigation, relative position sensing is crucial for vehicle intelligent driving. It plays a key role in the cooperative positioning algorithm of vehicle ad hoc networks (VANETs).
Wei Sun, Jingzhou Liu
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IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.To address the limitations of existing wireless and inertial navigation systems, this paper proposes a high‐precision integrated positioning scheme based on particle filtering. The method introduces a high‐weight particle neighbourhood attraction mechanism to solve the common issue of particle degeneracy.
Yanbiao Gao, Zhongliang Deng
wiley +1 more source
BP Neural Network–Based Kalman Filtering Method Under Multiple Cyberattacks
IET Signal Processing, Volume 2026, Issue 1, 2026.This paper proposes a Kalman‐gain‐driven neural Kalman filtering (KF) defense framework, termed KFDBP, for secure state estimation in cyber–physical systems (CPSs) under denial‐of‐service (DoS), spoofing, and replay attacks. Unlike end‐to‐end neural filtering approaches such as KalmanNet that directly learn state estimators or implicitly approximate ...
Zijing Li +7 more
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IET Signal Processing, Volume 2026, Issue 1, 2026.The implementation of Kalman filter (KF) in tracking high‐dimensional, strongly correlated graph structured data is often complex and unstable. Meanwhile, in practical applications, the system may be subject to interference from non‐Gaussian noise and various cyberattacks.
Bingyu Yin, Xinmin Song, Wenling Li
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Comparisons on Kalman-Filter-Based Dynamic State Estimation Algorithms of Power Systems
IEEE Access, 2020 The Kalman-filter-based algorithms as the mainstream algorithms of dynamic state estimation of power systems have been extensively used to provide accurate data for power system applications. However, few comparisons are made to show their advantages and
Hui Liu +4 more
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Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.Bearings‐only tracking (BOT) in sonar’s passive mode presents significant nonlinearity challenges, addressed here through a measure of nonlinearity (MoN) based on the filter’s covariance matrix. This study computes MoN to evaluate filter performance and enhance target motion estimation precision.
Kausar Jahan +7 more
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International Transactions on Electrical Energy Systems, Volume 2026, Issue 1, 2026.Forecasts are predictions of what is likely to happen in the future and are developed so that judgment and experience of administrators and managers may be supplemented by scientifically developed information to enhance decision‐making. This study presents a systematic literature review on recent applications (2018–2024) of exponential smoothing ...
Nhlanhla Mbuli, Yukun Bao
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Adaptive Robust Cubature Kalman Filter for Power System Dynamic State Estimation Against Outliers
IEEE Access, 2019 This paper develops an adaptive robust cubature Kalman filter (ARCKF) that is able to mitigate the adverse effects of the innovation and observation outliers while filtering out the system and measurement noises.
Yi Wang +4 more
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Adaptively Robust Square-Root Cubature Kalman Filter Based on Amending
IEEE Access, 2021 To solve the problem of decreased filtering accuracy and even filter divergence for the case that the model errors and measurement outliers exist simultaneously, an adaptively robust square-root cubature Kalman filter (SRCKF) based on amending is ...
Chunhui Li +3 more
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Journal of Engineering, Volume 2026, Issue 1, 2026.Vehicle sideslip angle is one of the irreplaceable variable indicators for evaluating vehicle stability. However, it is difficult to directly measure vehicle sideslip angle with onboard sensors. In order to obtain precise vehicle sideslip angle using onboard sensors, a novel observation strategy based on fusion of steady‐state model method and square ...
Zhendong Zhu +3 more
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