Results 41 to 50 of about 3,341 (138)

Research on Collaborative Estimation of SOC and SOH for Lithium‐Ion Batteries Based on BS‐SRCKF‐DEKF

Energy Science &Engineering, Volume 14, Issue 3, Page 1416-1430, March 2026.
This paper presents a novel method for jointly estimating the state of charge (SOC) and state of health (SOH) in lithium‐ion battery systems. A second‐order hysteresis RC model and the BS‐SRCKF‐DEKF algorithm are used to improve estimation accuracy. Simulation and experimental results verify the method′s robustness and superior performance.
Meijin Lin, Haokun Lin, Jiehua Tan
wiley   +1 more source

Harmonizing Terrestrial Carbon Cycle Observations Over CONUS NEON Sites: Assessing the Information Contributions of Multiple Data Constraints

Global Change Biology, Volume 32, Issue 2, February 2026.
The Workflow of the State Data Assimilation (SDA). ABSTRACT Accurate inventories of terrestrial carbon pools and fluxes are crucial for understanding ecosystem processes, tracking climate change impacts, and meeting the monitoring, reporting, and verification (MRV) requirements in international treaties and voluntary carbon markets.
Dongchen Zhang, Qianyu Li, Alexis Helgeson, Shawn P. Serbin, Michael Dietze   +4 more
wiley   +1 more source

Robust Gaussian Filtering using a Pseudo Measurement

, 2016
Many sensors, such as range, sonar, radar, GPS and visual devices, produce measurements which are contaminated by outliers. This problem can be addressed by using fat-tailed sensor models, which account for the possibility of outliers. Unfortunately, all
Bohg, Jeannette, Cifuentes, Cristina Garcia, Issac, Jan, Meier, Franziska, Schaal, Stefan, Trimpe, Sebastian, Wüthrich, Manuel   +6 more
core   +1 more source

An Improved Robust Filter Algorithm for Manoeuvering Target Tracking With the Unknown and Time‐Varying Noise

Electronics Letters, Volume 62, Issue 1, January/December 2026.
The unstable radar measurement noise in natural environments degrades tracking performance. This Letter introduces a noise‐adaptive matrix to efficiently compute a corrected fading factor, enabling real‐time compensation for noise variations. Superior performance is verified through comparison with existing methods. ABSTRACT In the natural environment,
Tianhao Liu, Xi Chen, Naichang Yuan
wiley   +1 more source

Unscented Kalman Filter With Enhanced Generalised Cross Correlation Entropy for Robust State Estimation of Power System

IET Energy Systems Integration, Volume 8, Issue 1, January/December 2026.
ABSTRACT To solve the complex scenarios, such as multimodal noise, bad measurement data and sudden load changes, in the power system, the enhanced generalised cross correlation entropy unscented Kalman filter (EnGCCE‐UKF) method is proposed in this paper.
Liangzheng Wu, Taofei Ku, Kaiman Li, Peifeng Chen   +3 more
wiley   +1 more source

Non-linear Kalman filters for calibration in radio interferometry

, 2014
We present a new calibration scheme based on a non-linear version of Kalman filter that aims at estimating the physical terms appearing in the Radio Interferometry Measurement Equation (RIME).
Tasse, Cyril
core   +2 more sources

Time‐Varying Inertia Estimation for Grid‐Connected DFIG‐Based Wind Farms Using Sensitivity‐Guided Clustering and Aggregation

IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.
This paper proposes a time‐varying inertia estimation framework based on sensitivity‐guided clustering and aggregation. It can achieve high‐accuracy inertia estimation with limited measurements, reducing the relative error by nearly 10% compared with existing methods, and exhibit strong robustness to noise and disturbances.
Yulong Li, Wei Yao, Yongxin Xiong, Hongyu Zhou, Shanyang Wei, Wei Huang, Jinyu Wen   +6 more
wiley   +1 more source

Distributed Object Tracking Using a Cluster-Based Kalman Filter in Wireless Camera Networks [PDF]

, 2008
Local data aggregation is an effective means to save sensor node energy and prolong the lifespan of wireless sensor networks. However, when a sensor network is used to track moving objects, the task of local data aggregation in the network presents a new
Medeiros, Henry, Park, Johnny, Kak, Avinash   +2 more
core   +1 more source

Adaptive High Manoeuvring Target Tracking Algorithm Based on CNN‐LSTM Fusion Architecture

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
To solve the problems of model switching lag and tracking accuracy decline in interacting multiple model (IMM) algorithm in complex manoeuvring target tracking, an adaptive interacting multiple model unscented Kalman filter (IMM‐UKF) algorithm based on convolutional neural network and long short‐term memory network (CNN‐LSTM) fusion architecture is ...
Yuhan Cui, Chunbo Xiu, Yuxia Liu, Dawei Liu   +3 more
wiley   +1 more source

Dynamic Error Suppression of Inertial Measurement Unit Based on Improved Unscented Kalman Filter

Transactions of Nanjing University of Aeronautics and Astronautics
In this paper， an algorithm on measurement noise with adaptive strong tracking unscented Kalman filter （ASTUKF） is advanced to improve the precision of pose estimation and the stability for data computation.
LI Na, LI Kun, HE Haiyu, JING Min
doaj   +1 more source