Results 241 to 250 of about 8,926,578 (308)

Carrier Tracking Estimation Analysis by Using the Extended Strong Tracking Filtering

IEEE Transactions on Industrial Electronics, 2017
When the extended strong tracking filter (ESTF) is used to improve the carrier tracking estimation instead of the extended Kalman filter (EKF), it is found to be difficult to effectively and consistently evaluate superiority of the ESTF than the EKF. The primary cause is that the basic properties of the traditional Kalman filter are broken due to the ...
Quanbo Ge, Teng Shao, Shaodong Chen, Chenglin Wen   +3 more
semanticscholar   +4 more sources

The Strong Tracking Innovation Filter

IEEE Transactions on Aerospace and Electronic Systems, 2022
Sliding innovation filter (SIF) has recently been introduced as a robust strategy for estimation of linear systems. The SIF has been extended to nonlinear systems via analytical linearization.
Maryam Kiani, Reza Ahmadvand
openaire   +2 more sources

Hybrid Nonsingleton Fuzzy Strong Tracking Kalman Filtering for High Precision Photoelectric Tracking System

IEEE Transactions on Industrial Informatics, 2023
This article presents a hybrid nonsingleton fuzzy strong tracking Kalman filter (H-NFSTKF) for the high-precision photoelectric tracking system (PTS) to improve state estimation performance in the complex case of measurement noise change and velocity ...
Tao Zhao, Wei Tong, Yao Mao
semanticscholar   +3 more sources

Symmetric-Strong-Tracking-Extended-Kalman-Filter-Based Sensorless Control of Induction Motor Drives for Modeling Error Reduction

IEEE Transactions on Industrial Informatics, 2019
This paper proposes a real-time speed identification method by using a symmetric strong tracking extended Kalman filter (SSTEKF) for induction motor sensorless drive.
Zhonggang Yin, Guoyin Li, Yanqing Zhang, Jing Liu   +3 more
semanticscholar   +3 more sources

Strong Tracking Tobit Kalman Filter with Model Uncertainties

International Journal of Control, Automation and Systems, 2019
The Tobit Kalman filter (TKF) is a good choice for applications of discrete time-varying systems with censored measurements. The traditional TKF is usually designed under the assumption of exactly knowing system state and measurement functions, which can not guarantee the good performance and is even unsuitable for system with model mismatch. To ensure
Zhan-long Du, Xiao-min Li
openaire   +2 more sources

Strong Tracking UKF-Based Hybrid Algorithm and Its Application to Initial Alignment of Rotating SINS With Large Misalignment Angles

IEEE transactions on industrial electronics (1982. Print), 2023
In this article, the fast and precise initial alignment of the low-cost rotary strapdown inertial navigation system under mooring conditions is investigated.
Jianguo Liu, Xiyuan Chen, Junwei Wang
semanticscholar   +1 more source

Vehicle Sideslip Angle Estimation Based on Strong Tracking SCKF Considering Road Inclinations

IEEE Transactions on Vehicular Technology, 2023
As one of the most significant states to represent lateral stability, vehicle sideslip angle holds significant importance in vehicle dynamic control systems.
Yicai Liu, Changyao Huang, Daolin Zhou, Xiang-yu Wang, Liang Li   +4 more
semanticscholar   +1 more source

Modified Strong Tracking Slide Window Variational Adaptive Kalman Filter With Unknown Noise Statistics

IEEE Transactions on Industrial Informatics, 2023
The filter performance will be degraded in the measurements with time-varying and unknown noise statistics. To combat the above challenges, a modified strong tracking slide window variational adaptive Kalman filter algorithm is proposed in this article ...
Shuanghu Qiao, Yunsheng Fan, Guofeng Wang, Dongdong Mu, Zhiping He   +4 more
semanticscholar   +1 more source