Results 61 to 70 of about 1,423 (188)

A Novel Case of Practical Exponential Observer Using Extended Kalman Filter [PDF]

, 2018
This technical note presents a case of practical exponential observer using extended Kalman filter (EKF) independent of certain restrictions, such as online check and estimation error of initial state.
Deng, Z, Ji, D, Li, S, Ma, D, Pan, H, Sharma, S, Song, W, Wang, T, Wang, Z, Yang, X, Zhu, S   +10 more
core   +2 more sources

A Tightly Coupled Fusion Positioning Method Based on Particle Filtering With Effective Particle Neighbourhood Attraction Optimisation

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

Robust Filtering and Smoothing with Gaussian Processes

, 2012
We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models.
,, Deisenroth, MP, Hanebeck, UD, Huber, MF, Rasmussen, CE, Turner, RD   +5 more
core   +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, Keting Huang, Gang Wang, Zhuowei Liang, Yun Zhou, Desheng Zheng, Yaoxin Duan, Wenling Li   +7 more
wiley   +1 more source

A New Approach to Linear/Nonlinear Distributed Fusion Estimation Problem

, 2018
Disturbance noises are always bounded in a practical system, while fusion estimation is to best utilize multiple sensor data containing noises for the purpose of estimating a quantity--a parameter or process.
Chen, Bo, Ho, Daniel W. C., Hu, Guoqiang, Yu, Li   +3 more
core   +1 more source

Using a single band GNSS receiver to improve relative positioning in autonomous cars [PDF]

, 2016
We show how the combination of a single band global navigation satellite systems (GNSS) receiver, standard automotive level inertial measurement unit (IMU), and wheel speed sensors, can be used for relative positioning with accuracy on a decimeter scale.
Hammarstrand, Lars, Stenborg, Erik
core   +1 more source

Student’s t‐Kernel‐Based Graph Signals Maximum Correntropy Unscented Kalman Filter Under Hybrid Cyberattacks

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
wiley   +1 more source

Intelligent Vehicle Sideslip Angle Observation Strategy Based on Steady‐State Model and SCKF With Nonlinear Compensation

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, Qiangqiang Yao, Yiheng Shi, Abdullah A. Kendoush   +3 more
wiley   +1 more source

Multiple-sensor Fusion Tracking Based on Square-root Cubature Kalman Filtering

Journal of Networks, 2014
Nonlinear state estimation and fusion tracking are always hot research topics for information processing. Compared to linear fusion tracking, nonlinear fusion tracking takes many new problems and challenges. Especially, the performances of fusion tracking, based on different nonlinear filters, are obviously different.
openaire   +1 more source

Research on Landmarks of SLAM Based on Square Root Cubature Kalman Filter

Journal of Physics: Conference Series, 2018
Under the large noise, the system's observability is weak, which leads to the instability of the filtering algorithm and the slow convergence speed. The algorithm of simultaneous localization and mapping based on the square-root Cubature Kalman filter (SRCKF) with Spherical Simplex(SS) was proposed in this paper.
Dandan Wang, Kaituo Tan, Zhengbin Li, Gannan Yuan   +3 more
openaire   +1 more source