Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
As the core method of cooperative navigation, relative positioning plays a key role in realizing intelligent vehicle driving and vehicle self-assembling network collaboration algorithms. However, when the contamination rate of measurement noise is high, the performance of filtering will be seriously affected. To better address the filtering performance degradation problem due to noise contamination, this paper proposes a vehicular cooperative localization method based on the Maximum Correentropy Robust Square-root Cubature Kalman Filter (MCSCKF). The algorithm not only retains the advantages of Square-root Cubature Kalman Filter (SCKF) but also has strong robustness to non-Gaussian noise. The experimental results of tightly integrated vehicular cooperative navigation show that compared with the Extended Kalman Filter (EKF) and Cubature Kalman Filter (CKF), the localization accuracy of MCSCKF is improved by 35.08% and 31.83%, respectively, which verified the effectiveness in improving the accuracy and robustness of the relative position estimation.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10752878 | PMC |
| http://dx.doi.org/10.1038/s41598-023-50377-w | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Flexible and Stable Cycle-by-Cycle Phase-Locked Deep Brain Stimulation System Targeting Brain Oscillations in the Management of Movement Disorders.
Brain Stimul
September 2025
Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom. Electronic address:
Background: Precisely timed brain stimulation, such as phase-locked deep brain stimulation (PLDBS), offers a promising approach to modulating dysfunctional neural networks by enhancing or suppressing specific oscillations. However, its clinical application has been hindered by the lack of user-friendly systems and the challenge of real-time phase estimation amid stimulation artifacts.
Material And Method: In this work, we developed a clinically translatable PLDBS framework that enables real-time, cycle-by-cycle stimulation using standard amplifiers and a computer-in-the-loop system.
A Variational Theorem-Based Uncertain Initialization SOC Estimation Technique in Li-Ion Battery Applications.
ACS Omega
September 2025
College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing 211169, Jiangsu, China.
State of charge (SOC) is extremely critical to the reliability of lithium-ion (Li-ion) battery utilization. In this study, a novel problem in which internal differences occurred in the battery package, causing uncertain SOC initialization of each battery unit, is solved by combining the variational theorem and the extended Kalman filter (EKF) algorithm. First, the importance of the initialized SOC setting of each unit in the battery package is proposed by determining the theoretical relationship between the initialization value and the current estimation result.
View Article and Find Full Text PDFHardware-enabled low latency rhythmic brain state tracking for brain stimulation applications.
Neuroimage
September 2025
Center for Bioelectric Interfaces, Higher School of Economics, Moscow, Russia; LLC "Life Improvement by Future Technologies Center", Moscow, Russia; AIRI, Artificial Intelligence Research Institute, Moscow, Russia. Electronic address:
Objective: Upcoming neuroscientific research will require bidirectional and context dependent interaction with nervous tissue. To facilitate the future neuroscientific discoveries we have created HarPULL, a genuinely real-time system for tracking oscillatory brain state.
Approach: The HarPULL technology ensures reliable, accurate and affordable real-time phase and amplitude tracking based on the state-space estimation framework operationalized by Kalman filtering.
Denoising and reconstruction of nonlinear dynamics using truncated reservoir computing.
Chaos
September 2025
Centre for Audio, Acoustics and Vibration (CAAV), School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia.
Measurements acquired from distributed physical systems are often sparse and noisy. Therefore, signal processing and system identification tools are required to mitigate noise effects and reconstruct unobserved dynamics from limited sensor data. However, this process is particularly challenging because the fundamental equations governing the dynamics are largely unavailable in practice.
View Article and Find Full Text PDFComprehensive outdoor UWB dataset: Static and dynamic measurements in LOS/NLOS environments.
Sci Data
September 2025
Department of Mechanical Convergence Engineering, Hanyang University, 222 Wangsimni-ri, Seongdong-gu, Seoul, 04763, Republic of Korea.
This study provides a comprehensive outdoor ultra-wideband (UWB) dataset to examine the multipath effects in line-of-sight and non-line-of-sight (NLOS) environments for real-time localization. Specifically, the dataset comprises static and dynamic datasets designed to capture discrete multipaths affected by antenna height, obstructions, and time-varying environments. A static dataset varies the antenna height and distance to analyze the multipath interference on the received signal strength and ranging error with a UWB pair and walls to replicate NLOS environments.
View Article and Find Full Text PDF