An improved transformed unscented FastSLAM with adaptive genetic resampling
Fast simultaneous localization and mapping (FastSLAM) is a well-known study for robot
navigation. To enhance the performance of FastSLAM, an improved importance sampling is …
navigation. To enhance the performance of FastSLAM, an improved importance sampling is …
An improved algorithm based on particle filter for 3D UAV target tracking
W Xie, L Wang, B Bai, B Peng… - ICC 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
The widespread application of unmanned aerial vehicles (UAVs) urgently requires an
effective tracking algorithm as technical support. Particle filter has been widely applied in …
effective tracking algorithm as technical support. Particle filter has been widely applied in …
Error-ellipse-resampling-based particle filtering algorithm for target tracking
In this paper, an error-ellipse-resampling-based particle filter (EER-PF) algorithm is
proposed for target tracking in wireless sensor networks. In order to improve the …
proposed for target tracking in wireless sensor networks. In order to improve the …
Probability hypothesis density filter for parameter estimation of multiple hazardous sources
This study introduces an advanced methodology for estimating the source term of multiple,
variable-number biochemical hazard releases, where the exact count of sources is not …
variable-number biochemical hazard releases, where the exact count of sources is not …
A novel adaptive resampling for sequential Bayesian filtering to improve frequency estimation of time-varying signals
N Aunsri, K Pipatphol, B Thikeaw, S Robroo… - Heliyon, 2021 - cell.com
This paper presents a new algorithm for adaptive resampling, called percentile-based
resampling (PBR) in a sequential Bayesian filtering, ie, particle filter (PF) in particular, to …
resampling (PBR) in a sequential Bayesian filtering, ie, particle filter (PF) in particular, to …
A Distribution Network State Estimation Method With Non-Gaussian Noise Based on Parallel Particle Filter
The particle filter (PF) algorithm is a powerful method for tackling non-Gaussian noise
interference in distribution network state measurement. However, this algorithm suffers from …
interference in distribution network state measurement. However, this algorithm suffers from …
A Key Conditional Quotient Filter for Nonlinear, non-Gaussian and non-Markovian System
Y Zhao, F Wu, L Zhu - arXiv preprint arXiv:2501.05162, 2025 - arxiv.org
This paper proposes a novel and efficient key conditional quotient filter (KCQF) for the
estimation of state in the nonlinear system which can be either Gaussian or non-Gaussian …
estimation of state in the nonlinear system which can be either Gaussian or non-Gaussian …
Adaptive particle filter for state estimation with application to non‐linear system
F Zhao, R Cai - IET Signal Processing, 2022 - Wiley Online Library
Particle filtering (PF) has certain application value, but the disadvantage is that there is a
phenomenon of particle degradation. In order to reduce the impact of this problem, this …
phenomenon of particle degradation. In order to reduce the impact of this problem, this …
Study on the Tangent Calculation Method of Frequency-domain Dielectric Loss Angle Based on Improved Kalman Filtering Algorithm
Z Huang, R Zhuo, M Fu, Y Yu, Y Luo… - … Materials and Power …, 2021 - ieeexplore.ieee.org
Frequency-domain dielectric spectroscopy realizes the dielectric loss detection within the
range of 1 mHz-10 kHz, which can detect the insulation condition of electrical equipment …
range of 1 mHz-10 kHz, which can detect the insulation condition of electrical equipment …
An improved particle filter for UAV passive tracking based on RSS
J Gao, H Zhao - 2020 IEEE 92nd Vehicular Technology …, 2020 - ieeexplore.ieee.org
The increasing demand for unmanned aerial vehicle (UAV) supervision urgently requires
accurate tracking algorithms as technical support. Particle filter (PF) is widely used for …
accurate tracking algorithms as technical support. Particle filter (PF) is widely used for …