Results 1 to 10 of about 14,518,071 (324)

Adaptive Robust Unscented Kalman Filter via Fading Factor and Maximum Correntropy Criterion [PDF]

Sensors, 2018
In most practical applications, the tracking process needs to update the data constantly. However, outliers may occur frequently in the process of sensors’ data collection and sending, which affects the performance of the system state estimate.
Zhihong Deng, Lijian Yin, Baoyu Huo, Yuanqing Xia   +3 more
doaj   +5 more sources

Integrated Navigation Algorithm Based on Multiple Fading Factors Kalman Filter

Sensors, 2022
An integrated navigation algorithm based on a multiple fading factors Kalman filter (MFKF) is proposed to solve the problems that the Kalman filtering (KF) algorithm easily brings about diffusion when the model becomes a mismatched or noisy, and the MFKF
Bo Sun, Zhenwei Zhang, Shicai Liu, Xiaobing Yan, Chengxu Yang   +4 more
doaj   +4 more sources

Adaptive Fading Factor Unscented Kalman Filter with Application to Target Tracking [PDF]

Aerospace Systems, 2020
AbstractOne purpose of target tracking is to estimate the states of targets, and unscented Kalman filter is one of the effective algorithms for estimating in the nonlinear tracking problem. Considering the characteristics of complex maneuverability, it is easy to reduce the tracking accuracy and cause divergence due to the mismatch between the system ...
Peng Gu, Zhongliang Jing, Liangbin Wu
semanticscholar   +4 more sources

Estimation of Rice Factor Ratio for Doubly Selective Fading Channels [PDF]

IEEE Access, 2020
In wireless communication systems, Rice factor ratio (RFR) defined as K/(1 + K) is a key parameter not only to evaluate the quality of communication channel since it can reveal the severity of the small-scale fading, but also to be employed as a priori ...
Junfeng Wang, Yue Cui, Hao Jiang, Gaofeng Pan, Haixin Sun, Jianghui Li, Hamada Esmaiel   +6 more
doaj   +5 more sources

Multi-Fading Factor and Updated Monitoring Strategy Adaptive Kalman Filter-Based Variational Bayesian. [PDF]

Sensors (Basel), 2020
Aiming at the problem that the performance of adaptive Kalman filter estimation will be affected when the statistical characteristics of the process and measurement of the noise matrices are inaccurate and time-varying in the linear Gaussian state-space ...
Shan C, Zhou W, Yang Y, Jiang Z.
europepmc   +2 more sources

Adaptive Markov IMM Based Multiple Fading Factors Strong Tracking CKF for Maneuvering Hypersonic-Target Tracking

Applied Sciences, 2022
Hypersonic targets have complex motion states and high maneuverability. The traditional interactive multi-model (IMM) has low tracking accuracy and a slow convergence speed.
Yalun Luo, Zhaoming Li, Yurong Liao, Haining Wang, Shuyan Ni   +4 more
doaj   +2 more sources

Analysis of the Fading Factor of an Adaptive Fading Kalman Filter under Ramp GNSS Fault Conditions

TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, 2018
A GNSS fault detection method using an adaptive fading Kalman fi lter is proposed for detecting GNSS faults such as step- and ramp-type bias error in pseudorange measurements. The fading factor of the fi lter is used as a detection parameter.
Sun Young Kim, Chang Ho Kang, Chan Gook Park   +2 more
openaire   +3 more sources

A Strong Tracking SLAM Algorithm Based on the Suboptimal Fading Factor [PDF]

Journal of Sensors, 2018
This paper proposes an innovative simultaneous localization and mapping (SLAM) algorithm which combines a strong tracking filter (STF), an unscented Kalman filter (UKF), and a particle filter (PF) to deal with the low accuracy of unscented FastSLAM (UFastSLAM).
Yunpei Liang, Jiahui Dai, Kequan Wang, Xiaobo Li, Pengcheng Xu   +4 more
openaire   +2 more sources

An Improved Strong Tracking UKF Based on Fading Factor

International Journal of Hybrid Information Technology, 2014
STUKF (Strong tracking UKF) algorithm uses the time-varying fading factor to fade the past data and reduce the impact on current filter value, thus achieves the goal of adjusting the filter gain matrix in real time. But STUKF algorithm needs three UT for each filtering, and compared with the UKF filter, calculating amount of three UT increases ...
Jian Feng, Xiao-dong Su, Yu-ru Zhang, Hai-tao Jiang, Jun-ling Li   +4 more
openaire   +2 more sources

An Improved Fading Factor-Based Adaptive Robust Filtering Algorithm for SINS/GNSS Integration with Dynamic Disturbance Suppression

Remote Sensing
Aiming at the problem of nonlinear observation model mismatch and insufficient anti-interference ability of SINS/GNSS integrated navigation system in complex dynamic environment, this paper proposes an adaptive robust filtering algorithm with improved ...
Zhaohao Chen, Yixu Liu, Shangguo Liu, Shengli Wang, Lei Yang   +4 more
doaj   +2 more sources