Non-iterative Cauchy kernel-based maximum correntropy cubature Kalman filter for non-Gaussian systems
Aastha Dak
Rahul Radhakrishnan
Department of Electrical Engineering,Sardar Vallabhbhai National Institute of Technology,Surat,Gujarat 395007,India
摘要：This article addresses the nonlinear state estimation problem where the conventional Gaussian assumption is completely relaxed.Here,the uncertainties in process and measurements are assumed non-Gaussian,such that the maximum correntropy criterion(MCC)is chosen to replace the conventional minimum mean square error criterion.Furthermore,the MCC is realized using Gaussian as well as Cauchy kernels by defining an appropriate cost function.Simulation results demonstrate the superior estimation accuracy of the developed estimators for two nonlinear estimation problems.
机标关键词：kalmanfiltersystemscauchycorrentropycubaturekernel-basedmaximum
论文发表日期：2022-11-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：10( 465-474 )
英文信息