Robust quaternion Kalman filter for state saturation systems with stochastic nonlinear disturbances

IF 3.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Dongyuan Lin , Xiaofeng Chen , Peng Cai , Yunfei Zheng , Qiangqiang Zhang , Junhui Qian , Shiyuan Wang
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引用次数: 0

Abstract

To tackle the quaternion robust state estimation problem, the robust quaternion Kalman filter (RQKF) has been developed for quaternion signals by the quaternion maximum correntropy criterion (QMCC) under non-Gaussian noises. However, in the presence of saturation phenomena and nonlinear disturbances impacting quaternion systems, the performance of RQKF may deteriorate. Hence, this paper focuses on the quaternion Kalman filtering issue for state saturation systems with stochastic nonlinear disturbances under non-Gaussian noises. First, a feasible upper bound on the filtering error covariance is first obtained by some quaternion matrix techniques, and then a QMCC-based RQKF for state saturation systems (MCQKF-SS) is developed. The posterior estimate of the MCQKF-SS algorithm, developed as an iterative online method with a recursive structure, is updated by a quaternion iterative equation (QIE). Subsequently, a sufficient condition is proposed to ensure the uniqueness of the QIE’s fixed point, thereby guaranteeing the convergence of MCQKF-SS. Moreover, an adaptive kernel width strategy addresses the kernel width selection problem, leading to the development of a variable kernel width version of MCQKF-SS (VKMCQKF-SS). Finally, simulation results of two numerical examples verify the effectiveness and robustness of proposed quaternion algorithms in the considered environment.
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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