Huber's M-estimation-based cubature Kalman filter for an INS/DVL integrated system
type: Item
instance of: scholarly article
title: Huber's M-estimation-based cubature Kalman filter for an INS/DVL integrated system
zbMATH Open document ID: 1459.93180
DOI: 10.1155/2020/1060672
author: Yao Li
author: Lanhua Hou
author: Yang Yang
author: Jinwu Tong
published in: Mathematical Problems in Engineering
publication date: 2020-10-14T00:00:00Z
review text: Summary: To deal with the problems of outliers and nonlinearity in the complex underwater environment, a Huber's M-estimation-based cubature Kalman filter (CKF) is proposed for an inertial navigation system (INS)/Doppler velocity log (DVL) integrated system. First, a loosely coupled INS/DVL integrated system is designed, and the nonlinear system model is established in the case of big misalignment angle. Then, Huber's M-estimation is introduced for robust estimation to resist outliers. Meanwhile, the CKF is focused to handle the nonlinearity of the state equation. Finally, simulation and the vehicle test are conducted to evaluate the effectiveness of the proposed method. Results show that the proposed method outperforms the conventional Kalman filter (KF) and outlier detection-based robust cubature Kalman filter (RCKF) in terms of navigation accuracy in the complex underwater environment.
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 62G35
Mathematics Subject Classification ID: 62J05
zbMATH DE Number: 7260828
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2020/1060672
OpenAlex ID: W3088311925
cites work: A robust regression methodology via M-estimation
cites work: Robust regression: Asymptotics, conjectures and Monte Carlo
description: scientific article; zbMATH DE number 7260828