elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

A Novel Kalman Filter Design and Analysis Method Considering Observability and Dominance Properties of Measurands Applied to Vehicle State Estimation

Ruggaber, Julian and Brembeck, Jonathan (2021) A Novel Kalman Filter Design and Analysis Method Considering Observability and Dominance Properties of Measurands Applied to Vehicle State Estimation. Sensors, 21. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/s21144750. ISSN 1424-8220.

[img] PDF - Published version
13MB

Official URL: https://www.mdpi.com/1424-8220/21/14/4750

Abstract

In Kalman filter design, the filter algorithm and prediction model design are the most discussed topics in research. Another fundamental but less investigated issue is the careful selection of measurands and their contribution to the estimation problem. This is often done purely on the basis of empirical values or by experiments. This paper presents a novel holistic method to design and assess Kalman filters in an automated way and to perform their analysis based on quantifiable parameters. The optimal filter parameters are computed with the help of a nonlinear optimization algorithm. To determine and analyze an optimal filter design, two novel quantitative nonlinear observability measures are presented along with a method to quantify the dominance contribution of a measurand to an estimate. As a result, different filter configurations can be specifically investigated and compared with respect to the selection of measurands and their influence on the estimation. An unscented Kalman filter algorithm is used to demonstrate the method’s capabilities to design and analyze the estimation problem parameters. For this purpose, an example of a vehicle state estimation with a focus on the tire-road friction coefficient is used, which represents a challenging problem for classical analysis and filter parameterization.

Item URL in elib:https://elib.dlr.de/143206/
Document Type:Article
Title:A Novel Kalman Filter Design and Analysis Method Considering Observability and Dominance Properties of Measurands Applied to Vehicle State Estimation
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Ruggaber, JulianJulian.Ruggaber (at) dlr.dehttps://orcid.org/0000-0003-4300-9104
Brembeck, Jonathanjonathan.brembeck (at) dlr.dehttps://orcid.org/0000-0002-7671-5251
Date:12 July 2021
Journal or Publication Title:Sensors
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:21
DOI :10.3390/s21144750
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Special Issue: Advance in Sensors and Sensing Systems for Driving and Transportation: Part B
ISSN:1424-8220
Status:Published
Keywords:Kalman filter; estimator design; nonlinear state estimation; nonlinear observability; tire-road friction coefficient; vehicle dynamics; vehicle state estimation
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC KoFiF
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of System Dynamics and Control > Vehicle System Dynamics
Deposited By: Ruggaber, Julian
Deposited On:30 Sep 2021 17:56
Last Modified:30 Sep 2021 17:56

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.