Performance of state estimation and fusion with elliptical motion constraints

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider tracking of a target with known elliptical nonlinear constraints on its motion dynamics. The state estimates are generated by sensors and sent over long-haul links to a remote fusion center for fusion. We show that the constraints can be projected onto the ellipse and hence incorporated into the estimation and fusion process. In particular, two methods based on (i) direct connection to the center, and (ii) shortest distance to the ellipse are discussed. A tracking example is used to illustrate the tracking performance using projection-based methods with various fusers in a lossy long-haul tracking environment.

Original languageEnglish
Title of host publicationMultisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System - An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems MFI 2017
EditorsHanseok Ko, Sukhan Lee, Songhwai Oh
PublisherSpringer Verlag
Pages39-51
Number of pages13
ISBN (Print)9783319905082
DOIs
StatePublished - 2018
Event13th IEEE International Conference on Multisensor Integration and Fusion, IEEE MFI 2017 - Daegu, Korea, Republic of
Duration: Nov 16 2017Nov 22 2017

Publication series

NameLecture Notes in Electrical Engineering
Volume501
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference13th IEEE International Conference on Multisensor Integration and Fusion, IEEE MFI 2017
Country/TerritoryKorea, Republic of
CityDaegu
Period11/16/1711/22/17

Funding

Acknowledgments. This work was funded by the Mathematics of Complex, Distributed, Interconnected Systems Program, Office of Advanced Computing Research, U.S. Department of Energy, and SensorNet Project of Office of Naval Research, and was performed at Oak Ridge National Laboratory managed by UT-Battelle, LLC for U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

FundersFunder number
Office of Advanced Computing Research
SensorNet Project of Office of Naval Research
U.S. Department of Energy
Oak Ridge National Laboratory
UT-BattelleDE-AC05-00OR22725

    Keywords

    • Elliptical track constraints
    • Error covariance matrices
    • Long-haul sensor networks
    • Nonlinear constraints
    • Projection
    • Root-mean-square-error (RMSE) performance
    • State estimate fusion

    Fingerprint

    Dive into the research topics of 'Performance of state estimation and fusion with elliptical motion constraints'. Together they form a unique fingerprint.

    Cite this