Overbounding sequential estimation errors due to non-Gaussian correlated noise

Steven Langel, Omar García Crespillo, Mathieu Joerger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we develop, analyze, and implement a new recursive method to conservatively account for non-Gaussian measurement errors with an uncertain correlation structure in Kalman filters (KFs). Under the assumptions of symmetric overbounding, the method guarantees a CDF overbound on the entire KF estimation error distribution. First, we leverage previous work on symmetric overbounding and frequency-domain overbounding to show how to transform a measurement domain CDF overbound into a position domain overbound. The second part of the paper evaluates the proposed method through Monte Carlo simulation for a GPS-based position estimation problem. Specifically, we show that while frequency domain overbounding produces a position domain overbound for Gaussian noise with an uncertain correlation structure, combination with symmetric overbounding is required to ensure position domain overbounding for non-Gaussian correlated noise.

Original languageEnglish (US)
Title of host publicationProceedings of the 33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020
PublisherInstitute of Navigation
Pages1054-1067
Number of pages14
ISBN (Electronic)0936406267, 9780936406268
DOIs
StatePublished - 2020
Externally publishedYes
Event33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020 - Virtual, Online
Duration: Sep 22 2020Sep 25 2020

Publication series

NameProceedings of the 33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020

Conference

Conference33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020
CityVirtual, Online
Period9/22/209/25/20

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Electrical and Electronic Engineering

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