Integrity of laser-based feature extraction and data association

Mathieu Joerger, Michael Jamoom, Matthew Spenko, Boris Pervan

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

15 Scopus citations

Abstract

In this paper, a new integrity risk evaluation method is developed and tested for laser and radar-based navigation algorithms using feature extraction (FE) and data association (DA). This work is intended for safety-critical autonomous vehicle navigation. FE and DA are two pre-estimator measurement processing steps that aim at repeatedly and consistently identifying landmarks in the environment. A major risk for safety in FE and DA is caused by incorrect associations (mistaking one landmark for another). To assess this risk, a criterion is first introduced at FE: it establishes the minimum normalized separation between landmarks ensuring that they can be reliably, quantifiably distinguished. Then, an innovation-based DA process is designed, which provides the means to evaluate the probability of incorrect associations while considering all potential measurement permutations. These algorithms are analyzed and tested, showing the impact of incorrect associations on safety risk.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE/ION Position, Location and Navigation Symposium, PLANS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages557-571
Number of pages15
ISBN (Electronic)9781509020423
DOIs
StatePublished - May 26 2016
Externally publishedYes
EventIEEE/ION Position, Location and Navigation Symposium, PLANS 2016 - Savannah, Georgia
Duration: Apr 11 2016Apr 14 2016

Publication series

NameProceedings of the IEEE/ION Position, Location and Navigation Symposium, PLANS 2016

Conference

ConferenceIEEE/ION Position, Location and Navigation Symposium, PLANS 2016
Country/TerritoryGeorgia
CitySavannah
Period4/11/164/14/16

Keywords

  • autonomous vehicle
  • data association
  • integrity
  • navigation safety
  • SLAM

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Instrumentation

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