Quantifying safety of laser-based navigation

Mathieu Joerger, Boris Pervan

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

In this paper, a new safety risk evaluation method is developed, simulated, and tested for laser-based navigation algorithms using feature extraction (FE) and data association (DA). First, at FE, we establish a probabilistic measure of separation between features to quantify the sensor's ability to distinguish landmarks. Then, an innovation-based DA process is designed to evaluate the impact on integrity risk of incorrect associations, while considering all potential measurement permutations. The algorithm is analyzed and tested in a structured environment.

Original languageEnglish (US)
Article number8395344
Pages (from-to)273-288
Number of pages16
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume55
Issue number1
DOIs
StatePublished - Feb 2019

Keywords

  • Autonomous vehicle
  • data association (DA)
  • integrity
  • navigation
  • safety

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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