Vision-Aided measurement level integration of multiple GPS receivers for UAVs

Akshay Shetty, Grace Xingxin Gao

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

Abstract

Robust and reliable navigation of Unmanned Aerial Vehicles (UAVs) is an upcoming and promising field of research. In this paper we describe tightly-coupled initialization procedure using a monocular camera to resolve the GPS carrier phase integer ambiguities. This helps us obtain heading estimates during flight, using the GPS receivers. Further, we describe a sensor fusion structure which uses the measurements from multiple GPS receivers and multiple sensors on-board a UAV. We implement an unscented Kalman filter (UKF) to fuse information from the GPS receivers, the monocular camera, the inertial measurement unit (IMU) and the motor tachometers. In the filter we use pseudoranges and carrier phases from the GPS receivers, as opposed to directly using the position updates. Experiments were conducted outdoors with an Ascending Technologies Firefly hexacopter. We validate the integer ambiguity resolution by our tightly coupled initialization, and the robust sensor fusion structure.

Original languageEnglish (US)
Title of host publication28th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2015
PublisherInstitute of Navigation
Pages834-840
Number of pages7
ISBN (Electronic)9781510817258
StatePublished - Jan 1 2015
Event28th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2015 - Tampa, United States
Duration: Sep 14 2015Sep 18 2015

Publication series

Name28th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2015
Volume2

Other

Other28th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2015
CountryUnited States
CityTampa
Period9/14/159/18/15

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Software

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