A Computationally Efficient GNSS/INS Design of Multirotor based on Error-state Kalman Filter

Sheng Wen Cheng*, Yi Hsiang Huang

*Corresponding author for this work

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

Abstract

This paper presents a GNSS/INS based on an error-state Kalman filter (ESKF) to combine the global navigation satellite system (GNSS) and inertial navigation system (INS) for multirotors. The onboard sensors consist of an inertial measurement unit (IMU), a magnetometer, a GNSS receiver, and a rangefinder. The proposed system can estimate the position, velocity, quaternion, and IMU bias, where the INS design significantly improves the positioning update rate of the GNSS. In addition, to execute the algorithm on flight computers with restricted computational resources, a code generator is developed to utilize the sparse and symmetric structure of the ESKF, which can produce high-efficient C code to speed up the computation time.

Original languageEnglish
Title of host publication2023 62nd Annual Conference of the Society of Instrument and Control Engineers, SICE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages907-913
Number of pages7
ISBN (Electronic)9784907764807
DOIs
StatePublished - 2023
Event62nd Annual Conference of the Society of Instrument and Control Engineers, SICE 2023 - Tsu, Japan
Duration: 6 Sep 20239 Sep 2023

Publication series

Name2023 62nd Annual Conference of the Society of Instrument and Control Engineers, SICE 2023

Conference

Conference62nd Annual Conference of the Society of Instrument and Control Engineers, SICE 2023
Country/TerritoryJapan
CityTsu
Period6/09/239/09/23

Keywords

  • Global Positioning System
  • Inertial Navigation System
  • Unmanned Aerial Vehicle

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