Onboard Wind Velocity Estimation Comparison for Unmanned Aircraft Systems

Matthew B. Rhudy, Yu Gu, Jason N. Gross, Haiyang Chao

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


This paper presents a novel wind estimation approach, which is compared with existing ideas utilizing different combinations of common aircraft sensors to estimate the wind velocity in real time at the location of an aircraft. These different techniques were evaluated using simulation data as well as two experimental unmanned aircraft flight tests using validation data from a ground weather station. Significant performance advantage was shown of the new filtering technique over the existing approaches.

Original languageEnglish (US)
Article number7807266
Pages (from-to)55-66
Number of pages12
JournalIEEE Transactions on Aerospace and Electronic Systems
Issue number1
StatePublished - Feb 2017

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Onboard Wind Velocity Estimation Comparison for Unmanned Aircraft Systems'. Together they form a unique fingerprint.

Cite this