On uas sensor flight pattern determination for studies in atmospheric science

Tobias J. Weyer, Nick Engelhardt, Suzanne W. Smith

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


Mobile sensing of field quantities is a question of interest for underwater and atmospheric fields. Consequently a number of approaches have been recently developed. In this work, a covariance-based trajectory optimization approach was adopted to develop a method for quantified comparison of candidate flight trajectories for measurements of an atmospheric field. With this method, comparisons are also possible among logistics scenarios involving different numbers and types of UAS platforms. In this approach a posteriori error variance based on spatial and temporal decorrelation scales leads to the optimization integral that is numerically evaluated for each proposed trajectory. A CM1 convective boundary layer simulation dataset was used for the initial evaluation of the method and to determine different spatial decorrelation scales in different directions. In addition, a dataset from a fixed weather tower was used to understand the impact of the temporal decorrelation scale. Ultimately, the uncertainty of field quantity estimates resulting from trajectory families were compared to determine which candidate trajectories are more suitable or are comparable for sampling the field variables of interest.

Original languageEnglish
Title of host publicationAIAA Scitech 2019 Forum
StatePublished - 2019
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: Jan 7 2019Jan 11 2019

Publication series

NameAIAA Scitech 2019 Forum


ConferenceAIAA Scitech Forum, 2019
Country/TerritoryUnited States
CitySan Diego

Bibliographical note

Publisher Copyright:
© 2019 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

ASJC Scopus subject areas

  • Aerospace Engineering


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