elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Artificial Neural Networks for Individual Tracking and Characterization of Wake Vortices in LIDAR Measurements

Stephan, Anton and Rotshteyn, Grigory and Wartha, Niklas Louis and Holzäpfel, Frank and Petross, Nicolass and Stietz, Lars Olaf (2023) Artificial Neural Networks for Individual Tracking and Characterization of Wake Vortices in LIDAR Measurements. In: AIAA AVIATION 2023 Forum, 2023 (3682). AIAA AVIATION 2023 Forum, 2023-06-12 - 2023-06-16, San Diego, California, USA. doi: 10.2514/6.2023-3682.

[img] PDF
4MB

Official URL: https://arc.aiaa.org/doi/abs/10.2514/6.2023-3682

Abstract

A vortex detection and characterization strategy in LiDAR measurements (Light Detection and Ranging), consisting of two different parts, is presented in this study. First, a two-stage detection pipeline is implemented combining the computer vision deep neural network YOLO and a regression convolutional neural network to detect vortices individually. An accuracy in the order of the instrument accuracy is achieved. Second, a new characterization method the so-called Projection Method is presented which has has the following important features. First, it is very accurate. Second, it yields valuable quantification of the accuracy of the results. Third, it is very fast and outperforms conventional methods by two to three orders of magnitude, hence it enables to process a high amount of data in a short time. Fourth, it provides much flexibility in choosing different models and compare the performance of the respective models. Fifth, it comes with a natural visualization of the underlying calculus. Sixth, it can be generalized to situations, where measurements provide a reduced and skewed image of the reality and certain structures or features have to be identified and characterized employing models.

Item URL in elib:https://elib.dlr.de/198308/
Document Type:Conference or Workshop Item (Speech)
Title:Artificial Neural Networks for Individual Tracking and Characterization of Wake Vortices in LIDAR Measurements
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Stephan, AntonDLR, IPAUNSPECIFIEDUNSPECIFIED
Rotshteyn, GrigoryDLR, IPAUNSPECIFIEDUNSPECIFIED
Wartha, Niklas LouisDLR, IPAhttps://orcid.org/0000-0002-9672-2360UNSPECIFIED
Holzäpfel, FrankDLR, IPAhttps://orcid.org/0000-0003-3182-1832UNSPECIFIED
Petross, NicolassDLR, IPAUNSPECIFIEDUNSPECIFIED
Stietz, Lars OlafDLR-IPA, Universität HamburgUNSPECIFIEDUNSPECIFIED
Date:12 June 2023
Journal or Publication Title:AIAA AVIATION 2023 Forum
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:2023
DOI:10.2514/6.2023-3682
Status:Published
Keywords:lidar, wake vortex detection, computer vision, image processing, projection method
Event Title:AIAA AVIATION 2023 Forum
Event Location:San Diego, California, USA
Event Type:international Conference
Event Start Date:12 June 2023
Event End Date:16 June 2023
Organizer:AIAA
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Air Transportation and Impact
DLR - Research area:Aeronautics
DLR - Program:L AI - Air Transportation and Impact
DLR - Research theme (Project):L - Climate, Weather and Environment
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Transport Meteorology
Deposited By: Stephan, Anton
Deposited On:20 Oct 2023 09:28
Last Modified:24 Apr 2024 20:58

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Website and database design: Copyright © German Aerospace Center (DLR). All rights reserved.