The feasibility of unmanned aerial vehicle-based acoustic atmospheric tomography

被引:7
|
作者
Finn, Anthony [1 ]
Rogers, Kevin [1 ]
机构
[1] Univ S Australia, Def & Syst Inst, Mawson Lakes, SA 5095, Australia
来源
基金
澳大利亚研究理事会;
关键词
TRAVEL-TIME TOMOGRAPHY; DELAY ESTIMATION; NARROW-BAND; WIND-SPEED; LOCALIZATION; TEMPERATURE; AEROSONDE; AIRCRAFT; ARRAY;
D O I
10.1121/1.4926900
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
A technique for remotely monitoring the near-surface air temperature and wind fields up to altitudes of 1 km is presented and examined. The technique proposes the measurement of sound spectra emitted by the engine of a small unmanned aerial vehicle using sensors located on the aircraft and the ground. By relating projected and observed Doppler shifts in frequency and converting them into effective sound speed values, two- and three-dimensional spatially varying atmospheric temperature and wind velocity fields may be reconstructed using tomography. The feasibility and usefulness of the technique relative to existing unmanned aerial vehicle-based meteorological techniques using simulation and trials is examined. VC 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.
引用
收藏
页码:874 / 889
页数:16
相关论文
共 50 条
  • [21] Unmanned aerial vehicle-based structure from motion biomass inventory estimates
    Bedell, Emily
    Leslie, Monique
    Fankhauser, Katie
    Burnett, Jonathan
    Wing, Michael G.
    Thomas, Evan A.
    [J]. JOURNAL OF APPLIED REMOTE SENSING, 2017, 11
  • [22] ShetlandsUAVmetry: unmanned aerial vehicle-based photogrammetric dataset for Antarctic environmental research
    Roman, Alejandro
    Navarro, Gabriel
    Tovar-Sanchez, Antonio
    Zarandona, Pedro
    Roque-Atienza, David
    Barbero, Luis
    [J]. SCIENTIFIC DATA, 2024, 11 (01)
  • [23] Deep Learning for Unmanned Aerial Vehicle-Based Object Detection and Tracking: A Survey
    Wu, Xin
    Li, Wei
    Hong, Danfeng
    Tao, Ran
    Du, Qian
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2022, 10 (01) : 91 - 124
  • [24] Systemic Performance Analysis on Zoning for Unmanned Aerial Vehicle-Based Service Delivery
    Pedersen, Casper Bak
    Rosenkrands, Kasper
    Sung, Inkyung
    Nielsen, Peter
    [J]. DRONES, 2022, 6 (07)
  • [25] Unmanned Aerial Vehicle-Based Ground-Penetrating Radar Systems A review
    Alvarez Lopez, Yuri
    Garcia-Fernandez, Maria
    Alvarez-Narciandi, Guillermo
    Las-Heras Andres, Fernando
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2022, 10 (02) : 66 - 86
  • [26] Unmanned Aerial Vehicle-Based Compressed Data Acquisition for Environmental Monitoring in WSNs
    Lv, Cuicui
    Yang, Linchuang
    Zhang, Xinxin
    Li, Xiangming
    Wang, Peijin
    Du, Zhenbin
    [J]. SENSORS, 2023, 23 (20)
  • [27] An Unmanned Aerial Vehicle-Based Gas Sampling System for Analyzing CO2 and Atmospheric Particulate Matter in Laboratory
    Li, Chaoqun
    Han, Wenting
    Peng, Manman
    Zhang, Mengfei
    Yao, Xiaomin
    Liu, Wenshuai
    Wang, Tonghua
    [J]. SENSORS, 2020, 20 (04)
  • [28] Automated Unmanned Aerial Vehicle-Based Bridge Deck Delamination Detection and Quantification
    Zhang, Qianyun
    Ro, Sun Ho
    Wan, Zhe
    Babanajad, Saeed
    Braley, John
    Barri, Kaveh
    Alavi, Amir H.
    [J]. TRANSPORTATION RESEARCH RECORD, 2023, 2677 (08) : 24 - 36
  • [29] Efficient unmanned aerial vehicle-based data collection for IoT smart farming
    Haider, Sami Ahmed
    Ahmad, Khwaja Mutahir
    Khan, Abdullah Aman
    [J]. INTERNET OF THINGS, 2024, 26
  • [30] Unmanned Aerial Vehicle-based Autonomous Tracking System for Invasive Flying Insects
    Pak, Jeonghyeon
    Kim, Bosung
    Ju, Chanyoung
    Son, Hyoung Il
    [J]. Computers and Electronics in Agriculture, 2024, 227