RMIT University
Browse

Bistatic measurement system for characterisation of aviation pollutant concentrations

Download (500.13 kB)
conference contribution
posted on 2024-11-23, 06:08 authored by Alessandro GardiAlessandro Gardi, Roberto SabatiniRoberto Sabatini
This paper presents the conceptual design of a low-cost measurement system for the dete1mination of aviation-related pollutant concentrations in dense air traffic areas. The proposed bistatic Light Detection and Ranging (LIDAR) system consists of two noncollocated components. The source component consists of a tuneable laser emitter, which can either be installed on a Remotely Piloted Aircraft System (RP AS) or operated from fixed and movable surface installations. The sensor component is constituted by a target surface calibrated for reflectance and a rail-mounted visible or infrared camera calibrated for radiance. The system perfmms Differential Absorption LIDAR (DIAL) measurements. The relevant oppo1t1mities and challenges, and the viability of the system in the intended operational environments are discussed. N1m1erical simulation results show promising perfmmances in term of error expected error budget even in degraded meteorological conditions, which are comparable to the more complex and relatively costly monostatic LIDAR techniques cmTently available.

History

Related Materials

Start page

1

End page

18

Total pages

18

Outlet

Proceedings of the16th Australian International Aerospace Congress

Editors

Arvind Sinha, Cees Bil, Bogdan Hristea, Bob Teunisse

Name of conference

AIAC 16: Multinatioinal Aerospace Programs-Benefits and Challenges

Publisher

Engineers Australia

Place published

Barton, Australia

Start date

2015-02-23

End date

2015-02-24

Language

English

Copyright

© 2015 Authors; Engineers Australia

Former Identifier

2006052539

Esploro creation date

2020-06-22

Fedora creation date

2015-04-22

Open access

  • Yes

Usage metrics

    Scholarly Works

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC