When: 27th of November, 1:00pm AEDT
Where: This seminar will be partially presented at the ACFR seminar area, J04 lvl 2 (Rose St Building) and partially online via Zoom. RSVP
Speaker: Michael Rubin
Title: Towards real-time characterisation of air turbulence using Radar Acoustic Sounding
Abstract:
The widespread use of small, lightweight, autonomous airborne vehicles has heightened the need for accurate, real-time air turbulence analysis to mitigate their susceptibility to unpredictable atmospheric conditions. This research is on the development of a real-time, accurate and reliable Radar Acoustic Sounding System (RASS) to image air turbulence. The approach uses acoustic pulses and a coaxially aligned Doppler radar to image the acoustic pulses as they propagate through the air. Classically, Radar Acoustic Sounding is typically used in long-range meteorological studies to measure air temperature where the effects of turbulence constitute unwanted noise, this study inverts the problem in order to detect and characterise the intensity and direction of the turbulence as function of range using a conically scanned mirror which allows the acoustics to pass unimpeded while the co-located radar beam is scanned. To function as a RASS, the acoustic beam must remain centered on the origin of the radar beam. A conical scanning, adjustable-pitch mirror that allows for up to 20 degrees of squint angle of the radar beam over a 360 degree scan, while facilitating the unobstructed vertical projection of an acoustic beam through the middle of the mirror, has been designed and developed. Test measurements are ongoing to characterise the mirror transfer function and general radar performance. It is envisaged that the final system will operate at about 94GHz/212kHz and weigh only two hundred grams allowing it to be attached to a UAV.
Bio:
Michael Rubin is a PhD candidate in the School of Aerospace, Mechanical and Mechatronic Engineering at the University of Sydney. His doctoral research is on the development of a Radar Acoustic Sounding System (RASS) as a new sensing modality to detect and characterise atmospheric turbulence at a stand-off range with the eventual application in small autonomous airborne vehicles. Michael holds a Bachelor of Engineering Honours in Mechatronic Engineering from the University of Sydney. He tutors a variety of Mechatronic Engineering courses at the same institution and works part-time in a technical role at the Agricultural Robotics Group at the Australian Centre for Robotics.