This paper aims to address the technical challenges associated with traditional ground-based system by introducing a novel approach of using unmanned aerial vehicle (UAV) to perform tomographic sensing. This reconstruction algorithm uses the most recent development in auroral ionospheric modelling as a synthetic prior combined with an innovative reconstruction approach involving a multiscale Natural Pixel decomposition and a MAP-based penalty weighted least-squared (PWLR) Signal Reconstruction. This proposed algorithm will not only improve the existing CIT techniques by providing high resolution reconstructions of the space plasma density, but also generate a new array of research opportunities for modern space tomographic imaging.
['Yishi Lee', 'Jun Jason Zhang', 'Matthew Zettergren', 'Kimon P. Valavanis']
Unmanned aerial vehicle based passive radar agile sensing for computerized ionospheric tomography