A Differential Approach for Rain Field Tomographic Reconstruction Using Microwave Signals from LEO Satellites

Felix Shen, David Huang, Claire Vincent, Wenxiao Wang, Roberto Togneri

Research output: Chapter in Book/Conference paperConference paperpeer-review

3 Citations (Scopus)
31 Downloads (Pure)

Abstract

A differential approach is proposed for tomographic rain field reconstruction using the estimated signal-to-noise ratio of microwave signals from low earth orbit satellites at the ground receivers, with the unknown baseline values eliminated before using least squares to reconstruct the attenuation field. Simulations are done when the baseline is modelled by an autoregressive process and when the baseline is assumed fixed. Comparisons between the reconstruction results for the differential and non-differential approaches suggest that the differential approach performs better in both scenarios. For high correlation coefficient and low model noise in the autoregressive process, the differential approach surpasses the non-differential approach significantly.
Original languageEnglish
Title of host publication ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages9001-9005
Number of pages5
ISBN (Electronic)9781509066315
DOIs
Publication statusPublished - May 2020
Event2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020 - Barcelona, Spain
Duration: 4 May 20208 May 2020

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2020-May
ISSN (Print)1520-6149

Conference

Conference2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020
Abbreviated titleICASSP 2020
Country/TerritorySpain
CityBarcelona
Period4/05/208/05/20

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