HTPCP: GNSS-R multi-channel correlation waveforms post-process solution for GOLD-RTR Instrument

Global navigation satellite system reflectometry (GNSS-R) remote sensing is a new remote sensing technique of satellite navigation application. Essentially, it entails a method of remote sensing that receives and processes microwave signals reflected from various surfaces to extract useful informati...

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Bibliographic Details
Published in:2010 NASA/ESA Conference on Adaptive Hardware and Systems
Main Authors: Guo, Yi, Atienza Alonso, David, Rius, Antonio, Ribo, Serni, Ferrer, Carles
Format: Text
Language:unknown
Published: San Francisco, IEEE Press 2010
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Online Access:http://infoscience.epfl.ch/record/147849
https://doi.org/10.1109/AHS.2010.5546267
https://infoscience.epfl.ch/record/147849/files/NASAESA2010-05546267.pdf
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Summary:Global navigation satellite system reflectometry (GNSS-R) remote sensing is a new remote sensing technique of satellite navigation application. Essentially, it entails a method of remote sensing that receives and processes microwave signals reflected from various surfaces to extract useful information about those surfaces. The GPS open-loop differential real-time receiver (GOLD-RTR) instrument was designed by the ICE (IEEC-CSIC)1 to gather global positioning satellite system signals after they have been reflected from suitable surfaces (e.g. sea, ice and ground). In this paper, the problem of real-time postprocessing design is addressed in order to process the multichannel cross correlations waveform. This work is to realize real time single correlation integration algorithm (SCI) on the proposed novel platform, named as Heterogeneous Transmission and Parallel Computing Platform (HTPCP). The numerical results show that system throughput can reach up to about 1.669MB/sec. Comparing with the state-of-the-art serial SW solution, the processing time of SCI algorithm can improve about 19%. The coherent integration time can improve 8.17 times comparing with the conventional Symmetric Multiprocessing (SMP). And the parallel computing speed of HTPCP outperforms SMP.