HTPCP: GNSS-R multi-channel cross-correlation waveforms post-processing solution for GOLD-RTR instrument

Abstract

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. The GPS open-loop differential real-time receiver (GOLD-RTR) instrument have been proposed as GNSS-R instrument, to gather global positioning satellite system signals after they have been reflected from suitable surfaces (e.g. sea, ice and ground); and extract useful information about those surfaces. However to fully benefit from real-time characteristic, the overhead between the stringent real-time parallel processing and the storage of amount of multi-channel cross-correlation waveforms(CC-WAVs) prior to downlink issues have been addressed. Over last years, several embedded solutions for parallel processing are ready available: Symmetric Multiprocessing (SMP), Network-On-Chip (NOC). Indeed, higher performance is achieved, but bus congestion and memory allocation issues have increased with these new embedded solutions. This paper presents a novel architecture, namely, the Heterogeneous Transmission and Parallel Computing Platform (HTPCP); And the mandates imposed by the stringent timing constraints by a Dual-Port RAM (DPRAM). The pros and cons of different approaches are discussed, range from providing parallel computing to analyzing bus busy ratio and memory access time. The numerical results show that HTPCP reaches a speed-up of 8.17x in comparison to the SMP architecture, which enables the highest throughput in the real-time system design of GNSS-R.