Rationale of GNSS Reflected Delay–Doppler Map (DDM) Distortions Induced by Specular Point Inaccuracies

Abstract

Global navigation satellite system reflectometry (GNSS-R)-derived winds from the cyclone GNSS (CYGNSS) satellite constellation are expected to significantly improve weather forecasts in the tropical region. Delay-Doppler maps (DDMs) acquired by the TechDemosat-1 (TDS-1) GNSS-R satellite mission suffer from distortions that are highly correlated to on-board specular point estimation inaccuracies. Such distortions may affect wind retrievals, especially when multilook approaches aiming at exploiting the ambiguity-free area of the DDM are applied. This article demonstrates: that CYGNSS DDMs are also affected by such distortions; the rationale of DDM shape asymmetries induced by specular point location inaccuracies; and a simple strategy for reducing such induced distortions. Two different datasets have been used, consisting of both regular and raw intermediate frequency CYGNSS measurements. The results show that, similar to TDS-1, the CYGNSS DDM distortions are correlated to specular point location inaccuracies. Furthermore, such inaccuracies are significantly reduced if more accurate specular point related parameters are used to recompress the raw GNSS-R echo, highlighting some sampling issues that are common to both TDS-1 and CYGNSS missions. These results suggest that multilook wind retrieval approaches aiming at exploiting also the peripheral parts of the DDM may be seriously compromised by such distortions. The latter may be substantially reduced by oversampling the outcoming DDM and by a posteriori choosing the proper DDM subsample. For future upcoming GNSS-R missions, it is strongly recommended to store the raw data for eventual reprocessing in case of miscalibration or processing issues such as those shown in this article.Index Terms-Delay-Doppler map (DDM) distortions, global navigation satellite system (GNSS), reflectometry.

On the Impact and Mitigation of Signal Crosstalk in Ground-Based and Low Altitude Airborne GNSS-R

“…It is worth pointing out that since the seminal GNSS-R works [4,[11][12][13][14][15][16][17], a significant number of contributions have been made in the field over the last decade, leading to a non-negligible amount of results for both iGNSS-R and cGNSS-R. For completeness, we summarize some of the main contributions in the sequel: (i) a well-accepted model for the reflected waveform is the one derived in [18], which can be computed very efficiently using the methodology in [19]; (ii) the specular point delay can be computed as the maximum derivative of the reflected waveform [20,21], by fitting a model to the observed waveform [22] or taking the maximum as in standard GNSS receivers (i.e., the maximum likelihood solution) if the waveform is not deformed by the surface; (iii) the impact of different processing and system errors on the DDM were analyzed in [23][24][25][26]; (iv) the system performance and noise characterization were studied in [27][28][29] and the statistics of the GNSS-R waveforms in [30,31] and crosstalk in [22]; and (v) several results with real data are reported in the literature [32][33][34][35][36][37][38][39].…”