Study of Delay Drift in GNSS-R Altimetry

Martín-Neira, Manuel; DaAddio, Salvatore; Vitulli, Raffaele

doi:10.1109/jstars.2014.2307168

Cited by 5 publications

(5 citation statements)

References 3 publications

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“…The new methods exploit a variety of techniques for enhancing performance characterised by improvements to spatial and temporal resolutions, signal to noise ratio and/or accuracy and precision. With respect to error characterisation, Martin-Neira et al [36] studied the effects of errors in delay drift compensation on the waveform and its impact on the altimetric accuracy and precision, while Pascual et al [37] used simulated GPS and Galileo signals to investigate the impact of bandwidth and low-power transmitters on height accuracy and precision. Rius et al [38] investigated the scatterometric and specular delay observables and considered various sources of uncertainty including observation statistics and model parameterisation or calibration error.…”

Section: Ocean Observationmentioning

confidence: 99%

An overview of GNSS remote sensing

Rizos

Burrage

et al. 2014

EURASIP J. Adv. Signal Process.

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The Global Navigation Satellite System (GNSS) signals are always available, globally, and the signal structures are well known, except for those dedicated to military use. They also have some distinctive characteristics, including the use of L-band frequencies, which are particularly suited for remote sensing purposes. The idea of using GNSS signals for remote sensing -the atmosphere, oceans or Earth surface -was first proposed more than two decades ago. Since then, GNSS remote sensing has been intensively investigated in terms of proof of concept studies, signal processing methodologies, theory and algorithm development, and various satellite-borne, airborne and ground-based experiments. It has been demonstrated that GNSS remote sensing can be used as an alternative passive remote sensing technology. Space agencies such as NASA, NOAA, EUMETSAT and ESA have already funded, or will fund in the future, a number of projects/missions which focus on a variety of GNSS remote sensing applications. It is envisaged that GNSS remote sensing can be either exploited to perform remote sensing tasks on an independent basis or combined with other techniques to address more complex applications. This paper provides an overview of the state of the art of this relatively new and, in some respects, underutilised remote sensing technique. Also addressed are relevant challenging issues associated with GNSS remote sensing services and the performance enhancement of GNSS remote sensing to accurately and reliably retrieve a range of geophysical parameters. Review

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Section: Ocean Observationmentioning

confidence: 99%

An overview of GNSS remote sensing

Rizos

Burrage

et al. 2014

EURASIP J. Adv. Signal Process.

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“…Papers [31] and [32] both look at the retracking strategies as a way to address the effect of the delay (and Doppler) drifts suffered by the altimetric observables during the integration period. These papers analyze how to mitigate this effect and the final residual impact on the altimetric solution.…”

Section: Altimetrymentioning

confidence: 99%

“…These papers analyze how to mitigate this effect and the final residual impact on the altimetric solution. In [31], it is found that, for the PARIS-IOD scenario, both the coherent time and the refreshing period are relevant parameters to control the retracking performance: shorter coherent times are better to reduce the negative effect of the drift, but it is possible to preserve precision in longer integrations times by refreshing the delay compensation at every correlation period. The analysis is extended to the effects of the Doppler dynamic variations within integration in [32].…”

Section: Altimetrymentioning

confidence: 99%

Foreword to Special Issue on Reflectometry using Global Navigation Satellite Systems and Other Signals of Opportunity (GNSS+R)

Garrison

Cardellach

Gleason

et al. 2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…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].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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Global Navigation Satellite System Reflectometry (GNSS-R) is a powerful way to retrieve information from a reflecting surface by exploiting GNSS as signals of opportunity. In dual antenna conventional GNSS-R architectures, the reflected signal is correlated with a clean replica to obtain the specular reflection point delay and Doppler estimates, which are further processed to obtain the GNSS-R product of interest. An important problem that may appear for low elevation satellites is signal crosstalk, that is the direct line-of-sight signal leaks into the antenna dedicated to the reflected signal. Such crosstalk may degrade the overall system performance if both signals are very close in time, similar to multipath in standard GNSS receivers, the reason why mitigation strategies must be accounted for. In this article: (i) we first provide a geometrical analysis to justify that the estimation performance is only affected for low height receivers; (ii) then, we analyze the impact of crosstalk if not taken into account, by comparing the single source conditional maximum likelihood estimator (CMLE) performance in a dual source context with the corresponding Cramér–Rao bound (CRB); (iii) we discuss dual source estimators as a possible mitigation strategy; and (iv) we investigate the performance of the so-called variance estimator, which is designed to eliminate the coherent signal part, compared to both the CRB and non-coherent dual source estimators. Simulation results are provided for representative GNSS signals to support the discussion. From this analysis, it is found that: (i) for low enough reflected-to-direct signal amplitude ratios (RDR), the crosstalk has no impact on standard single source CMLEs; (ii) for high enough signal-to-noise ratios (SNR), the dual source estimators are efficient irrespective of the RDR, then being a promising solution for any reflected signal scenario; (iii) non-coherent dual source estimators are also efficient at high SNR; and (iv) the variance estimator is efficient as long as the non-coherent part of the signal is dominant.

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Study of Delay Drift in GNSS-R Altimetry

Cited by 5 publications

References 3 publications

An overview of GNSS remote sensing

An overview of GNSS remote sensing

Foreword to Special Issue on Reflectometry using Global Navigation Satellite Systems and Other Signals of Opportunity (GNSS+R)

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

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