Sea Surface Altimetry Based on Airborne GNSS Signal Measurements

Yu, Kegen; Rizos, Chris; Dempster, Andrew G.

doi:10.5194/isprsannals-i-7-347-2012

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…Both the Lidar experiment and the GNSS reflectometry experiment were conducted in the aircraft at the same time. Details about this experiment can be found in [11].…”

Section: Estimation Results Using Experimental Datamentioning

confidence: 99%

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Performance of GNSS-based altimetry using airborne experimental data

Rizos

Dempster

2012

2012 Workshop on Reflectometry Using GNSS and Other Signals of Opportunity (GNSS+R)

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This paper focuses on sea surface height (SSH) estimation using GNSS direct and reflected signals observed via an airborne receiver. A power-ratio-based method is presented to compute the relative delay of the reflected signal, which is then used to estimate the SSH. The power ratio is defined as the ratio of the correlation power at the code phase over the peak correlation power. Preliminary results from processing airborne experimental data collected over a duration of 1 minute demonstrate that the mean power ratios associated with four satellites are very similar. When such a single constant mean power ratio is used to estimate the relative delay and the SSH, the mean of the SSH estimation errors is 4.5cm and the error standard deviation (STD) is 1.08m in the presence of significant wave height of about 4 metres.

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“…Both the Lidar experiment and the GNSS reflectometry experiment were conducted in the aircraft at the same time. Details about this experiment can be found in [11].…”

Section: Estimation Results Using Experimental Datamentioning

confidence: 99%

“…SSH is calculated relative to the WGS84 mean sea level (MSL) which has zero altitude. A two-loop iterative method for SSH calculation is proposed in [11]. For easy reference this method is briefly described below.…”

Section: Sea Surface Height Calculationmentioning

confidence: 99%

Performance of GNSS-based altimetry using airborne experimental data

Rizos

Dempster

2012

2012 Workshop on Reflectometry Using GNSS and Other Signals of Opportunity (GNSS+R)

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“…This bi-/multistatic observation is known as GNSS reflectometry and was proposed by Marin-Neira in 1993 to provide a high density of sea surface heights through the simultaneous tracking of several observation points [1]. At present, GNSS reflectometry is demonstrated to be capable of measuring sea surface height [2][3][4], wind speed [5][6][7], sea ice [8][9][10], and soil moisture [11][12][13]. Compared to radar altimeters and scatterometers, GNSS reflectometry uses low power and is lower cost because of the lack of a transmitter and can provide higher spatial-temporal resolution with many GNSS satellites.…”

Section: Introductionmentioning

confidence: 99%

Measurement of the Sea Surface Height with Airborne GNSS Reflectometry and Delay Bias Calibration

et al. 2021

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Sea surface height can be measured with the delay between reflected and direct global navigation satellite system (GNSS) signals. The arrival time of a feature point, such as the waveform peak, the peak of the derivative waveform, and the fraction of the peak waveform is not the true arrival time of the specular signal; there is a bias between them. This paper aims to analyze and calibrate the bias to improve the accuracy of sea surface height measured by using the reflected signals of GPS CA, Galileo E1b and BeiDou B1I. First, the influencing factors of the delay bias, including the elevation angle, receiver height, wind speed, pseudorandom noise (PRN) code of GPS CA, Galileo E1b and BeiDou B1I, and the down-looking antenna pattern are explored based on the Z-V model. The results show that (1) with increasing elevation angle, receiver height, and wind speed, the delay bias tends to decrease; (2) the impact of the PRN code is uncoupled from the elevation angle, receiver height, and wind speed, so the delay biases of Galileo E1b and BeiDou B1I can be derived from that of GPS CA by multiplication by the constants 0.32 and 0.54, respectively; and (3) the influence of the down-looking antenna pattern on the delay bias is lower than 1 m, which is less than that of other factors; hence, the effect of the down-looking antenna pattern is ignored in this paper. Second, an analytical model and a neural network are proposed based on the assumption that the influence of all factors on the delay bias are uncoupled and coupled, respectively, to calibrate the delay bias. The results of the simulation and experiment show that compared to the meter-level bias before the calibration, the calibrated bias decreases the decimeter level. Based on the fact that the specular points of several satellites are visible to the down-looking antenna, the multi-observation method is proposed to calibrate the bias for the case of unknown wind speed, and the same calibration results can be obtained when the proper combination of satellites is selected.

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GNSS-Based Model-Free Sea Surface Height Estimation in Unknown Sea State Scenarios

Rizos

Dempster

2014

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

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Sea Surface Altimetry Based on Airborne GNSS Signal Measurements

Cited by 5 publications

References 9 publications

Performance of GNSS-based altimetry using airborne experimental data

Performance of GNSS-based altimetry using airborne experimental data

Measurement of the Sea Surface Height with Airborne GNSS Reflectometry and Delay Bias Calibration

GNSS-Based Model-Free Sea Surface Height Estimation in Unknown Sea State Scenarios

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