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16 pages, 7423 KiB

Open AccessArticle

Evaluation of HY-2 Series Satellites Mapping Capability on Mesoscale Eddies

by Fangjie Yu, Juanjuan Qi, Yongjun Jia and Ge Chen

Remote Sens. 2022, 14(17), 4262; https://doi.org/10.3390/rs14174262 - 29 Aug 2022

Cited by 3 | Viewed by 1237

Abstract

With the launches of HY-2B, HY-2C and HY-2D, the National Satellite Ocean Application Service (NSOAS) successfully established the first batch of HY-2 constellation on 19 May 2021, dedicated to detecting the marine dynamic environment. While the validation and calibration of HY-2 series satellites [...] Read more.

With the launches of HY-2B, HY-2C and HY-2D, the National Satellite Ocean Application Service (NSOAS) successfully established the first batch of HY-2 constellation on 19 May 2021, dedicated to detecting the marine dynamic environment. While the validation and calibration of HY-2 series satellites have been well studied, using both in situ and cross-track measurements, further evaluation is required of HY-2 series satellites mapping capability on mesoscale eddies. In this study, we conducted two groups of pseudo-observations obtained by ocean models output at positions and times of the satellite along ground tracks. The two altimetry satellite combinations are the Jason-3+Sentinel-3A/B configuration (reference group) and the Jason-3+Sentinel-3A/B+HY-2B/C/D configuration (evaluation group). Three regions at different latitudes were selected as the study areas. Then, we gridded the satellite along ground tracks into synthetic SSH products for each satellite configuration group. Finally, the attributes of mesoscale eddies extracted from gridded products were analyzed to evaluate the mapping capability of HY-2 series satellites. Our results suggest that the gridded products of evaluation groups are more similar to model data compared to reference groups, with a maximum difference reduced by 23%. In terms of eddy identification, the evaluation groups using HY-2 series satellites can alleviate eddy incorrect estimation and add more details to the spatial distribution of eddy radius and amplitude. Additionally, the evaluation groups displayed better performance in mesoscale eddy detection, with a maximum enhancement of 14% and 16% in eddy recognition rate and accuracy. Full article

(This article belongs to the Special Issue Remote Sensing Technology for New Ocean and Seafloor Monitoring)

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12 pages, 4772 KiB

Open AccessArticle

Experimental Measurement of Forward Scattering from Very Rough Sand Ripples in a Water Tank

by Liang Wang, Gaokun Yu, Minshuai Liang, Yun Ren and Linhui Peng

Remote Sens. 2022, 14(16), 3865; https://doi.org/10.3390/rs14163865 - 09 Aug 2022

Viewed by 1240

Abstract

High order Bragg scattering from sand ripples is investigated by a tank experiment, where the artificially produced sand ripples have a spatial period of 0.2 m and ripple height of 5 cm. Bragg scattering has been measured at three frequencies 22 kHz, 24.57 [...] Read more.

High order Bragg scattering from sand ripples is investigated by a tank experiment, where the artificially produced sand ripples have a spatial period of 0.2 m and ripple height of 5 cm. Bragg scattering has been measured at three frequencies 22 kHz, 24.57 kHz, and 27 kHz and three incident grazing angles

20^{\circ}

,

30^{\circ}

,

40^{\circ}

by a method based on the conventional beamforming using two horizontal receiving arrays. It is illustrated that high order Bragg scatterings can be observed, and the corresponding scattered grazing angles agree with the theoretical prediction. Owing to the ripple height being on the order of wavelength, it is found that the distribution of forward scattering amplitude is different from the distribution for sand ripples of small height, i.e., the diffuseness of scattering amplitude is increased with the ripple height. Full article

(This article belongs to the Special Issue Remote Sensing Technology for New Ocean and Seafloor Monitoring)

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16 pages, 4270 KiB

Open AccessArticle

Investigation on Vertical Position and Sound Velocity Variation for GNSS/Acoustic Seafloor Geodetic Calibration Based on Moving Survey Data

by Rui Shan, Huimin Liu, Shuang Zhao and Haojun Li

Remote Sens. 2022, 14(15), 3739; https://doi.org/10.3390/rs14153739 - 04 Aug 2022

Cited by 3 | Viewed by 1428

Abstract

The accuracy of GNSS/Acoustic seafloor geodetic calibration is greatly influenced by the temporal variation of sound velocity, especially in the vertical direction. Aiming at correcting of the unknown parameters related to both the positions and the sound velocity, this paper proposes a step-by-step [...] Read more.

The accuracy of GNSS/Acoustic seafloor geodetic calibration is greatly influenced by the temporal variation of sound velocity, especially in the vertical direction. Aiming at correcting of the unknown parameters related to both the positions and the sound velocity, this paper proposes a step-by-step inversion scheme based on moving survey data. The proposed method firstly estimates the horizontal normalized travel time delay with sound ray tracing strategy and then computes the horizontal position with circle line observations. We reconstructed an inversion scheme for extracting the surface sound velocity disturbance (SSVD) and corrected the vertical position from cross line data. The SSVD is decomposed into a sum of different period disturbances, and a new SSVD is reconstructed by combining the long period disturbance and short period disturbance. The proposed algorithm is verified by the South China Sea experiment for GNSS/Acoustic seafloor geodetic calibration. The results demonstrate that the new method can take the effects of sound velocity variation into consideration and improve the precision of the vertical position, which is superior to the least squares (LS), the single-difference LS for seafloor geodetic calibration. Full article

(This article belongs to the Special Issue Remote Sensing Technology for New Ocean and Seafloor Monitoring)

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11 pages, 2133 KiB

Open AccessCommunication

Sparse Approximation of the Precision Matrices for the Wide-Swath Altimeters

by Max Yaremchuk

Remote Sens. 2022, 14(12), 2827; https://doi.org/10.3390/rs14122827 - 13 Jun 2022

Cited by 1 | Viewed by 1043

Abstract

The upcoming technology of wide-swath altimetry from space will deliver a large volume of data on the ocean surface at unprecedentedly high spatial resolution. These data are contaminated by errors caused by the uncertainties in the geometry and orientation of the on-board interferometer [...] Read more.

The upcoming technology of wide-swath altimetry from space will deliver a large volume of data on the ocean surface at unprecedentedly high spatial resolution. These data are contaminated by errors caused by the uncertainties in the geometry and orientation of the on-board interferometer and environmental conditions, such as sea surface roughness and atmospheric state. Being highly correlated along and across the swath, these errors present a certain challenge for accurate processing in operational data assimilation centers. In particular, the error covariance matrix

R

of the Surface Water and Ocean Topography (SWOT) mission may contain trillions of elements for a transoceanic swath segment at kilometer resolution, and this makes its handling a computationally prohibitive task. Analysis presented here shows, however, that the SWOT precision matrix

R^{- 1}

and its symmetric square root can be efficiently approximated by a sparse block-diagonal matrix within an accuracy of a few per cent. A series of observational system experiments with simulated data shows that such approximation comes at the expense of a relatively minor reduction in the assimilation accuracy, and, therefore, could be useful in operational systems targeted at the retrieval of submesoscale variability of the ocean surface. Full article

(This article belongs to the Special Issue Remote Sensing Technology for New Ocean and Seafloor Monitoring)

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26 pages, 8655 KiB

Open AccessArticle

A Joint Denoising Learning Model for Weight Update Space–Time Diversity Method

by Yu Zhang, Dan Zhang, Zhen Han and Peng Jiang

Remote Sens. 2022, 14(10), 2430; https://doi.org/10.3390/rs14102430 - 19 May 2022

Cited by 2 | Viewed by 1613

Abstract

Space–time diversity (STD) has been widely applied in underwater acoustic (UWA) communication due to its exceptional anti-multipath performance. However, underwater noise can seriously affect the processing results of STD. The conventional filtering algorithms cannot deal with the nonlinear components of underwater noise and [...] Read more.

Space–time diversity (STD) has been widely applied in underwater acoustic (UWA) communication due to its exceptional anti-multipath performance. However, underwater noise can seriously affect the processing results of STD. The conventional filtering algorithms cannot deal with the nonlinear components of underwater noise and may not work well for complex-type signals. This study proposes an improved STD method with a joint noise-reduction learning model for the above issues. We construct a noise-reduction learning model dedicated to complex-type UWA signals in the first stage. Complex-type features based on UWA data are extracted for pre-processing data, and a conditional generative adversarial network (CGAN) is used as the backbone network for noise-reduction. Residual learning is used to accomplish noise cancellation and yield noise-reduction estimates. In the second stage, an STD structure based on a weight update strategy is constructed. The STD structure can further constrain the weights of the signals from the main path, enhance the reception of the main path, and suppress the multi-access interference (MAI) caused by the spread spectrum communication. Finally, combining the signals on each path can improve the communication quality of the system based on the principle of the maximum signal-to-interference plus noise ratio (SINR). The simulation and experiments on a lake showed that the proposed method is more robust over the changing signal-to-noise ratio (SNR) and has a lower bit error rate (BER) than conventional methods. Full article

(This article belongs to the Special Issue Remote Sensing Technology for New Ocean and Seafloor Monitoring)

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18 pages, 4263 KiB

Open AccessArticle

Simulative Evaluation of the Underwater Geodetic Network Configuration on Kinematic Positioning Performance

by Menghao Li, Yang Liu, Yanxiong Liu, Guanxu Chen, Qiuhua Tang, Yunfeng Han and Yuanlan Wen

Remote Sens. 2022, 14(8), 1939; https://doi.org/10.3390/rs14081939 - 17 Apr 2022

Cited by 8 | Viewed by 3765

Abstract

The construction of underwater geodetic networks (UGN) is crucial in marine geodesy. To provide high-precision kinematic positioning for underwater submersibles, an underwater acoustic geodetic network configuration of three seafloor base stations, one subsurface buoy, and one sea surface buoy is proposed. The simulation [...] Read more.

The construction of underwater geodetic networks (UGN) is crucial in marine geodesy. To provide high-precision kinematic positioning for underwater submersibles, an underwater acoustic geodetic network configuration of three seafloor base stations, one subsurface buoy, and one sea surface buoy is proposed. The simulation results show that, for a 3 km-deep sea, based on the proposed UGN, the submersible positioning range and positioning accuracy are primarily affected by the size of the seafloor base station array, while the height of the subsurface buoy has a greater impact on the submersible positioning accuracy than the positioning range. Considering current acoustic ranging technology, the kinematic positioning performance of the UGN is optimal when the seafloor base stations are 9~13 km apart and the subsurface buoy is less than 2.5 km above the seafloor, which can achieve a submersible positioning accuracy of less than 30 m within an underwater space of 25 km × 25 km × 3 km. The proposed cost-effective UGN configuration can provide high-precision submersible kinematic positioning performance for seafloor surveying and ocean precision engineering. The impact of the underwater environment on the acoustic transmission characteristics should be further investigated. Full article

(This article belongs to the Special Issue Remote Sensing Technology for New Ocean and Seafloor Monitoring)

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23 pages, 9396 KiB

Open AccessArticle

Uncertainty Analysis in SAR Sea Surface Wind Speed Retrieval through C-Band Geophysical Model Functions Inversion

by Fabio Michele Rana and Maria Adamo

Remote Sens. 2022, 14(7), 1685; https://doi.org/10.3390/rs14071685 - 31 Mar 2022

Cited by 1 | Viewed by 1473

Abstract

The purpose of the study is to assess the suitability of synthetic aperture radar (SAR) data to provide sea surface wind (SSW) fields along with a spatial distribution of both SSW speed and direction uncertainty. A simple methodology based on geophysical model function [...] Read more.

The purpose of the study is to assess the suitability of synthetic aperture radar (SAR) data to provide sea surface wind (SSW) fields along with a spatial distribution of both SSW speed and direction uncertainty. A simple methodology based on geophysical model function (GMF) inversion to obtain a spatial distribution of both SSW speed and its uncertainty is proposed. Exploiting a dataset of Sentinel-1 images, a sensitivity analysis of the SSW speed uncertainty is carried out on both the uncertainties and the mean values of SAR normalised radar cross section (NRCS), incidence angle and SSW direction, at different spatial scales. The results show that SSW speed uncertainty significantly increases with wind vector cell (WVC) dimension. Moreover, the dominant contribution to the SSW speed uncertainty due to both NRCS and SSW direction uncertainty must always be taken into account. A better precision and accuracy in the estimation of SSW speed and its uncertainty is evidenced by C-band model 7 (CMOD7) GMF rather than the C-band model 5.N (CMOD5.N). To evaluate the results of SSW retrievals, wind data from the European Centre for Medium-Range Weather Forecasts (ECMWF) model are also exploited for comparisons. Findings indicate a high correlation between the uncertainty from SAR estimations and that from the comparison of SAR vs. ECMWF. Full article

(This article belongs to the Special Issue Remote Sensing Technology for New Ocean and Seafloor Monitoring)

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11 pages, 6940 KiB

Open AccessTechnical Note

Underwater Communication Using UAVs to Realize High-Speed AUV Deployment

by Yusuke Yokota and Takumi Matsuda

Remote Sens. 2021, 13(20), 4173; https://doi.org/10.3390/rs13204173 - 18 Oct 2021

Cited by 10 | Viewed by 4829

Abstract

To monitor ocean and seafloor properties in detail, sensors are generally installed on autonomous underwater vehicles (AUVs). An AUV cannot accurately determine its absolute position and needs to communicate with a sea-surface vehicle. However, sea-surface vehicles cannot perform high-speed observations with high efficiency [...] Read more.

To monitor ocean and seafloor properties in detail, sensors are generally installed on autonomous underwater vehicles (AUVs). An AUV cannot accurately determine its absolute position and needs to communicate with a sea-surface vehicle. However, sea-surface vehicles cannot perform high-speed observations with high efficiency due to their low mobility and high labor and equipment costs, e.g., vessel charter charges, operator restraint time on the sea surface during observations, etc. From this perspective, unmanned aerial vehicles (UAVs) have potential as the next-generation communication platform. In this study, we conducted a demonstration experiment to use UAV as a sea-surface base for underwater communication with an AUV. We investigated the capability of a UAV to land on the sea surface, drift like a buoy to receive underwater data, and finally lift off to return to its base. The experimental results suggest that UAVs provide suitable communication performance for research near the shore in terms of robust hovering control, stability against sway, and operation speed. To carry out more complicated work (such as transportation) of UAVs, further research in areas such as weight reduction is required. Full article

(This article belongs to the Special Issue Remote Sensing Technology for New Ocean and Seafloor Monitoring)

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