After over 12 years of development, the HY-2 series microwave scatterometers have been providing stable and reliable Ku-band observation data for operational forecasting departments and marine scientific research departments. The observation data of the satellite constellation comprising the HY-2B/C/D series satellites have played an important role in fields such as numerical forecasting models, typhoon monitoring, and polar sea ice edge identification. In 2019, the HY-2A scatterometer was retired after eight years of operation, having accumulated valuable experience for subsequent payloads and improvements in the processing algorithms of ground systems. Beginning from the HY-2B satellite, the performance of the scatterometer payload has been greatly improved, and the ground data processing system has also been improved accordingly. In addition, compared to the ECMWF Reanalysis v5 (ERA5) wind field, the wind speed accuracy has been increased from 1.35 to 0.9 m/s, and the wind direction accuracy has been increased from 27° to 12°, which is closely related to the improvement of the signal-to-noise ratio (SNR) of the observed data. In this article, the optimization process from experimental satellite payload to operational payload is introduced, then the calculation method of the normalized radar cross section (NRCS) is described in detail, and the consistency of observation data of four payloads is analyzed. The results show that the change in signal bandwidth, increase in signal slice, and improved slice finding and accumulation method have improved the data’s SNR reduced the measurement error, thus fundamentally ensuring the improvement of wind field inversion accuracy.

With the development of deep learning (DL), research on ship classification in synthetic aperture radar (SAR) images has made remarkable progress. However, such research has primarily focused on classifying large ships with distinct features, such as cargo ships, containers, and tankers. The classification of SAR fishing vessels is extremely challenging because of two main reasons: 1) the small size and minor interclass differences of fishing vessels make learning fine-grained features difficult, and 2) determining fishing vessel types is difficult, resulting in a lack of labeled data. Hence, after designing a process framework for vessel tagging, we construct a high-resolution fine-grained fishing vessel classification dataset (FishingVesselSAR), which contains 116 gillnetters, 72 seiners, and 181 trawlers. We then propose a novel DL model (FishNet) that aims to strengthen feature extraction and utilization. In FishNet, we introduce four innovative modules to ensure superior performance in SAR fishing vessel classification: a multipath feature extraction (MUL) module, a feature fusion (FF) module, a multilevel feature aggregation (MFA) module and a parallel channel and spatial attention (PCSA) module. Furthermore, we design an adaptive loss function to achieve better classification performance by mitigating the effects of class imbalance. In this paper, we report extensive ablation studies conducted to confirm the efficacy of the five improvements listed above. Sufficient comparisons with 33 advanced methods from the DL and SAR target classification communities demonstrate that FishNet achieves a SAR fishing vessel classification accuracy of 89.79%, which is 6.77% higher than that of the second-best method.

The azimuth cutoff wavelength of SAR is an important parameter for retrieval of sea surface wind and wave. Earlier studies have fully demonstrated the substantial dependence of azimuth cutoff wavelength on polarization, but the present studies only focus on H-V linear polarization bases (HH, HV/VH, and VV) without considering the effects of other polarization bases (e.g., linear rotated, circular, and elliptical polarization). Benefiting from the quad-polarization advantage of GaoFen-3 SAR wave mode data and the support of polarization basis transformation theory, this study used 4,648 SAR data to study the correlation between cutoff wavelength and wind and wave parameters (e.g., significant wave height, and wind speed) under different polarization bases, and analyzed the variation of correlation coefficient caused by polarization basis change. Finally, the results were applied to evaluating the performance of wind and wave parameters retrieval. The results of the study show that the azimuth cutoff is strongly dependent on the polarization state of electromagnetic wave. The azimuth cutoff wavelength under the elliptical polarization bases has higher correlation with wind and wave than that under H-V linear, circular, and linear rotated polarization bases. Using the azimuth cutoff wavelength of the elliptical polarization bases can significantly improve the retrieval accuracy of wind and wave parameters. This study shall enhance the capabilities of polarized SAR systems to precisely derive more ocean surface properties. The result implies that polarization basis is an important factor that must be considered in future ocean SAR studies.

The HY-2 series scatterometers (HSCAT) are now providing global Ku-band radar observations. In order to build two-decade normalized radar cross section ($\sigma ^{\circ }$) datasets with high quality and high stability, increased attention should first be paid to the instrument variations caused by space environments. The HY-2B scatterometer (HSCAT-B) has operated to yield a two-year dataset in orbit. The monitoring of long-term ocean calibration results and telemetric temperatures indicate that beam radiometric imbalances and long-term instability exist in$\sigma ^{\circ }$due to the gain variations related to temperature changes. Such variations will result in estimated$\sigma ^{\circ }$biases with a peak-to-peak of approximately 0.5 dB. Gain-related calibration models depicting the functions of temperatures were developed using ocean calibration results. The beam radiometric imbalances were corrected using linear gain compensation models of antenna temperatures. The long-term instability was corrected using a linear dependence on microwave front-end and antenna temperatures. Following gain-related calibration, the beam imbalances and long-term instability of the HSCAT-B$\sigma ^{\circ }$were eliminated. The seasonal responses over the Amazon rainforest were also found to correspond to the QuikSCAT$\sigma ^{\circ }$measurements, with amplitudes of approximately 0.15 dB for the morning passes and approximately 0.1 dB for the evening passes. The corrected$\sigma ^{\circ }$will be more suitable for the generation of climate data records. In addition, with the exception of the prelaunch thermal vacuum test, the external calibrations using natural targets are considered to be alternative approaches to gain-related calibrations due to the temperature variations of radar electronics.

The HY-2B scatterometer (HSCAT-B) has now completed a one-year orbit. The instrument was declared operational after six months of in-orbit testing. The ocean wind field products are routinely being made available to the global science community. The HY-2B will work with the HY-2A to provide the Ku-band sea surface observations on a long-term scale, and this collaboration is expected to be important for disaster prevention and mitigation, as well as globally focused climate change research. However, to obtain reasonable evaluations of the system’s functional, performance, and instrument stability results, the temperature, internal calibration parameters, attitude angles, and normalized radar cross section (NRCS) of the instrument were rigorously analyzed during the in-orbit tests. This study provided an overview of the six-month in-orbit testing process results. The temperature levels of some important parts of the scatterometer were found to meet the design requirements. The internal calibration and noise power had shown similar trends and were both within the normal range. The attitude angles, which mainly included the roll and pitch, had displayed variations within a very small scope. The evaluation results of the Amazon rainforest observations indicated that the scatterometer instrument had met all the design requirements and had established a good database for geophysical processing.

The new Ku-band scatterometer (HSCAT-B) onboard the HY-2B satellite was launched on October 25, 2018, and soon after the C-band scatterometer (Advanced Scatterometer (ASCAT)-C) onboard the MetOp-C satellite was launched on November 6, 2018. This article aims to validate the new sea surface wind products from them, and also to summarize the common issues in current scatterometer wind products. Thus, other scatterometer data are also used for comparisons, including the C-band MetOp-B/ASCAT, and Ku-band SCATSAT-1/OSCAT2 and HY-2A/SCAT winds. In this study, the C-band and Ku-band scatterometer wind products were each reproduced using the same procedures, in terms of backscatter calibration, wind retrieval, and quality control. The scatterometer winds are compared to the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 winds or buoy winds, and the results show that the quality of ASCAT-C winds is almost the same as the well-known ASCAT-B; the HSCAT-B winds show quite good quality and similar validating statistics as ASCAT winds. Noticeable wind-speed-dependent biases are found in all Ku-band scatterometer winds, which suggests that refinements are needed for the NSCAT-4 geophysical model function, especially in terms of wind speed dependence for all incidence angles.

HY-2B satellite is launched on 25thOct, 2018 at Taiyuan satellite launch center. It carried four main payloads: radar altimeter, microwave scatterometer, scanning microwave radiometer, and corrected microwave radiometer. HY-2B microwave scatterometer (HY-2B/SCAT) is a pencil-beam rotating scatterometer, which is simillar to HY-2A microwave scatterometer (HY-2A/SCAT). HY-2B satellite is in the same orbit of HY-2A, and about 30 min ahead of HY-2A. The HY-2B microwave scatterometer started to work on 30thOctober, after days of testing. The performance of HY-2B/SCAT become stable since 14th, Nov. This paper provied some preliminary results of HY-2B/SCAT data, such as pulse power DN value, sigma0, retrieved sea surface wind field.

The Chinese HY-2A satellite microwave scatterometer (HSCAT) is designed to measure the ocean surface wind vector with a large observation swath. HSCAT is a Ku-band scatterometer that has continuously observing the earth’s surface for more than 6 years. Approximately, 30 000 orbit revolutions of scientific data are archived in its ground application system. To further understand the characteristics of the instrument, deeper analyses of these scientific data must be carried out. Currently, the geolocation accuracy of the normalized radar cross section (NRCS) has yet to be documented. However, geolocation errors can cause significant measurement bias, and have large impacts on the calibration and validation results. In this paper, the coastline crossing detection method is used to evaluate the geolocation errors of the NRCS data. Some coastal areas and islands where the NRCS data have large gradients are selected for the geolocation error analysis. The coastline inflection points can be identified on the basis that the radar backscatter of land and water exhibits a significant difference when the ocean surface wind speed is relatively low. The longitudes and latitudes of these points from different time periods are then fit to the global self-consistent hierarchical high-resolution shorelines map. The comparison results show that the overall distance error of HSCAT is approximately 2.59 km. This geolocation accuracy meets the instrument design requirements. The sources of geolocation errors are also analyzed in this paper in order to improve the geolocation accuracy.

The research constructed a retrieval algorithm of routine wind fields for microwave scatterometer onboard HY-2A (HY-2A/SACT). To prepare the sigma0 measurements for conducting wind vectors retrieval, the time ordered L1B product was regrouped to the sub-track aligned wind vector cells (WVCs). Besides, the authors utilized an extension land and ice mask to simplify the surface flag process. The maximum-likelihood estimator (MLE) was applied to retrieve wind vector for each WVC with the NSCAT-2 as geophysical model function (GMF). Furthermore, to greatly improve the ambiguity removal skill, the research used circular median filter to remove the ambiguities, and the NCEP wind field as a background to re-initialized wind field comprising of ambiguous wind vectors. Wind vectors observed by HY-2A/SACT were evaluated by comparing with NDBC buoy observations. The RMS difference for wind speed was less than 2 m/s or 10%; while the RMS difference for wind direction was less than 20°comparing with wind direction. This result showed that the wind products provided by HY-2A/SCAT are able to meet the requirements of science and routine meteo users.