In robotic operation, asymmetric tasks requiring dual-arm cooperation are the highly challenging research direction. Autonomous operation generally has a low success rate or poor generalization because of its excessive dependence on the accuracy of sub-goals from asymmetric tasks. Although teleoperation can significantly improve the performances above, during operation, the operators are prone to neglect crucial intermediate sub-goals that are conducive to fine-grained dual-arm cooperation. Therefore, we propose a dual-arm shared control framework which firstly introduces the Sub-goal Generation module to sufficiently concentrate on the intermediate states, thus improving the ability of fine-grained dual-arm cooperation and reducing the adjustment quantity during robotic asymmetric task operation. Also, we integrate the Trajectory Prediction module that computes the future trajectory based on the historical movement information to enhance the robot motion smoothness. Finally, through dynamic combination of Sub-goal Generation module, Trajectory Prediction module and operator movement in the shared control framework, we effectively decrease the sensitivity to the accuracy of sub-goals, thus significantly improving the success rate. In simulation, we conduct the comparative experiments with autonomous operation and teleoperation on four common asymmetric tasks to validate the advantages of our shared control framework. The effect of each element in our framework is verified by ablation study. Certainly, our shared control framework can also be applied in real-world scenario.

In recent years, multi-sensor fusion has gained significant attention from researchers and is used extensively in simultaneous localization and mapping (SLAM) applications, such as visual-inertial odometry (VIO). This technology primarily utilizes visual and odometry measurements for unmanned aerial vehicles (UAVs) to estimate their position, orientation, and environment. However, in most previous works, the input error data of sensors in the system were considered independent. To improve system precision and fully utilize sensor data, a new method called Multi-State Constraint Kalman Filter with NearSAC (MSCKF-NearSAC), based on the MSCKF, is proposed. This method eliminates outliers by limiting the range of selected points, which significantly improves the success rate of feature point matching in the front-end. Furthermore, the MSCKF-ZNN method is proposed for the back-end, and combines zeroing neural network (ZNN) (originated from the Hopfield-type neural network) and error state, resulting in an exponentially converging output trajectory error, thus improving the trajectory precision of the SLAM system. The proposed algorithms, MSCKF-NearSAC and MSCKF-ZNN, are used in the excellent work of the stereo multi-state constraint Kalman filter system (S-MSCKF). A plethora of comparison experiments, utilizing precise measurement and calibration techniques, are conducted on open-source datasets and real-world environments. Experimental results demonstrate that the introduced approach exhibits higher stability in contrast to other algorithms.

The first C- and Ku-band dual-frequency scatterometer (WindRAD) onboard the Chinese FengYun-3E (FY-3E) satellite was successfully launched in July 2021. The WindRAD scatterometer uses an advanced fan-beam conical scanning mechanism to acquire wind vector data of global ocean surfaces and other geophysical parameters through backscattering measurements of the Earth. This article provides an introduction to the WindRAD instrument, an overview of the data preprocessing, and assessment of WindRAD measurements. The numerical weather prediction-based ocean calibration (NOC) approach, natural targets, and cross-calibration against the Ku-band scatterometer onboard the HY-2B satellite based on collocated backscatter measurements, were used to validate WindRAD backscatter results. The evaluation results revealed that the performance of the WindRAD data is generally in good agreement with other scatterometer data currently in use, while WindRAD backscatter data may contain nonlinear calibration issues that require further investigation. WindRAD has the ability to provide high-quality global backscattering measurements, which can be used for the inversion of various geophysical parameters and assimilation applications.

Scatterometer wind data are critical for meteorological and oceanographic applications. The differences between scatterometer winds and buoy reference winds largely depend on the type of reference wind used in the fitting of the scatterometer’s geophysical model function (GMF). This study evaluates scatterometer winds using advanced buoy reference winds, specifically stress-equivalent winds (U10S), and equivalent-neutral winds (U10N). We utilized HSCAT-B scatterometer wind products retrieved using both NSCAT-4 and NSCAT-5 GMFs). NSCAT-4 winds were corrected to stress-equivalent winds, and these scatterometer winds were compared with various buoy reference winds, including true buoy winds, stress-equivalent winds, and equivalent-neutral winds. The results show that in extratropical regions, stress-equivalent winds provided a closer match to scatterometer winds, while in tropical regions, equivalent-neutral winds exhibited smaller errors. Scatterometer winds derived from the NSCAT-5 GMF demonstrated superior consistency with buoy reference winds, further reducing wind speed biases compared to NSCAT-4. An extended triple collocation (ETC) analysis was conducted to address the uncertainties arising from differences in spatial resolution between scatterometer and buoy measurements. The findings emphasize the importance of using appropriate wind correction methods for scatterometer wind validation, particularly in regions with significant atmospheric variability.

Seven satellite scatterometers, namely, the C-band MetOp-A/Advanced Scatterometer (ASCAT), MetOp-B/ASCAT, MetOp-C/ASCAT, Ku-band HY-2A/SCAT, HY-2B/SCAT, Chinese-French Oceanography Satellite (CFOSAT)/SCAT, and SCATSAT-1/OceanSat Satellite Scatterometer (OSCAT2), are operating in orbits. These satellites make a high-frequency observation of sea surface winds possible, particularly at high latitudes. This work analyzes the passing time, passing frequency, coverage of these seven scatterometers, and the quality of high-latitude surface wind products. All the scatterometer wind products were reproduced with the same processing procedures, in terms of backscatter calibration, wind retrieval, numerical weather prediction (NWP) wind, and quality control. The target region (74–78 N, 167°–171 W) was chosen to analyze the passing frequency. A spatial grid of$0.25^{\circ } \times 0$.25° in the range of 60° N–88° N was chosen to analyze the spatial coverage of the scatterometers. The results show that more than 40 observation times can be provided daily by all the seven scatterometers; however, there is a 9-h gap between UTC 9:00 and UTC 18:00, suggesting that international cooperation is needed for optimizing the equatorial crossing time in future scatterometer missions, such that an optimal virtual scatterometer constellation can be achieved. The scatterometer winds are compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) winds, and with each other. The comparison results confirmed noticeable wind speed biases due to sea surface temperature (SST) in all Ku-band scatterometer winds with respect to the C-band scatterometer and ERA5 winds.

The total mean square slope (mss) of large-scale (in comparison with the scale of radar wavelengths) ocean waves can describe the roughness of the ocean surface. This important parameter has found many applications and can be determined by the dependence of large-scale mss on azimuthal angles. The Surface Waves Investigation and Monitoring instrument onboard the China France Oceanography Satellite (CFOSAT) can provide a two-dimensional (2D) normalized backscattering radar cross section (NRCS) for 2D global ocean-surface wave detection. In this paper, the 2D NRCS is used to calculate the total large-scale mss via two methods. The first method is constructed from regression, while the second scheme is derived from a three-solution method. Finally, the total large-scale mss are calculated using these methods, and the map of the distribution of the global total mss is presented for the first time. Our results show that the two sources of total large-scale mss obtained are consistent with each other. CFOSAT can provide a 2D total large-scale mss map and be used as a new data resource for global applications.

Sea surface winds derived from the spaceborne rotating pencil-beam scatterometers, such as the current Chinese Haiyang-2 (HY-2) scatterometers and the Indian SCATSAT-1 scatterometer, are used in a wide range of atmospheric and oceanic applications. One key problem of the pencil-beam scatterometers is the relatively low wind quality in the nadir region, due to the poor azimuth diversity of the nadir-track observations. This article proposes to include the altimeter backscatter measurements in the wind inversion to improve the retrieved wind quality in the nadir region of HY-2B scatterometer (HSCAT). First, empirical model functions are developed to relate the C- and Ku-band altimeter backscatters to the neutral surface winds at 10-m height. Subsequently, the maximum likelihood estimator, which is commonly used to perform wind inversion for satellite scatterometers, is adapted to retrieve winds with simultaneous scatterometer and altimeter measurements. The significance of altimeter measurements in the combined wind inversion is addressed by comparing the cost functions of the combined scatterometer/altimeter wind retrieval and the nominal scatterometer inversion. The experimental results are eventually validated using moored buoy winds and the European Centre for Medium-range Weather Forecasting (ECMWF) model winds, indicating that the inclusion of altimeter backscatters has a positive impact on the wind quality over the HSCAT nadir region. Finally, the potential approaches to further improve the combined scatterometer and altimeter wind inversion are summarized.

In the context of the ocean surface vector wind virtual constellation, the combined wind products from the ongoing operational scatterometers will unprecedentedly increase the spatial and temporal coverage of remote sensing winds, and ease the development of gap-free sea surface wind data of high quality and high spatial/temporal resolution for a variety of applications, including a better marine forecasting and monitoring. However, systematic differences do exist in the wind products derived from different scatterometers, which may result in detrimental impacts in these applications. Therefore, the difference between the retrieved winds from C- and Ku-band scatterometers is further explored in this paper. In particular, sea surface temperature (SST) effects, quality control and high wind sensitivity of both C- and Ku-band scatterometers are analyzed, with the objective to better understand the sources of the inconsistencies, and to provide the wind users with support and recommendations in terms of wind applications.

China has launched five satellites scatterometers, namely, the Haiyang-2A scatterometer (HSCAT-A), Haiyang-2B scatterometer (HSCAT-B), China-French Satellite scatterometer (CSCAT), Haiyang-2C scatterometer (HSCAT-C) and Haiyang-2D scatterometer (HSCAT-D). This article aims to introduce calibration and validation methods for products of these Chinese scatterometers. Active transponders are used for post-launch absolute calibration, while the Numerical Weather Prediction Ocean Calibration (NOC) method is applied for post-launch relative calibration for the sigma0 observed in these Chinese scatterometers. As a complement to NOC, a natural terrestrial target of the Amazon rainforest is chosen as a calibration site. A long time-series analysis of sigma0 over the Amazon rainforest is also used to assess the temporal stability. To validate the winds from these Chinese scatterometers, the HSCAT-A/B/C and CSCAT winds are compared to in-situ buoy, ECMWF and ASCAT winds, respectively. The comparison results show that all these four Chinese scatterometers winds are comparable and meet the mission requirements, i.e., the error is less than 2 m/s or 10% in terms of the speed and 20° in terms of the direction. HSCAT-B and HSCAT-C perform better than HSCAT-A and show similar qualities to that of ASCAT-A.

The first rotating fan beam scatterometer onboard China-France Oceanography Satellite (CFOSAT) was successfully launched on October 29, 2018. CFOSAT SCATterometer (CSCAT) is dedicated to the monitoring of sea surface wind vectors but also provides valuable data for the applications over land and Polar Regions. This article provides an overview of the relevant procedures of CSCAT data processing, including onboard signal processing and operational ground processing. Then a post-launch analysis is carried out to evaluate the first results of CSCAT L1 and L2 products. It shows that the CSCAT instrument is generally stable in terms of noise measurements and internal calibration, unless there is any important change in the system configuration. Specifically, the CSCAT backscatter (σθ) precision and wind quality are studied using a set of collocated ancillary data. The σθprecision degrades as wind speed decreases, and it is relatively low at high incidence angles (e.g., θ >46°). In particular, backscatter estimation of the horizontally polarized beam should be further improved by correcting the noise subtraction factor. The retrieved CSCAT winds are in good agreement with the European Centre for Medium Range Weather Forecasts (ECMWF) winds, the Advanced Scatterometer (ASCAT) winds, as well as the buoy winds. However, due to unresolved calibration and interbeam consistency problems, the wind quality degrades remarkably for the out-swath and the nadir-region wind vector cells, implying that the σθcalibration should be improved in the future updates.

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.

The sea surface winds from the CFOSAT scatterometer (CFOSCAT) are retrieved using the maximum likelihood estimator, and the inversion residual is used to sort the good-quality winds from the poor-quality ones. A two-dimensional variational analysis ambiguity removal (2DVAR) scheme is then applied over the CFOSCAT swath such that a unique wind field is selected from the available local scatterometer wind vector ambiguities. The preliminary results of CFOSCAT Level 2 (L2) processing show that the retrieved wind speed is overestimated under low-wind conditions (w15 m/s). Moreover, the inversion residual for the sweet swath (where there are more than 10 views) is generally higher than that for the nadir/outer swath. These imply that observations with different geometries (views) at the same WVC are inconsistent with respect to the geophysical model function, and thus a comprehensive calibration is highly demanded. A more detailed assessment of the CFOSCAT wind quality will be carried out after calibration and validation campaign.

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 China-France Oceanography Satellite (CFOSAT) to be launched in October 2018 will carry two innovative payloads, i.e., the surface wave investigation and monitoring instrument and the rotating fan-beam scatterometer [CFOSAT scatterometer (CFOSCAT)]. Both instruments, operated in Ku-band microwave frequency, are dedicated to the measurement of sea surface wave spectra and wind vectors, respectively. This paper provides an overview of the system definition and characteristics of the CFOSCAT instrument. A prelaunch analysis is carried out to estimate the scatterometer backscatter and wind quality based on the developed CFOSCAT simulator prototype. The overall simulation includes two parts: first, a forward model is developed to simulate the ocean backscatter signals, accounting for both instrument and geophysical noise. Second, a wind inversion processor is used to retrieve wind vectors from the outputs of the forward model. The benefits and challenges of the novel observing geometries are addressed in terms of the CFOSCAT wind retrieval. The simulations show that the backscatter accuracy and the retrieved wind quality of CFOSCAT are quite promising and meet the CFOSAT mission requirements.

The Ku-band rotating fan-beam scatterometer (RFSCAT) onboard the China-France Oceanography Satellite (CFOSAT) is dedicated to the measurement of sea surface wind vectors. The flight model of RFSCAT has been assembled and tested, and the data processing algorithms have been developed. This paper provides an overview of the design and characteristics of RFSCAT instrument, and then a prelaunch analysis is carried out to estimate the scatterometer backscatter and wind accuracy. The overall study includes two parts: first, a forward model is developed to simulate the ocean backscatter signals under certain wind conditions; second, a wind inversion processor is used to retrieve sea surface wind vectors from the outputs of the forward model. Simulations show that the backscatter accuracy and the retrieved wind quality of RFSCAT are quite promising and meet the scientific requirements of the mission.

Recent developments on the wind geophysical model function (GMF) of Ku-band scatterometers include a sea surface temperature (SST) dependent term. It has been found that the SST effects on the radar backscatter are wind speed dependent and more pronounced in vertical polarization (VV) than in horizontal polarisation (HH) at higher incidence angles, and are mainly relevant at radar wavelengths smaller than C-band. The new Ku-band GMF, NSCAT-5, is developed based on a physical model and RapidScat radar backscatter measurements, which are only available at two incidence angles, i.e., 48.8° and 55.2°, for HH and VV beams, respectively. The objective of this paper is to verify the NSCAT-5 GMF at similar incidence angles, using data from the scatterometer onboard Indian SCATSat-1 satellite, which operates at 49.1° (HH) and 57.9° (VV) incidence angles. First, the SCATSat-l backscatter sensitivity to sea surface wind and SST is assessed using the C-band Advance Scatterometer (ASCAT) winds as reference. Second, the approach used to derive the NSCAT-5 GMF for RapidScat is adapted to derive a SST-dependent GMF for SCATSat-l. The new GMF will be used to consolidate the current NSCAT-5 model, and then evaluated for SCATSat-l wind retrieval.

Closely collocated C and Ku band scatterometer winds are investigated and significant differences occur depending on sea surface temperature (SST). C-band scatterometer winds do not show any significant SST effect against independent wind references, but Ku-band scatterometer winds show a clear SST-dependent effect, but varying as a function of wind speed. Both statistical and physical analyses of these effects are presented.