Multi-Layer Overlapped Subaperture Algorithm for Extremely-High-Squint High-Resolution Wide-Swath SAR Imaging with Continuously Time-Varying Radar Parameters

Extremely-high-squint (EHS) geometry of the traditional constant-parameter synthetic aperture radar (SAR) induces non-orthogonal wavenumber spectrum and hence the distortion of point spread function (PSF) in focused images. The method invented to overcome this problem is referred to as new-concept parameter-adjusting SAR. It corrects the PSF distortion by adjusting radar parameters, such as carrier frequency and chirp rate, based on instant data acquisition geometry. In this case, the characteristic of signal is quite different from the constant-parameter SAR and therefore, the traditional imaging algorithms cannot be directly applied for parameter-adjusting SAR imaging. However, the existing imaging algorithm for EHS parameter-adjusting SAR suffers from insufficient accuracy if a high-resolution wide-swath (HRWS) performance is required. Thus, this paper proposes a multi-layer overlapped subaperture algorithm (ML-OSA) for EHS HRWS parameter-adjusting SAR imaging with three main contributions: First, a more accurate signal model with time-varying radar parameters in high-squint geometry is derived. Second, phase errors are compensated with much higher accuracy by implementing multiple layers of coarse-to-fine spatially variant filters. Third, the analytical swath limit of the ML-OSA is derived by considering both the residual errors of signal model and phase compensations. The presented approach is validated via both the point- and extended-target computer simulations.

A Novel Imaging Algorithm for High-Resolution Wide-Swath Space-Borne SAR Based on a Spatial-Variant Equivalent Squint Range Model

High-Resolution Wide-Swath (HRWS) is an important development direction of space-borne Synthetic Aperture Radar (SAR). The two-dimensional spatial variation of the Doppler parameters is the most significant characteristic of the sliding spotlight space-borne SAR system under the requirements of HRWS. Therefore, the compensation of the two-dimensional spatial variation is the most challenging problem faced in the imaging of HRWS situations. The compensatory approach is then proposed to address this problem in this paper. The spatial distribution of the Doppler parameters for the HRWS space-borne SAR data in the sliding spotlight working mode is firstly analyzed, based on which a Spatial-Variant Equivalent Slant Range Model (SV-ESRM) is put forward to accurately formulate the range history for the distributed target. By introducing an azimuth-varying term, the SV-ESRM can precisely describe the range history for not only central targets but also marginal targets, which is more adaptive to the HRWS space-borne SAR requirements. Based on the SV-ESRM, a Modified Hybrid Correlation Algorithm (MHCA) for HRWS space-borne SAR imaging is derived to focus the full-scene data on one single imaging processing. A Doppler phase perturbation incorporated with the sub-aperture method is firstly performed to eliminate the azimuth variation of the Doppler parameters and remove the Doppler spectrum aliasing. Then, an advanced hybrid correlation is employed to achieve the precise differential Range Cell Migration (RCM) correction and Doppler phase compensation. A range phase perturbation method is also utilized to eliminate the range profile defocusing caused by range-azimuth coupling for marginal targets. Finally, a de-rotation processing is performed to remove the azimuth aliasing and the residual azimuth-variance and obtain the precisely focused SAR image. Simulation shows that the SAR echoes for a 20 km × 20 km scene with a 0.25 m resolution in both the range and azimuth directions could be focused precisely via one single imaging processing, which validates the feasibility of the proposed algorithm.

Intensional Gaps: Relating veridicality, factivity, doxasticity, bouleticity, and neg-raising

We investigate which patterns of lexically triggered doxastic, bouletic, neg(ation)-raising, and veridicality inferences are (un)attested across clause-embedding verbs in English. To carry out this investigation, we use a multiview mixed effects mixture model to discover the inference patterns captured in three lexicon-scale inference judgment datasets: two existing datasets, MegaVeridicality and MegaNegRaising, which capture veridicality and neg-raising inferences across a wide swath of the English clause-embedding lexicon, and a new dataset, MegaIntensionality, which similarly captures doxastic and bouletic inferences. We focus in particular on inference patterns that are correlated with morphosyntactic distribution, as determined by how well those patterns predict the acceptability judgments in the MegaAcceptability dataset. We find that there are 15 such patterns attested. Similarities among these patterns suggest the possibility of underlying lexical semantic components that give rise to them. We use principal component analysis to discover these components and suggest generalizations that can be derived from them.

Application of Advanced Land Observing Satellite 3 (ALOS-3) Data to Land Cover and Vegetation Mapping

Advanced Land Observing Satellite 3 (ALOS-3) is capable of observing global land areas with wide swath (4000 km along-track direction and 70 km cross-track direction) at high spatial resolution (panchromatic: 0.8m, multispectral: 3.2m). Maintenance and updating of Land Cover and Vegetation (LCV) information at national level is one of the major goals of the ALOS-3 mission. This paper presents the potential of simulated ALOS-3 images for the classification and mapping of LCV types. We simulated WorldView-3 images according to the configuration of the ALOS-3 satellite sensor and the ALOS-3 simulated (ALOS-3S) images were utilized for the classification and mapping of LCV types in two cool temperate ecosystems. This research dealt with classification and mapping of 17 classes in the Hakkoda site and 25 classes in the Zao site. We employed a Gradient Boosted Decision Tree (GBDT) classifier with 10-fold cross-validation method for assessing the potential of ALOS-3S images. In the Hakkoda site, we obtained overall accuracy, 0.811 and kappa coefficient, 0.798. In the Zao site, overall accuracy and kappa coefficient were 0.725 and 0.711 respectively. Regardless of limited temporal scenes available in the research, ALOS-3S images showed high potential (at least 0.711 kappa-coefficient) for the LCV classification. The availability of more temporal scenes from ALOS-3 satellite is expected for improved classification and mapping of LCV types in the future.

An Azimuth Signal-Reconstruction Method Based on Two-Step Projection Technology for Spaceborne Azimuth Multi-Channel High-Resolution and Wide-Swath SAR

Azimuth non-uniform signal-reconstruction is a critical step for azimuth multi-channel high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) data processing. However, the received non-uniform signal has noise in the actual azimuth multi-channel SAR (MCSAR) operation, which leads to the serious reduction in the signal-to-noise ratio (SNR) of the results processed by a traditional reconstruction algorithm. Aiming to address the problem of reducing the SNR of the traditional reconstruction algorithm in the reconstruction of non-uniform signal with noise, a novel signal-reconstruction algorithm based on two-step projection technology (TSPT) for the MCSAR system is proposed in this paper. The key part of the TSPT algorithm consists of a two-step projection. The first projection is to project the given signal into the selected intermediate subspace, spanned by the integer conversion of the compact support kernel function. This process generates a set of sparse equations, which can be solved efficiently by using the sparse equation solver. The second key projection is to project the first projection result into the subspace of the known sampled signal. The secondary projection can be achieved with a digital linear translation invariant (LSI) filter and generate a uniformly spaced signal. As a result, compared with the traditional azimuth MCSAR signal-reconstruction algorithm, the proposed algorithm can improve SNR and reduce the azimuth ambiguity-signal-ratio (AASR). The processing results of simulated data and real raw data verify the effectiveness of the proposed algorithm.

Assimilating realistically simulated wide-swath altimeter observations in a high-resolution shelf-seas forecasting system

The impact of assimilating simulated wide-swath altimetry observations from the upcoming Surface Water and Ocean Topography (SWOT) mission is assessed using observing system simulation experiments (OSSEs). These experiments use the Met Office 1.5 km resolution North West European Shelf analysis and forecasting system. In an effort to understand the importance of future work to account for correlated errors in the data assimilation scheme, we simulate SWOT observations with and without realistic correlated errors. These are assimilated in OSSEs along with simulated observations of the standard observing network, also with realistic errors added. It was found that while the assimilation of SWOT observations without correlated errors reduced the RMSE (root mean squared error) in sea surface height (SSH) and surface current speeds by up to 20 %, the inclusion of correlated errors in the observations degraded both the SSH and surface currents, introduced an erroneous increase in the mean surface currents and degraded the subsurface temperature and salinity. While restricting the SWOT data to the inner half of the swath and applying observation averaging with a 5 km radius negated most of the negative impacts, it also severely limited the positive impacts. To realise the full benefits in the prediction of the ocean mesoscale offered by wide-swath altimetry missions, it is crucial that methods to ameliorate the effects of correlated errors in the processing of the SWOT observations and account for the correlated errors in the assimilation are implemented.

Internal solitary waves propagation speed estimation in the northern-part of Lombok Strait observed by Sentinel-1 SAR and Himawari-8 images

Remotely sensed data, both Synthetic Aperture Radar (SAR) and optical sensors, significantly contribute to the study and understanding internal solitary wave (ISW) dynamics in the ocean. Pairs of SAR and optical sensors were analyzed to estimate the ISW propagation speed in the northern-part of Lombok Strait. ISW propagation speed estimation used an image from Sentinel-1 SAR and three image pairs of Himawari-8 on 29 October 2018 with a time difference of 409 minutes. Sentinel-1 wide-swath imagery (250 km x 400 km) from two adjacent scenes can provide information on multiple ISW packets evolution in the northern-part of Lombok Strait. ISW propagation speed estimation on Sentinel-1 SAR image using the simple estimation by measuring the interpacket distance and dividing by the semidiurnal tidal period. The high temporal resolution of the optical sensor from Himawari-8 can estimate the ISW propagation speed using two different approaches. ISW propagation speed estimation using the semidiurnal tidal period from Sentinel-1 and Himawari-8 showed almost similar values. Sentinel-1 estimation results are 2.69 m.s−1 (Lombok Strait) and 1.30 m.s−1 (northern-part area), Himawari-8 results are 2.52 m.s−1 (Lombok Strait) and 1.27 m.s−1 (northern-part area). ISW propagation speed variability in the northern-part of the Lombok Strait shown in this study.

Contribution of a constellation of two Wide-Swath Altimetry Missions to Global Ocean Analysis and Forecasting

Swath altimetry is likely to revolutionize our ability to monitor and forecast ocean dynamics. To meet the requirements of the EU Copernicus Marine Service, a constellation of two wide-swath altimeters is envisioned for the long-term (post-2030) evolution of the Copernicus Sentinel 3 topography mission. A series of Observing System Simulation Experiments is carried out to quantify the expected performances. The OSSEs use a state-of-the-art high resolution (1/12°) global ocean data assimilation system similar to the one used operationally by the Copernicus Marine Service. Flying a constellation of two wide-swath altimeters will provide a major improvement of our capabilities to monitor and forecast the oceans. Compared to the present situation with 3 nadir altimeters flying simultaneously, the Sea Surface Height analysis and 7-day forecast error will be globally reduced by about 50 %. With two wide-swath altimeters, the quality of Sea Surface Height 7-day forecasts is equivalent to the quality of SSH analysis errors from three nadir altimeters. Our understanding of ocean currents is also greatly improved (30 % improvements at the surface and 50 % at 300 m depth). The resolution capabilities will be drastically improved and will be closer to 100 km wavelength compared to about 250 km today. Flying a constellation of two wide-swath altimeters thus looks to be a very promising solution for the long-term evolution of the Sentinel 3 constellation and the Copernicus Marine Service.