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Earth-based repeat-pass synthetic aperture radar (SAR) interferometry (InSAR) is a powerful tool to obtain the high-precision lunar terrain and deformation information, due to the short revisit period as well as the all-weather, long-time, and large-coverage characteristics of radar lunar observation. In this article, the baseline formation mechanism is investigated. Theoretical analyses show that the interferometric baselines mainly come from the lunar libration; however, the lunar libration may also result in a significant change of baselines and further lead to serious geometric decorrelation. To address this problem and ensure the Earth-based repeat-pass InSAR of the Moon, the precise relative motion model between the radar and the lunar target, considering lunar libration, is established, and the subradar point (SRP) wagging phenomenon is analyzed. Then, to evaluate the effects of SRP wagging on InSAR coherence, a geometric decorrelation model based on azimuth angle and incident angle is proposed. Based on that, the spatial–temporal baseline for Earth-based repeat-pass InSAR of the Moon is analyzed based on numerical simulation. Results show that the temporal baseline has obvious periodicity with a cycle of about 27 days. When the temporal baseline is an integral multiple of 27, the spatial baseline usually has the minimum value and the geometric decorrelation effect is relatively slight. Moreover, using the geometric decorrelation criteria, we examine the effects of radar frequency, position, and target location on the quantity of viable interferometric pairs, which has guiding significance for the selection of radar system parameters, radar position, and lunar target area. [ABSTRACT FROM AUTHOR]

It is challenging to estimate satellite targets’ absolute attitude and size with limited observational data. This article proposes an innovative way to jointly estimate satellite targets’ absolute attitude and size in the 3-D stable coordinates based on inverse synthetic aperture radar (ISAR) image interpretation with only one image. By taking advantage of the rectangular solar panels commonly equipped on satellites, this article extracts solar panel’s principal components, line features, and phase features of single ISAR imagery with principal component analysis (PCA), radon transform (RT), and minimum-entropy (ME)-based autofocus method, respectively. The projection relationship between these features and the absolute attitude and size of the satellite are established separately. Through multi-features fusion, a joint parameter estimation optimization function is established. This optimization is solved iteratively by the quasi-Newton method. The attitude and size parameters can be estimated simultaneously and rapidly, realizing the satellite state estimation under limited observation data. The excellent performance of the proposed algorithm is verified through different experiments. [ABSTRACT FROM AUTHOR]

Due to the small size of foreign object debris (FOD) and varied complex weather conditions, the detection of FOD on airport runways is a great challenge. Radar is an important method for detecting FOD targets. However, almost all the existing systems are based on real apertures, which have disadvantages such as low azimuth resolution and susceptibility to rain interference. Here, an innovative FOD detection radar system based on arc-scanning synthetic aperture radar (AS-SAR) technology, the AS-SAR based FOD detection system (AS-FODR), achieves omnidirectional coverage with a very high azimuth resolution and the suppression of flicker clutter, such as rain drops in severe weather. According to the radar imaging simulation of a scene under rainy conditions and the information processing analysis of field experiments, a prototype system was built, and an efficient data process flow was proposed. In short, a one centimeter FOD target was detected on the runway more than 250 m away, proving that the use of AS-FODR is feasible and effective. [ABSTRACT FROM AUTHOR]

An intrinsic challenge in the geophysical interpretation of low-frequency synthetic aperture radar (SAR) imagery of semitransparent media, such as ice sheets, is the position ambiguity of the scattering structures within the glacial volume. Commonly tackled by applying interferometric and tomographic techniques, their spaceborne implementation exhibits by orders higher complexity compared to missions relying on single SAR images, making them cost expensive or, in the context of planetary missions, even impossible due to limited navigation capability. Besides, even these sophisticated techniques are commonly biased due to inaccurate permittivity estimates, leading to geometric distortions up to several meters. We present a novel inversion procedure to estimate volume parameters of ice sheets, namely, the depth of the scattering layer within the glacial volume and the dielectric permittivity of the ice, based on single-image single-polarization SAR acquisitions. The information is inherent in the processed SAR data as phase errors on the azimuth signals resulting from uncompensated nonlinear propagation of the radar echoes through ice. We suggest a local map-drift autofocus approach to quantify and spatially resolve the phase errors and an inversion model to relate them to the penetration depth and permittivity. Testing the proposed technique using P-band SAR data acquired using DLR’s airborne sensor F-SAR during the ARCTIC15 campaign in Greenland shows promising results and good agreement with tomographic products of the analyzed test site. [ABSTRACT FROM AUTHOR]

Radio spectrum bands allocated to spaceborne synthetic aperture radar (SAR) imagery are shared by multiple missions. In practical radio spectrum environments, these bands are also used by some ground radars, e.g., C-band weather radar. Due to this fact, radio frequency interference (RFI) may occur for a spaceborne SAR when its received signals contain the transmitted waveforms from another SAR or radar operating at the same frequency band. This particular class of RFI is usually linear-frequency-modulation (LFM) signals, which can cause bright radiometric artifacts in focused SAR images. Most existing signal processing approaches designed for addressing this problem belong to the class of preprocessing methods, which removes RFI in level-0 raw radar data before SAR focusing. In this article, we propose a postprocessing kernel—2-D SPECtral ANalysis (2-D SPECAN) filter, for removing the class of LFM RFI in level-1 SLC images. The filtering consists of three main steps: Step 1: focus LFM RFI artifacts in SLC images as point-like responses in the spectral domain via 2-D SPECAN; Step 2: perform 2-D notch filtering in the spectral domain to remove the most contribution of the RFI responses; and Step 3: transform the filtered spectrum back into the SLC image domain using the inverse operation of the 2-D SPECAN. For computation efficiency, we design a simplified processing flow and adopt a blockwise processing strategy. Experiments with several Sentinel-1 SLC images demonstrate that severe RFI artifacts in SLC images can be removed significantly by the proposed method. [ABSTRACT FROM AUTHOR]

This article develops and examines methods for the production of real-world, very high-resolution imagery using a high-frequency drone-borne synthetic aperture radar (SAR) operating at short ranges. The significance of motion errors which lead to space-invariant/variant phase errors is discussed. Subsequently, an imaging algorithm capable of handling these errors is proposed and presented. The validity of the approach is tested through both simulation and experiment. We present novel short-range, fine-resolution imagery (less than 2 cm in cross-range) of an extended target area generated using a low-cost, drone-borne vehicular frequency-modulated continuous-wave (FMCW) radar operating at 77 GHz, without using a dedicated inertial navigation system (INS) or Global Positioning System (GPS). [ABSTRACT FROM AUTHOR]

Marine X-band radar has been suggested to be capable of monitoring significant wave heights in both offshore and open sea areas. In contrast to studies on offshore radar, significant wave height estimations from coastal radar images, which exhibit complicated radar backscattering features, have received little attention. This study proposes a method for retrieving the significant wave height from coastal areas that are often influenced by nononshore winds. The square root of the signal-to-noise ratio in radar images has been widely applied to estimate the significant wave height. However, nononshore wind cases show a poor correlation between the square root of the signal-to-noise ratio and the in situ significant wave height. In addition, the spectral shapes from radar images in nononshore wind cases are very different from those in onshore wind cases. To improve the significant wave height estimations from coastal radar images, we implement an artificial neural network algorithm. After training and testing the algorithm, we confirm that the estimated significant wave heights are more reliable for both onshore and nononshore wind cases if the square root of the signal-to-noise ratio, power from nearshore radar subimages, and in situ wind components are included in the input layer of the neural network. [ABSTRACT FROM AUTHOR]

Spaceborne multistatic synthetic aperture radar (M-SAR) has extensive applications, including multiangle imaging, digital beamforming (DBF) and cross- and along-track interferometry. However, it is difficult for classical satellite formations to meet the multimission (e.g., cross-track interferometry and along-track interferometry, i.e., XTI and ATI) requirements of M-SAR concurrently. Therefore, superpolyhedron (SP), an innovative satellite formation based on the dual-helix and pendulum formations, is proposed to maximize the coverage ratio of the effective cross- and along-track interferometric baselines at the same time. A method of constructing the SP formation is detailed. The method is a three-step procedure, in which the first two steps aim at obtaining an initial formation via exploiting the geometry of the formation dynamics; the last step solves an optimization problem. Then, the design of a supertetrahedron (ST) formation, a special case of the SP formation, is investigated as a numerical example. The merit of SP formation is represented as the coverage ratios of effective cross- and along-track interferometric baselines. The result is compared with those of the classical satellite formations. It shows that only the coverage ratios of the ST formation are greater than 70% simultaneously. Therefore, the ST formation can realize both effective XTI and ATI. It implies that the SP formation has the potential to be used in future spaceborne M-SAR interferometry. [ABSTRACT FROM AUTHOR]

Ground-based synthetic aperture radar (GBSAR) systems are widely used for monitoring slopes, especially in quarries and open pits. Unfortunately, the movement of the machinery (cranes, trucks, shovels, and excavators) in the radar field of view often prevents to correctly focus large circular sections of the radar images, producing a characteristic artifact, often named “blurring.” Therefore, the aim of this article is to propose both an acquisition modality and an image processing technique able to mitigate the blurring due to moving clutter. The proposed acquisition modality (named “free-running” or “on-the-fly”) allows to filter out the high-frequency clutter, which is often noticeable in GBSAR images, but it is not effective with low-frequency clutter caused by slow movement of machinery like heavy trucks or large cranes. For this reason, the authors propose even a suitable processing method that can be used in combination with high-frequency sampling. The application of these two methods has been proved to be very effective in realistic quarry scenario. [ABSTRACT FROM AUTHOR]

In the context of spaceborne synthetic aperture radar (SAR) imaging, high resolution and wide swath are inherently conflicting requirements. These may, however, be simultaneously satisfied by advanced imaging modes with multichannel architectures in elevation and/or azimuth. This article elaborates on a new mode based on multiple elevation beams and a simple pulse repetition interval (PRI) variation scheme which allows high-resolution wide-swath imaging. It is shown to use the illumination time more efficiently than ScanSAR and yet to be simpler than staggered SAR. Good SAR imaging performance is achieved with a rather compact antenna design. The proposed imaging mode is suitable for spaceborne SAR systems with planar and reflector antennas. In order to improve the imaging performance, a reflector antenna architecture with a multichannel feed in both elevation and azimuth is considered. [ABSTRACT FROM AUTHOR]

A new method for separating convective, intermediate, and stratiform rainfall based on the wavelet scale analysis is presented. A robust classification has resulted from the two choices: 1) the transformation of radar reflectivities to rain rates and 2) the inclusion of the intermediate class. The method uses á trous wavelet transform (WT) to separate heterogeneous convective features from the relatively smooth stratiform field. The heterogeneous region is further split into a convective class for the large wavelet coefficients and an intermediate class for the small wavelet coefficients. There is an improvement in the estimation of convective-stratiform fraction and frequency distribution of rain rates in comparison to the well-established Steiner method. The new method correctly reclassified a significant fraction of Steiner’s convective regions, which had low mean rain rates of 5.5 $\mathrm {mm}\cdot \mathrm {h}^{-1}$ , as stratiform regions. Similarly, Steiner’s stratiform regions, which had high mean rain rates of $15\,\,\mathrm {mm}\cdot \mathrm {h}^{-1}$ , are classified as convective by the wavelet method. The method is tested and evaluated over the Indian region during monsoon, and it is found that the three wavelet classes have distinct raindrop-size distributions. [ABSTRACT FROM AUTHOR]

This paper presents a novel automatic real-time remote sensing algorithm that uses radar images and global positioning satellite system measurements to estimate the ice-drift velocity vector in a region around a free-floating and potentially moving vessel. It is motivated by the low image frequency of satellite systems together with the inconvenience of deploying and retrieving ice trackers (beacons) on the ice. The algorithm combines radar image processing with two Kalman filters to produce the estimated local drift vector decoupled from the ship motion. The proposed design is verified using a full-scale data set from an ice management operation north of Svalbard in 2015. It is found that the performance of the algorithm is comparable with that of trackers on the ice. [ABSTRACT FROM AUTHOR]

State-of-the-art and future spaceborne synthetic aperture radar (SAR) systems increasingly often face the requirement of providing high-resolution images with reduced revisit times, requiring coverage of wide swaths. Since these are contradicting drivers in terms of system design, different alternatives for high-resolution wide-swath SAR imaging have been investigated, relying on digital beamforming and the use of multiple receiver channels, both in elevation and azimuth dimensions. In this context, staggered SAR, which operates with a pulse repetition frequency (PRF) variation, using a single channel in azimuth proves itself as a promising alternative for covering wide continuous swaths with moderate azimuth resolution, whereas the use of multiple azimuth receiver channels bears the potential of improving the azimuth resolution over a given swath, but has yet only been applied to systems with a fixed PRF. This paper introduces and analyzes in detail processing techniques suitable for the combination of these techniques, leading to novel multichannel staggered SAR imaging modes with the potential for very fine azimuth resolution over ultra-wide swaths. A system concept with 2-m azimuth resolution over a 400-km swath in quad-pol is provided as an example. [ABSTRACT FROM AUTHOR]

This paper presents the first experimental demonstration of the virtual bandwidth synthetic aperture radar (VB-SAR) imaging scheme. VB-SAR is a newly developed subsurface imaging technique which, in stark contrast to traditional close proximity ground penetrating radar schemes, promises imaging from remote standoff platforms such as aircraft and satellites. It specifically exploits the differential interferometric SAR (DInSAR) phase history of a radar wave within a drying soil volume to generate high-resolution vertical maps of the scattering through the soil volume. For this study, a stack of C-band vertically polarized DInSAR images of a sandy soil containing a buried target was collected in the laboratory while the soil moisture was varied--first during controlled water addition, and then during subsequent drying. The wetting image set established the moisture-phase relationship for the soil, which was then applied to the drying DInSAR image set using the VB-SAR scheme. This allowed retrieval of high-resolution VB-SAR imagery with a vertical discrimination of 0.04 m from a stack of 1-m vertical resolution DInSAR images. This paper unequivocally shows that the basic principles of the VB-SAR technique are valid and opens the door to further investigation of this promising technique. [ABSTRACT FROM AUTHOR]

The most intuitive way to extract depth information from remote sensing images is stereogrammetry, in which a digital elevation model (DEM) is achieved by computing stereoscopic radar images. When only the amplitude of the radar images is considered, this computation is called radargrammetry. The main idea of which is to match stereopair radar images in order to create a disparity map from one image to the other and, finally, to compute the elevation. Therein, we present our studies on the extraction of 3-D information from radar images. We examine a way to produce a DEM of a challenging area of the French Alps. The central issue of this paper concerns improvements for radargrammetric synthetic aperture radar image processing for high-relief reconstruction, and we focus on the matching step, which is one of the most important points of the radargrammetric processing. Thus, we propose original methods using different correlation windows. On the one hand, we take the advantages of a multiwindow approach to combine relevant information by multiplying the correlation surfaces obtained for each correlation window size during the matching operation. On the other hand, the second improvement is based on the expansion of windows on foreshortened areas, particularly because of the side-looking radar view. These methods allow us to achieve reliable image matching and to improve the accuracy of the DEM. [ABSTRACT FROM AUTHOR]