Coherent multistatic radio imaging represents a pivotal opportunity for forthcoming wireless networks, which involves distributed nodes cooperating to achieve accurate sensing resolution and robustness. This paper delves into cooperative coherent imaging for vehicular radar networks. Herein, multiple radar-equipped vehicles cooperate to improve collective sensing capabilities and address the fundamental issue of distinguishing weak targets in close proximity to strong ones, a critical challenge for vulnerable road users’ protection. We prove the significant benefits of cooperative coherent imaging in the considered automotive scenario in terms of both probability of correct detection, evaluated considering several system parameters, as well as resolution capabilities, showcased by a dedicated experimental campaign wherein the collaboration between two vehicles enables the detection of the legs of a pedestrian close to a parked car. Moreover, as coherent processing of several sensors’ data requires very tight accuracy on clock synchronization and sensor’s positioning—referred to as phase synchronization—(such that to predict sensor-target distances up to a fraction of the carrier wavelength), we present a general three-step cooperative multistatic phase synchronization procedure, detailing the required information exchange among vehicles in the specific automotive radar context and assessing its feasibility and performance by hybrid Cramér-Rao bound.

This paper tackles two open problems concerning automotive Synthetic Aperture Radar (SAR): whether it is possible to develop a fast and efficient focusing routine and assess the effect of multipath on MIMO-SAR images. First, we present a processing technique that enables real-time imaging of the scene under observation. The idea is that the SAR image is already present in the Range-Angle-Velocity (RAV) data cube and must be extracted with a simple 3D interpolation. Unlike standard Doppler beam sharpening techniques, this processor is accurate since it handles range migration and phase curvature. For what concerns the multipath, instead, we introduce a simple yet effective approach to mitigate this issue, which significantly improves the robustness of SAR systems concerning multipath. To showcase the capabilities and potential of our proposed method, we conducted a comprehensive set of experiments utilizing simulated data. The results were not only able to demonstrate the enhancement of robustness of the SAR system in dealing with multipath but also highlighted the ability of our approach to deliver highly accurate and high-quality real-time imaging of the scene being surveyed.

This article discusses the effect of multipath in automotive radar imaging under different sensor configurations. The study is motivated by the fact that radar technologies are becoming indispensable in the automotive scenario. Many applications such as collision avoidance systems, assisted parking, and driving assistance systems take advantage of radar technologies to accomplish their task. However, one of the main concerns about automotive radars is the possibility of detecting false targets due to multiple signal reflections. In this article, we show how different sensor layouts experience multipath differently. In particular, we demonstrate that with multiple-input multiple-output (MIMO) radars, what really matters is the physical positions of the transmitting and receiving antennas. The monostatic/bistatic equivalent configurations cannot be used to design a system and to simulate an acquisition in the presence of a multipath. We also demonstrate how vehicle-based MIMO-synthetic aperture radar (MIMO-SAR) imaging can generate a bi-dimensional aperture which significantly reduces multipath effects in the focused image, avoiding the detection of false targets. All the theoretical analyses are supported by several simulations where different sensor layouts are tested, and the capability of MIMO-SAR to reject multipath is validated.

With the advent of self-driving vehicles, autonomous driving systems will have to rely on a vast number of heterogeneous sensors to perform dynamic perception of the surrounding environment. Synthetic Aperture Radar (SAR) systems increase the resolution of conventional mass-market radars by exploiting the vehicle’s ego-motion, requiring very accurate knowledge of the trajectory, usually not compatible with automotive-grade navigation systems. In this setting, radar data are typically used to refine the navigation-based trajectory estimation with so-calledautofocusalgorithms. Although widely used in remote sensing applications, where the timeliness of the imaging is not an issue, autofocus in automotive scenarios calls for simple yet effective processing options to enable real-time environment imaging. This paper aims at providing a comprehensive theoretical and experimental analysis of the autofocusrequirementsin typical automotive scenarios. We analytically derive the effects of navigation-induced trajectory estimation errors on SAR imaging, in terms of defocusing and wrong targets’ localization. Then, we propose a motion estimation and compensation workflow tailored to automotive applications, leveraging a set of stationary Ground Control Points (GCPs) in the low-resolution radar images (before SAR focusing). We theoretically discuss the impact of the GCPs position and focusing height on SAR imaging, highlighting common pitfalls and possible countermeasures. Finally, we show the effectiveness of the proposed technique employing experimental data gathered during open road campaign by a 77 GHz multiple-input multiple-output radar mounted in a forward-looking configuration.

Today, one of the biggest challenges faced in the intersection of the Deep Learning (DL) and synthetic aperture RADAR (SAR) domains is the scarcity of precisely annotated datasets suitable for properly training a supervised algorithm. This paper shows that it is possible to successfully exploit weak-labeled data instead of relying on manually annotated labels. In particular, we show how it is possible to train, with state-of-the-art performance, a deep model for the segmentation of water surfaces in SAR images from a weak-labeled dataset. Finally, we present examples of applications of the learned model to the segmentation of inland water bodies and floods.

Automated driving requires a huge number of on-board sensors to provide advanced functionalities, from parking assistance to emergency braking and environment mapping for target recognition/classification. While low-cost automotive-legacy radars are mostly used for target detection due to their limited angular resolution, vehicular Synthetic Aperture Radar (SAR) is emerging as a promising imaging solution, provided that the motion is known with high accuracy. This paper assesses the benefits of a navigation-augmented SAR system exploiting multiple on-board sensors, e.g., Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), odometers and steering angle sensors. The results confirm the potential of the proposed multi-sensor-aided SAR system to obtain centimeter-level accurate images of the driving scenario.

The present work presents a novel and robust method that exploits multi-temporal Sentinel-1 SAR data for land use classification. The method is built on an interferometric stack of multi-temporal Sentinel-1 SAR data and combines the intensity of backscattering, the short time interferometric coherence and the decorrelation time of scatterers. Promising preliminary results of land use classification and river corridor coverage are presented. The test case is located in the flat area of the Padana plains in west northern part of Italy. The proposed method is a novel, robust and all-conditions tool for improving unsupervised land use classification at large scale. In the future, this technique will be integrated with optical information for testing the potentiality offered to the classification of land-uses and river features.

In this paper we propose a strategy for phase calibrating repeat-pass Synthetic Aperture Radar (SAR) data for tomographic applications. The problem is tackled by observing that multi-baseline data provide equations enough to jointly estimate aircraft and target positions, up to a rototranslation of the coordinate system used for representing the imaged scene. Such a rototranslation is shown to correspond to the forward operator null space, which can be accounted for in order to project the results in the desired coordinate frame. Volumetric scatterers are treated by exploiting the Phase Linking algorithm, which allows to represent them as equivalent phase centers. Results are shown from synthetic data and real SAR data acquired over snow and ice.

The Italian Space Agency (ASI Agenzia Spaziale Italiana) funded 27 scientific projects in the framework of COSMO-SkyMed (CSK) program. A subset of them focused on the improvements of the quality and quantity of information which can be extracted from X-SAR data if integrated with other independent techniques (GPS, data and imagery in other bands and wavelengths). The paper summarizes the results obtained from same of these projects and, in particular, regarding: the use of GPS observations and Numerical Weather Models (NWM) to remove atmospheric artifacts from InSAR imagery so improving the CSK potentialities in the field of topographic mapping; the integration of SAR data in X, L and C bands to improve snow cover monitoring and glaciers detection; the use of X-SAR data to retrieve rain precipitation and its validation with C-band radar observations; the improvements of the focusing techniques.

Permanent Scatterer SAR Interferometry (PSInSAR) aims to identify coherent radar targets exhibiting high phase stability over the entire observation time period. These targets often correspond to point-wise, man-made objects widely available over a city, but less present in non-urban areas. To overcome the limits of PSInSAR, analysis of interferometric data-stacks should aim at extracting geophysical parameters not only from point-wise deterministic objects (i.e., PS), but also from distributed scatterers (DS). Rather than developing hybrid processing chains where two or more algorithms are applied to the same data-stack, and results are then combined, in this paper we introduce a new approach, SqueeSAR, to jointly process PS and DS, taking into account their different statistical behavior. As it will be shown, PS and DS can be jointly processed without the need for significant changes to the traditional PSInSAR processing chain and without the need to unwrap hundreds of interferograms, provided that the coherence matrix associated with each DS is properly “squeezed” to provide a vector of optimum (wrapped) phase values. Results on real SAR data, acquired over an Alpine area, challenging for any InSAR analysis, confirm the effectiveness of this new approach.

Synthetic Aperture Radar (SAR) and Sonar (SAS) systems provide high resolution reflectivity maps of the imaged scene by coherently combining the echoes collected along a virtual array of receivers. A peculiarity of SAS systems is that the echoes are often collected by moving a short real array of hydrophones to avoid range ambiguity. In this paper we present a modification of the standard wavenumber focusing algorithm widely used in SAR data processing to make it suitable for focusing bi-static SAS data. An autofocusing technique is then exploited to estimate and compensate for the deviation of the platform trajectory from the rectilinear one.

The permanent scatterers (PS) technique is able to estimate atmospheric artifacts that delay the SAR interferometric phase over pointwise targets. In this work, for the first time, the atmospheric phase screen (APS) estimated with ERS data is compared to the APS retrieved with ENVISAT data at 30' time delay. The goal of the comparison is to add new insights to the phase delay that affects InSAR measurements. Preliminary but interesting real data results have been obtained over the city of Milan.

In this work we present a methodology for developing a Permanent Scatterers (PS) analysis jointly exploiting data acquired from parallel orbits to estimate height and deformation trend of multi-angle urban targets. The methodology allows applying the PS technique also in areas where the number of ASAR acquisitions per single track would prevent to get reliable estimates. Preliminary experimental results achieved in the Shanghai test site confirm the promising potential of the proposed methodology.

This paper presents the results of a blind experiment that is performed using two pairs of dihedral reflectors. The aim of the experiment was to demonstrate that interferometric synthetic aperture radar (InSAR) measurements can indeed allow a displacement time series estimation with submillimeter accuracy (both in horizontal and vertical directions), provided that the data are properly processed and the impact ofin situas well as atmospheric effects is minimized. One pair of dihedral reflectors was moved a few millimeters between SAR acquisitions, in the vertical and east-west (EW) directions, and the ground truth was compared with the InSAR data. The experiment was designed to allow a multiplatform and multigeometry analysis, i.e., each reflector was carefully pointed in order to be visible in both Envisat and Radarsat acquisitions. Moreover, two pairs of reflectors were used to allow the combination of data gathered along ascending and descending orbits. The standard deviation of the error is 0.75 mm in the vertical direction and 0.58 mm in the horizontal (EW) direction. GPS data were also collected during this experiment in order to cross-check the SAR results

The application of the Permanent Scatterers (PS) Technique in multi-temporal data-sets, namely the identification and exploitation of sparse coherent targets, has shown that it is possible to estimate and remove interferometric phase components due to atmospheric effects and orbital fringes. So far, the application of the PS technique has been focused on the extraction of the motion field of the area of interest. However, it is also known that PS relative elevations can be estimated with sub-meter precision while smooth errors can be removed using a coarse resolution DEM or the data of the Shuttle Radar Topography Mission (SRTM). In this paper, we describe a new approach combining the PS Technique and standard interferometry to improve the quality of lnSAR DEM's. ERS Tandem interferograms are exploited to increase the number of coherent pixels, while atmospheric effects are estimated and subtracted by means of the sparse PS grid. Prior information and PS elevation are used to reduce the probability of phase-unwrapping errors. Preliminary results are reported and the key-factors for its successful application (e.g. the number of Tandem acquisitions available, PS density) are discussed.

Continuity of the European Remote Sensing Satellite Synthetic Aperture Radar (ERS SAR) archive by means of Envisat Advanced SAR (ASAR) data acquired from March 2002 has introduced the problem of the coherent combination of images coming from sensors with slightly different frequencies. The spectral shift principle states that in case of extended distributed targets, the frequency shift is equivalent to a change of looking angle. In this paper, the same principle is exploited to analyze the behavior of permanent scatterers (PSs) with an extension that is smaller than the ground resolution cell. The conditions under which the PSs identified by ERS can be continued by Envisat are then theoretically determined and experimentally validated. Moreover, this analysis shows that acquisitions characterized by different frequencies can be used to identify the slant-range position of scatterers with high subcell accuracy (tens of centimeters). From the processing side, a very precise images coregistration step is required to get the results described in this paper

The phase time series of a perfect point-wise Permanent Scatterer (PS) would show a phase jump passing from ERS to ENVISAT SAR images. A PS analysis has been carried out on a dataset including both ERS and ENVISAT images. For each PS, elevation, LOS velocity and phase jump have been jointly estimated and removed, allowing the identification of the atmospheric phase screen. The PS population so found represents the intersection of ERS and ENVISAT PS populations. The probability of natural targets to behave as PS both in ERS and ENVISAT has been analyzed as a function of their Radar Cross-Section, acquisition geometry and amplitude. Distributed targets with a narrow backscattering lobe pointed towards the first sensor (ERS) are not coherently observed by the second one (ENVISAT), whereas point-wise targets (e.g. natural corner reflectors, dihedrals and small mirrors) will remain coherent in both cases. Experimental results have been carried out on a data set of 69 ERS images and 7 ENVISAT images (ERS-like mode) on Milano over a 20 km side area.

The aim of this paper is to highlight some important issues that should be taken into account when designing and planning a SAR mission dedicated to differential SAR interferometry (DInSAR) and Permanent Scatterers (PS) analysis. Special attention is paid to the impact of different design parameters on the information that can be retrieved, namely: (1) different wavelengths; (2) repeat cycle; (3) polarization modes; (4) platform stability; (5) state vectors accuracy. The impact of satellite dead band at different frequencies is discussed as well, taking into account DEM estimation issues and the problem of atmospheric effects. It is shown how very small baselines are not always the best design solution at least for PS analysis. PS results obtained processing 3 multi-temporal data sets acquired by JERS, ERS and Radarsat over Tokyo are presented and discussed

The permanent scatterers (PS) technique (Ferretti et al, 2001, 2000, Colesanti et al., 2003), is a powerful and fully operational tool for monitoring ground deformations on a high spatial density grid of point-wise targets, exploiting long series of SAR data. The most attractive aspects of this approach is the capability of providing measurements relative to individual radar targets with unprecedented precision. Up to now, PS analyses have been carried out on ERS, RADARSAT, and JERS data sets. The purpose of this presentation is to discuss the feasibility of updating results obtained by means of a PS analysis on ERS interferometric data using ENVISAT ASAR images. In particular, the main goal is to stitch coherently the new ENVISAT ASAR measurements to the already available ERS displacement time series relative to individual PS. To this end, we will model the interferometric phase of point-wise targets taking account the different ERS and ENVISAT carrier frequencies. Then, we identify the main constraints to be met at individual permanent scatterers in order to guarantee the feasibility of coherent stitching.

This work concerns the application of space-borne SAR interferometry (InSAR) to the study of the land subsidence problem affecting the urban areas of the Firenze-Prato-Pistoia basin (Central Italy). Such a phenomenon is mainly related to the large amount of ground-water pumped for the industrial activities of this area. The interferometric analysis has been carried out by means of both traditional Differential Interferometry (DInSAR) and Permanent Scatterers technique (PS) by using SAR data acquired by the ESA ERS1/2 satellites. Different patterns of terrain subsidence have been detected in the industrial areas of the monitored basin.

Spaceborne differential radar interferometry has proven a remarkable potential for mapping ground deformation phenomena (e.g., urban subsidence, volcano dynamics, coseismic and postseismic displacements along faults, as well as slope instability). However, a full operational capability has not been achieved yet due to atmospheric disturbances and phase decorrelation phenomena. These drawbacks can often be-at least partially-overcome by carrying out measurements on a subset of image pixels corresponding to natural or artificial stable reflectors [permanent scatterers (PS)] and exploiting long temporal series of interferometric data. This approach allows one to push the measurement precision very close to its theoretical limit (in the order of /spl sim/1 mm for C-band European Remote Sensing (ERS)-like sensors). In this paper, the detection of both time-uniform and seasonal deformation phenomena is addressed, and a first assessment of the precision achievable by means of the PS Technique is discussed. Results highlighting deformation phenomena occurring in two test sites in California are reported (Fremont in the Southern Bay Area and San Jose in the Santa Clara Valley).

In this paper we start addressing the main advantages and possible applications of carrying out permanent scatterers analyses involving more independent data sets covering the same test area (i.e. data acquired along parallel orbits relative to adjacent tracks as well as data gathered by ascending and descending passes). First interesting results are provided.

Temporal and geometrical decorrelation often prevents SAR interferometry from being an operational tool for surface deformation monitoring and topographic profile reconstruction. Moreover, atmospheric disturbances can strongly compromise the accuracy of the results. The authors present a complete procedure for the identification and exploitation of stable natural reflectors or permanent scatterers (PSs) starting from long temporal series of interferometric SAR images. When, as it often happens, the dimension of the PS is smaller than the resolution cell, the coherence is good even for interferograms with baselines larger than the decorrelation one, and all the available images of the ESA ERS data set can be successfully exploited. On these pixels, submeter DEM accuracy and millimetric terrain motion detection can be achieved, since atmospheric phase screen (APS) contributions can be estimated and removed. Examples are then shown of small motion measurements, DEM refinement, and APS estimation and removal in the case of a sliding area in Ancona, Italy. ERS data have been used.

The authors present the experimental test of a SAR system that uses a fixed ground-based receiver and, as an illuminator, a TV broadcasting satellite. The synthetic aperture is obtained by exploiting the small daily motion of the satellite. The spatial resolution and the link budget are also analyzed.

Discrete and temporarily stable natural reflectors or permanent scatterers (PS) can be identified from long temporal series of interferometric SAR images even with baselines larger than the so-called critical baseline. This subset of image pixels can be exploited successfully for high accuracy differential measurements. The authors discuss the use of PS in urban areas, like Pomona, CA, showing subsidence and absidence effects. A new approach to the estimation of the atmospheric phase contributions, and the local displacement field is proposed based on simple statistical assumptions. New solutions are presented in order to cope with nonlinear motion of the targets.

Multibaseline synthetic aperture radar (SAR) interferometry can be exploited successfully for high-quality digital elevation model (DEM) reconstruction, provided that both noise and atmospheric effects are taken into account. A weighted combination of many uncorrelated topographic profiles strongly reduces the impact of phase artifacts on the final DEM. The key issue is weights selection. In the present article a wavelet domain approach is proposed. Taking advantage of the particular frequency trend of the atmospheric distortion, it is possible to estimate, directly from the data, noise and atmospheric distortion power for each interferogram. The available DEMs are then combined by means of a weighted average, carried out in the wavelet domain. This new approach provides a valuable tool not only for DEMs combination (improving accuracy), but for data evaluation and selection, since the phase error power is estimated for each interferogram. Results obtained using simulated and real data (ERS-1/2 TANDEM data of a test area around the Etna volcano, Sicily) are presented.

A technique to get medium resolution (40/spl times/40 m, on the ground), strip-map synthetic aperture radar (SAR) interferograms and coherence maps close to real-time by means of common UNIX workstations or PCs is presented. The requested efficiency is achieved by the following: 1) exploiting the spectral shift principle to reduce the data rate at the cost of some signal loss; 2) exploiting polyphase filters and integer implementation to get azimuth looks; 3) implementing a fast and robust estimator of coregistering parameters based both on amplitude cross correlation and of looks' phase mismatch estimate.

A synthetic aperture radar (SAR) is considered, located on a geosynchronous receiver, and illuminated by the backscattered energy of satellite broadcast digital audio or television signals. The principal application of such a passive system could be differential interferometry, since even low spatial resolution coupled to zero baseline would be useful; however, other imaging applications could be envisaged and even some topographic capabilities if a baseline is created by ellipticizing the receiver's orbit. Spatial resolution, link budget, and possible focusing techniques are evaluated.

Usual coherence estimation in SAR interferometry is a time consuming task since an accurate estimation of the local frequency of the interferometric fringes is required. This paper presents a fast algorithm for generating coherence maps, mainly intended for data browsing. The proposed estimator is based on the speckle similarity of coherent SAR data, and is thus independent of fringe frequency. The following advantages, with respect to the usual estimates, are achieved: (a) The estimator is more than 100 times faster, achieved at the cost of a reduced statistical confidence. (b) The estimator is not affected by possible local frequency estimation errors. (c) The estimator can be directly applied to single look detected images. The theoretical derivation of the statistical properties of the frequency independent estimator is carried out in the stationary case. The nonstationary case is then analyzed on real ERS SAR images.

The authors discuss an efficient phase preserving technique for ScanSAR focusing, used to obtain images suitable for ScanSAR interferometry. Given two complex focused ScanSAR images of the same area, an interferogram can be generated as for conventional repeat pass SAR interferometry. However, due to the nonstationary azimuth spectrum of ScanSAR images, the coherence of the interferometric pair and the interferogram resolution are affected, both by the possible scan misregistration between two passes and by the terrain slopes along the azimuth. The resulting decorrelation can be significantly reduced by means of an azimuth varying filter, provided that some conditions on the scan misregistration are met. Finally, the SAR-ScanSAR interferometry is proposed: here the decorrelation can always be removed. With no resolution loss by means of the technique presented.

SAR surveys from separate passes show relative shifts of the ground wavenumber spectra that depend on the local slope and the off-nadir angle. The authors discuss the exploitation of this spectral shift for different applications: 1) generation of "low noise" interferograms benefiting phase unwrapping, 2) generation of quick-look interferograms, 3) decorrelation reduction by means of tunable SAR systems (TINSAR), 4) range resolution enhancement, and 5) the combination of SAR data gathered by different platforms (airborne and satellite) for a "long-time coherence" study.>

SAR data spatially sampled at the Nyquist limit can be correctly processed if the Doppler centroid is precisely known. Whenever the Doppler centroid shows rapid variations either with range or azimuth, more care is required in order to take advantage of the computational efficiency of frequency domain techniques. It is shown that such focusing techniques can still be exploited, provided that SAR raw data are previously modified and a space-varying nondimensional filter is applied to the focused image. The computational cost increases, but it is still smaller than time-space domain processing. Results obtained with simulated SIR-C/X-SAR data and SPOTlight geometries are presented.>

For high-quality SAR (synthetic aperture radar) processing, the Doppler centroid frequency is needed. However, SAR data are sampled along the azimuth direction at the pulse repetition frequency (PRF); the estimation of the Doppler centroid frequency by means of spectral analysis techniques may produce ambiguous results due to aliases. The mathematical expression of the residual error that occurs when SAR data are focused with an incorrect alias of the PRF is thus derived. Then, a blind deconvolution technique is used to estimate the actual PRF replica from the focused image. Squinted X-band data, corresponding to those that will be generated by the SIR-C mission, have been generated from the JPL-AirSAR L- and C-band data by means of an inversion of the focusing process. Even if the real data may show differences with respect to the simulated data, the blind deconvolution method appears to be more precise and robust than the other conventional techniques tested.>

A particular approach to the azimuth migration of synthetic aperture radar (SAR) data is discussed. It is shown that a slightly defocused SAR image can be corrected by means of a short monodimensional filter with a quadratic phase vs. time characteristic. This kind of processing, called residual migration, has reduced computational complexity and minimal storage requirements compared to conventional focusing techniques. Residual migration is therefore suitable for implementing an efficient SAR autofocusing processor, which usually requires several focusing iterations to get a good image quality.>

In synthetic-aperture-radar interferometry from satellite, the altimetric information is obtained from the phase difference of two images gathered by the same sensor during two successive passes along parallel or crossing orbits. The altimetric resolution of such a system depends on the satellite's displacement in the cross-track direction. The satellite's displacement, however, is limited by the effective ground sampling in the cross-track direction. For the sake of a greater altimetric resolution, the satellite's displacement should be adapted to the terrain slope. A coarse altimetric map of the Panamint Valley area is constructed exploiting three repeated passes of the Seasat SAR satellite.>