This paper deals with the exploitation of shadow regions in high-resolution drone-borne synthetic aperture radar (SAR) images and utilizing them for accurate target height and shape estimation. While prior research has shown the potential of SAR shadows for height estimation, these efforts have primarily focused on airborne and spaceborne platforms and lack a theoretical analysis for assessing achievable performance. In contrast, this work introduces a processing chain for target height and shape extraction and proposes a theoretical framework to evaluate system performance. The study demonstrates that the geometric flexibility and maneuverability of drones offer significant advantages in height estimation accuracy compared to conventional SAR platforms. The proposed method is validated using experimental data from a 24 GHz INRAS radar-equipped drone-borne SAR system, showing strong alignment between the extracted 2D shapes and height estimates and the theoretical predictions. Additionally, the study highlights how multi-perspective drone imagery enables the reconstruction of three-dimensional structures, further extending the potential of drone-borne SAR systems.

This work consolidates the existing results in the field of information extraction from spaceborne SAR imagery based on Inverse Synthetic Aperture Radar (ISAR) techniques, as well as enhances the understanding of the phenomenology, the models, the processing algorithms, the applications, and the overall value in security applications. The focus is on ISAR based advanced processing methods to explore the potentialities of very high resolution (VHR) SAR data in a range of security related application domains, including maritime, inland water, and land scenarios.

This paper presents a novel processing chain based on Synthetic Aperture Radar (SAR) and Inverse SAR (ISAR) techniques to refocus SAR images of moving maritime targets and estimate their motion parameters. The proposed processing chain was developed and extensively evaluated The algorithm was tested on a large dataset of COSMO-SkyMed (CSK) and Cosmo Second Generation (CGS) dataset including 300 vessels, and spanning different maritime scenarios, in order to account for many contingencies such as the sea states, the ship movements, and the mutual geometry between the SAR orbit and the course of ship. To assess the refocusing capability, quantitative contrast measurements of the refocused images were conducted. The accuracy of vessel speed estimation was evaluated by comparing the results with Automatic Identification System (AIS) data as a reference. The key contribution of this work lies in demonstrating the effectiveness of ISAR processing applied to satellite SAR images for near real-time Maritime Awareness applications. This was achieved through the development of a robust and fully automatic processing chain, as well as an extensive experimentation and validation process.

This article explores the possibility to exploit global navigation satellite systems (GNSS) signals to obtain radar imagery of ships. This is a new application area for the GNSS remote sensing, which adds to a rich line of research about the alternative utilization of navigation satellites for remote sensing purposes, which currently includes reflectometry, passive radar, and synthetic aperture radar (SAR) systems. In the field of short-range maritime surveillance, GNSS-based passive radar has already proven to detect and localize ship targets of interest. The possibility to obtain meaningful radar images of observed vessels would represent an additional benefit, opening the doors to noncooperative ship classification capability with this technology. To this purpose, a proper processing chain is here conceived and developed, able to achieve well-focused images of ships while maximizing their signal-to-background ratio. Moreover, the scaling factors needed to map the backscatter energy in the range and cross-range domain are also analytically derived, enabling the estimation of the length of the target. The effectiveness of the proposed approach at obtaining radar images of ship targets and extracting relevant features is confirmed via an experimental campaign, comprising multiple Galileo satellites and a commercial ferry undergoing different kinds of motion.

This paper addresses the exploitation of global navigation satellite systems as opportunistic sources for the joint detection and localization of vessels at sea in a passive multistatic radar system. A single receiver mounted on a proper platform (e.g., a moored buoy) can collect the signals emitted by multiple navigation satellites and reflected from ship targets of interest. This paper puts forward a single-stage approach to jointly detect and localize the ship targets by making use of long integration times (tens of seconds) and properly exploiting the spatial diversity offered by such a configuration. A proper strategy is defined to form a long-time and multistatic range and Doppler (RD) map, where the total target power can be reinforced with respect to, in turn, the case in which the RD map is obtained over a short dwell and the case in which a single transmitter is employed. The exploitation of both the long integration time and the multiple transmitters can greatly enhance the performance of the system, allowing counteracting the low-power budget provided by the considered sources representing the main bottleneck of this technology. Moreover, the proposed single-stage approach can reach superior detection performance than a conventional two-stage process where peripheral decisions are taken at each bistatic link and subsequently the localization is achieved by multilateration methods. Theoretical and simulated performance analysis is proposed and also validated by means of experimental results considering Galileo transmitters and different types of targets of opportunity in different scenarios. Obtained results prove the effectiveness of the proposed method to provide detection and localization of ship targets of interest.

This paper considers the exploitation of navigation satellite systems as opportunity transmitters for bistatic and multistatic synthetic aperture radar (SAR). The simultaneous availability of multiple satellites over a scene of interest at different viewing angles allows multistatic SAR acquisitions using a single receiver on or near the ground. The resulting spatial diversity could be used to drastically improve image resolution or to enhance image information space. To exploit the availability of multiple satellites, two data fusion approaches are here considered. In the former, point features of the single images obtained from different perspectives are extracted and then combined, whereas in the latter, a multistatic image is first obtained by combining the single channel data at the image level and then the point features are extracted. This is achieved by considering ad hoc CLEAN-like techniques. These techniques have been developed on both the analytical and simulation levels and experimentally verified with real GNSS-based SAR imagery. The techniques described here are not limited to GNSS-based SAR but may be applied to any multistatic SAR system.

In the last years significant effort has been dedicated to prove that increased information and/or better performance can be retrieved in radar and radar imaging using a network of cooperating sensors. In this paper, data acquired by two Inverse Synthetic Aperture Radar sensors observing a target from different points of view in the long range surveillance operative case is exploited to estimate both radial and cross-radial components of a target's translational motion. Simulated objective functions prove the feasibility of the proposed techniques, confirmed by the analysis of the results of their application against real data acquired by the Radar Sensor Network installed at the NATO Centre for Maritime Research and Experimentation.

Multichannel space-based SAR systems that exploit receiving antenna sub-arrays displaced in the along track-direction have been shown to provide the capability to detect ground moving targets and potentially estimate their radial motion velocity, thus making possible their correct relocation inside the SAR image of the background. However, the use of only two receiving channels to contain cost, mass and data-rate, imposes limitations in terms of potentiality of joint clutter cancellation and target velocity estimation. To overcome this problem we propose a full MIMO SAR scheme obtained by transmitting nearly orthogonal waveforms with the two sub-arrays achieved from a single antenna aperture, and receiving with the two sub-arrays. A complete processing chain for the joint detection, imaging and radial speed estimation is presented and the performance of the proposed MIMO system is deeply investigated and compared to the performance of conventional multichannel systems to assess the relative merits and drawbacks.

This letter deals with the multiple-input-multiple-output distributed radar imaging of rotating targets. The distributed system is based on formation-flying platforms, which can be configured with proper cross-track and along-track displacements. The platforms carry active radar systems transmitting almost orthogonal waveforms; exploiting both monostatic and bistatic acquisitions, range and cross-range resolution improvement can be achieved, and a maximum theoretical 2-D resolution cell improvement factor can be obtained significantly greater than the number of flying platforms. The required distributed focusing technique is developed, and its effectiveness and robustness is tested against simulated data. The proposed distributed system could be suitable to the application of ship target imaging, using a reconfigurable formation of platforms, for maritime surveillance in wide sea areas.

This letter presents an analysis of the multistatic point-spread function (MPSF) for passive synthetic aperture radar (SAR) with navigation satellites as opportunity transmitters and a stationary receiver. It is shown that a noncoherent combination of bistatic SAR images, obtained by multiple, spatially separated satellites, can yield multistatic imagery that may be essentially improved in terms of resolution when compared with a single bistatic SAR image. The MPSF is derived analytically, for an arbitrary number of bistatic acquisitions and for any bistatic topologies. Analytical results are confirmed using both simulated and experimental data. The obtained result could be applied for the analysis of spatial resolution in multistatic real time radar, thus enabling the adaptive selection of the more suitable opportunity transmitters.

This paper presents an effective signal processing scheme to track moving vehicles and to obtain their cross-range profiles with a passive bistatic radar (PBR) based on the signals of opportunity emitted by a WiFi router. While the target detection using WiFi-based PBR has already been studied by the authors, this paper focuses on the targets moving with a low radial velocity component. These are especially interesting since they might have a reasonable cross-range velocity component, which allows us to apply inverse synthetic aperture radar (ISAR) techniques to provide a high-resolution cross-range profile. A specific problem for these targets is the presence of possibly strong echoes from the stationary background (clutter), which tend to mask their contributions. In such cases, the standard Doppler processing does not help in separating the targets from this clutter. Therefore, appropriate clutter cancellation schemes are applied, and their effectiveness and impact are analyzed both on the tracking and on the ISAR profiling. An appropriate ISAR scheme for cross-range profiling is introduced, tailored for the typical short-range and possibly bistatic surveillance scenarios of the WiFi-based PBR; this scheme comprises the automatic estimation from the data of the target motion components up to a higher order than in usual long-range imaging and their compensation. The reliability of the obtained profiles is also investigated, for both the monostatic and bistatic cases, which is essential both for the vehicle size/characteristics estimation and for the automatic recognition schemes based on vehicle databases. The results obtained using an experimental setup developed and fielded at the University of Rome “La Sapienza,” Rome, Italy, show that the considered approach is effective and that the obtained cross-range profiles achieved by ISAR processing with WiFi-based passive radar are quite reliable both in the monostatic and bistatic cases.

An innovative scheme is presented for moving target detection and high-resolution focusing that exploits a bank of chirp scaling algorithms (CSA), each one matched to a different along track target velocity component. The new scheme is thought for multichannel (MC) synthetic aperture radar systems, to provide a high-resolution focusing of the moving targets. Adequate target detection capability is ensured by integrating the aforementioned bank of CSA with a post-Doppler space-time adaptive processing clutter cancellation step. The presented scheme is very efficient from a computational point of view and is able to achieve sub-clutter visibility for the moving targets. The effectiveness of the proposed techniques is shown with reference to an emulated MC data set.

Advanced satellite SAR systems, such as Cosmo SkyMed, provide high resolution images with reasonably short revisiting time, allowing for a number of applications in areas such as Homeland Security and Maritime Surveillance. Especially in the case of maritime surveillance, non-ccoperative moving targets imaging represent a challenge for SAR systems as the complex target motions produce evident image defocusing. In the present paper, we show evidence of the effectiveness of the applications of ISAR processing to obtain well focused images of such type of targets. It will be also shown that super-resolution techniques are applicable to targets affected by complex motions after ISAR processing is used.

The aim of this work is the development of processing techniques in order to provide the Cosmo-SkyMed (CSK) single-channel SAR system of Ground Moving Target Indication (GMTI) capabilities. To this purpose a two step processing chain is proposed: the first step performs stationary clutter suppression while the second step performs moving targets detection. For the last step two different detection schemes are proposed based respectively on a Bank of Chirp Scaling Algorithms (BCSA-MTD) and on a Change Detection approach (CD-MTD). The effectiveness of the proposed techniques is demonstrated against CSK data.

This paper concerns the definition of efficient configurations of acquisition for improving the features of tomographic imaging using a constellation of SAR sensors. MIMO SAR measurements done in monostatic and bistatic configurations permit to enhance the spectral diversity of the acquisition in the vertical direction, yielding higher performance in terms of ambiguity height and resolution. Different cases are investigated, and in particular a configuration with tracks that would reveal ambiguous for systems operating in monostatic mode only, and another one consisting of sparse groups of acquisitions. The validity of the proposed approach is demonstrated using data sets acquired by a versatile multi channel Ground-Based SAR system, operating in alternating emit-receive mode, over coherent scatterers and distributed volumetric media.

In this paper, an innovative technique is presented for synthetic aperture radar (SAR) ground range resolution improvement using multiple transmit and receive platforms with adequate cross-track displacement. Using orthogonal waveforms, which occupy the same bandwidth in the range frequency domain, for the different platforms of the constellation, a multiple-input-multiple-output SAR system is configured. The proposed technique allows one to achieve a maximum theoretical range resolution improvement factor that is significantly greater than the number of operating SAR sensors by jointly exploiting both mono- and bistatic acquisitions. This can be exploited to obtain a ground range resolution that is much higher than the resolution corresponding to the frequency bandwidth transmitted by the single platform. After illustrating the proposed technique and its system requirements, a simulated data set is used to show the effectiveness of the proposed approach.

In this paper, we present a new technique to exploit the data acquired simultaneously by multiple radar sensors carried by multiple air platforms to increase the cross-range resolution of inverse synthetic aperture radar (ISAR) images of rotating targets. This distributed ISAR technique is devised for two different cases: 1) multiple-input-multiple-output (MIMO) case with each platform carrying an active radar that transmits and receives RF waveforms and 2) multistatic case with a single platform carrying an active radar (transmitting and receiving) and the remaining platforms equipped with passive sensors (namely, receiving only). The processing chain proposed for the distributed ISAR is shown, together with the results obtained against simulated ISAR data for both the MIMO and the multistatic cases. The performance analysis shows that the proposed technique is able to provide an increase of the cross-range resolution up to the number of platforms in the multistatic case and even higher in the MIMO case, if the platforms are properly located. This is of great benefit in applications where the target rotation angle is insufficient to guarantee the desired resolution. A typical case is the imaging of ship targets with rotation induced by the sea swell structure under low sea state conditions. To make the results appealing for practical application, the performance degradation is also analyzed arising from errors in the knowledge of both the target rotation motion and the acquisition geometry. Experimental data collected by a ground-based radar operating together with a rotating platform are processed by following the presented distributed ISAR technique to validate the proposed approach.

A moving target detection and high-resolution focusing scheme is presented for single-channel SAR systems. The moving target focusing is made of a bank of Chirp Scaling Algorithms (CSA), each one matched to a different along-track target velocity component, thus allowing to produce a high-resolution image of the target itself. The effectiveness of the proposed technique is shown with reference to a sample dataset obtained from a SAREX-92 image.

In this paper an innovative technique for ground range resolution improvement in Multiple Input Multiple Output (MIMO) SAR systems is presented. The technique allows to achieve a maximum theoretical range resolution improvement factor greater than the number of operating SAR sensors, by exploiting both the monostatic and the bistatic acquisitions. The effectiveness of the proposed technique is validated over a simulated dataset.

This paper investigates the effect of apodization on the statistical properties of synthetic aperture radar (SAR) images and its impact on the capability of extracting information from homogeneous regions of apodized SAR images. The statistical model for the pixel complex amplitude of the apodized image is derived in terms of both probability density function and statistical moments. Knowledge of the statistical properties is then used to develop appropriate schemes for parameter estimation and supervised classification of homogeneous regions with different radar cross sections in apodized SAR images. The performance analysis shows that the new techniques (properly derived for the apodized case) provide information extraction capabilities only slightly worse than those provided by the conventional techniques applied to the nonapodized case. This allows us to conclude that the use of nonlinear apodization yields sidelobe level reduction and main lobe resolution preservation that can be traded with the small losses above. A full characterization of the estimation and classification performance of these new techniques shows that nonlinear apodization globally introduces a performance degradation comparable to a reduction of the number of looks of a factor of 1.455 for a homogeneous region.

This paper assesses GPR (Ground Penetrating Radar) performance for archaeological investigations. We exploit extensive data acquisition campaigns to characterize the instrument behavior in different operative conditions and we select ad hoc processing techniques to optimally extract target signatures from the collected data. The extensive analysis demonstrates the real effectiveness of GPR surveys in archaeological investigations.

Ship detection in polarimetric SAR images of non-homogeneous sea areas is considered. We demonstrate the impact of non-homogeneous sea features on the false alarm rate and the need of extracting the image structure. We thus introduce polarimetric segmentation procedures that cooperate with high-resolution polarimetric detection features for the control of the false alarms. Different polarimetric segmentation-plus-detection procedures are tested over real data to devise the appropriate method to exploit the polarimetric information.