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 letter focuses on ship target localization using a multistatic passive radar system based on navigation satellites opportunistic illuminators. In such systems, the typical approach to localize the targets is taking peripheral decisions at each bistatic channel to detect the target followed by bistatic ranges intersection. In contrast, here we consider a centralized approach in order to jointly detect and localize the ship target of interest. The proposed approach entirely operates in a Cartesian plane representing the surveyed maritime area and it is able to combine the signals pertaining the different bistatic links despite the variation of the e.m. response of the targets, typically occurring in the framework under consideration as the target is illuminated by multiple (and possibly widely separated) transmitters viewing angles. Moreover, the hypothesis of point-like targets is here replaced with the more realistic case of extended targets (i.e., occupying more than one resolution cell). The ship localization effectiveness of the method is proved via both synthetic and experimental datasets.

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.

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.