The IRIDE constellation is an ambitious Italian space program that will support the national authorities in their analyses and monitoring activities, with a focus on Italian territory mapping. It will comprise a series of small satellite subconstellations exploiting a wide range of remote sensing technologies. This article analyses the NIMBUS X-Band synthetic aperture radar (SAR) IRIDE subconstellation, exploring potential orbital configurations beyond the more conventional and widespread dawn-dusk sun-synchronous orbit (SSO) one. In particular, starting from the mission target, we show that a 49° mid-inclination orbit (MIO) in a right-looking StripMap acquisition mode represents a highly effective choice for NIMBUS. We demonstrate that this configuration enhances the systematic coverage of the Italian territory with six nodal days of interferometric revisit time and high spatial resolution, thereby facilitating detailed observations of both natural phenomena and anthropic activities. In terms of differential SAR interferometry (DInSAR) performance, we prove that MIOs do not show significant limitations for what attains the critical baseline and geometric distortions. In addition, MIOs may lead to future advances in creating 3-D displacement maps because they allow for the recovery of the North-South deformation component that, conversely, cannot be precisely measured with DInSAR systems operating in SSO.

The Geostationary Synthetic Aperture Radar (GEO-SAR) concept aims at defining an Earth Observation system able to provide regional coverage with large swaths and subcontinental access with a very short revisit time by exploiting the unique characteristics of the GEO orbit. These peculiar characteristics make GEO-SAR suitable for imaging and interferometry of fast-evolving large-scale phenomena, such as ground motion or water vapor. The design of the orbit for a GEO-SAR is discussed to provide, at one time, wide imaging capability, compensation for the huge power loss due to the distance, and short interferometric revisit. In particular, interferometry imposes constraints on the repeatability of the orbit that are far more restrictive than the control required for telecommunication satellites. Here, two different specific control approaches are proposed to ensure small normal baselines and to maximize angular band overlap between subsequent acquisitions. The first one is based on four control maneuvers per orbit period that exploits tangential, normal, and radial burns, whereas the second one is based on three daily maneuvers that are performed only in tangential and normal directions. The latter assures accurate motion repetition while saving the required propellant mass.

Maritime situational awareness (MSA) refers to the effective understanding of activities related to maritime environment. Central to MSA, particularly concerning non-military vessels, is the automatic identification system (AIS), which provides real-time data on vessel movements. However, anomalies such as intentional AIS transponder disablement pose significant challenges to MSA, potentially indicating illicit activities. This paper introduces the Dark-VADER (dark vessel AIS delay event recognition) algorithm, designed to detect AIS switchoffs by comparing the frequency of message reception from a vessel under examination with that of neighboring vessels. Leveraging a statistical hypothesis testing procedure based on a Bernoulli process, the algorithm distinguishes between normal and anomalous behavior. Validation using real-world AIS data confirms the fitness of the selected distribution model for times between message arrivals, essential for the algorithm’s operation. Overall, this preliminary work provides a foundational framework for improving maritime AIS anomaly detection, with avenues for future development towards more robust and dynamic approaches.

In this work, we investigate potential orbital configurations of NIMBUS, one of the Synthetic Aperture Radar (SAR) components of the Italian constellation IRIDE, which will be completed by 2026 under the management of the European Space Agency (ESA), with the support of the Italian Space Agency (ASI). IRIDE is conceptualized as a "constellation of constellations", comprising multiple sub-constellations of satellites positioned in Low Earth Orbit (LEO) and equipped with various sensing technologies, including SAR and optical sensors with medium- and high-resolution capability, operating at different frequency ranges. Given both institutional and commercial users the constellation is expected to fulfill, this work introduces a methodology to compare different orbital configurations and finally identify the optimal orbital arrangement that maximizes the Italian national coverage within the shortest revisit time possible, considering both the capabilities and imaging performance of a SAR system planned for deployment in orbit.

Distributed Synthetic Aperture Radar (DSAR) systems represent an appealing solution to lower the overall costs and improve flexibility and efficiency of future Earth Observation missions. However, this type of systems requires receivers to fly very close to each other for enabling coherent beamforming techniques. Autonomous formation flying strategies can be employed to keep satellites within a small envelope. However, the variation over time of the distances among the satellites, that stems from the relative dynamics associated to the need of ensuring a safe formation geometry, results in a performance degradation for the beamforming over specific areas or time spans. The paper analyzes the problem of DSAR performance prediction when the satellite formation is designed exploiting the safety ellipse concept.

Along with the monostatic radar imaging configuration, as a standard approach for Synthetic Aperture Radar imaging, new generation ideas of radar imaging geometry under the name of bistatic configurations are emerging. Due to the separation of the transmitter and receiver positions in bistatic SAR systems, different configurations can be imagined for them. One of these configurations, which is more well-known, is the azimuth-invariant configuration. In this configuration, the receiver follows the transmitter in a fixed azimuth path, collates the ground targets’ response in the forward-looking mode and at different angles, and generates the final SAR image. This SAR image is comparable to the monostatic in various aspects such as resolution, signal-to-noise ratio (SNR), etc. In this paper, some of these aspects will be evaluated. The results show with the increase of bistatic angle, both of the resolution and SNR are worse.

Artificial Intelligence (AI) applications on Earth Observation (EO) satellite data, such as those for vessel detection, are gaining attention for their potential to meet strict bandwidth and latency requirements. While traditional on-ground computing pipelines often rely on heavy post-processing, implementing these techniques onboard satellites is challenging due to limited computing resources. To support the development of efficient onboard data processing strategies, this study compares the performance of object detection on raw data from Sentinel-2 and VENμS missions. The study demonstrates that the proposed two-stage approach with a focus on efficiency is capable of identifying vessels in raw data with minimal pre-processing. Specifically, our method achieved a remarkable Average Precision (AP) of 0.841 on the VENμS dataset.

This paper focuses on the timing analysis for a Distributed Synthetic Aperture Radar (DSAR) system exploiting an opportunity illuminator. This is the case of RODiO, which is a new mission concept funded by the Italian Space Agency (ASI) for a Phase A study in the framework of ALCOR program. RODiO’s aim is to match the growing trend towards the miniaturization of satellites and new Synthetic Aperture Radar (SAR) applications. For this reason, RODiO consists in a cluster of four receiving-only CubeSats flying in a close formation and exploiting the independent PLATiNO-1 satellite as a transmitter. Because of the nature of RODiO mission, simultaneous observations with respect to the monostatic illuminator are needed. Through the comparison of monostatic and bistatic chronograms, a timing analysis is performed in the paper in order to assess the effects of DSAR geometry on simultaneous observation opportunities, aiding the design of the system.

This paper presents the findings of the COAST project, an innovative investigation into maritime surveillance using Synthetic Aperture Radar (SAR) technology, funded by the Italian Space Agency. The research specifically delves into the synergistic potential of a multi-frequency/multi-mission (MFMM) approach to detect and identify vessels, a facet relatively unexplored in previous studies. Four technical objectives drive the study, including the detection of both visible and non-visible non-cooperating ships and their classification using SAR tomography techniques, as well as AIS/SAR data matching with velocity estimation. This research promises to enhance maritime domain awareness and security by furthering our understanding of SAR-based vessel detection and classification methodologies.

Nowadays, the use of Artificial Intelligence on board Earth Observation satellites is under investigation for applications having strict bandwidth and latency requirements, such as vessel detection. However, many of the on-ground current computing pipelines rely on data post-processing techniques whose applications onboard satellites are tricky because of their limited computing power. To enable the analysis and the research of lightweight onboard data processing techniques, we provide VDS2Raw, the first Sentinel-2 Raw dataset for vessel detection applications. Finally, we also compared different object detection Deep Learning techniques in terms of detection performance and inference time to perform a feasibility analysis of performing onboard vessel detection on raw multi-spectral data.

The wakes generated by moving vessels represent relevant patterns in remotely sensed images. They are a marker of ship presence and can be processed to infer route, speed, size, and type of ships. Automatic wake detection can be exploited by law enforcement agencies and local authorities for ensuring a wide range of applications, including maritime traffic surveillance, border control, and protection of marine protected areas. The topic is thus attracting increasing interest from the remote sensing community. This paper contributes in this context presenting a novel approach based on the detection of the keypoints of wake components by Convolutional Neural Networks (CNNs) in electro-optical satellite imagery. The selected approach to deep learning relies on a transfer learning procedure fine-tuning the ImageNet weights. This is performed through an ad-hoc developed dataset realized from Sentinel-2 multi-spectral images and Automatic Identification System (AIS) data in northern Europe. The experimental results confirm the robustness of the proposed method, which is tested against different spectral bands from visible to near-infrared and also by a domain shifting on lower resolution Landsat-9 images. Fractional errors in the positioning of the wake vertex are lower than 10% and the achieved heading accuracy is below 10°. The proposed method is faster than the traditional approaches based on Radon Transform, and due to its lightweight nature, our model can be executed efficiently on edge-AI devices, enabling real-time processing onboard.

Maritime trade and trasport occupy a pivotal position in the current era of globalization. Thus, monitoring ships at sea represents the starting point of this paper in which a novel approach to detect ships by wake has been proposed, based on Instance Segmentation deep learning architecture Mask R-CNN. In order to train and test this network, 766 wake chips cropped from 50 multispectral images acquired from Sentinel-2 satellites were observed. In particular, B2 (blue), B3 (green), B4 (red) and B8 (Infrared) bands were considered since they are all characterized by same resolution. The results proved that Mask R-CNN is capable to detect the vast majority of ship wakes with high confidence percentage in different configurations, i.e. slanted wakes, multiple wake scenarios or wakes in dark areas not related to their features.

The recent launches of Earth Observation (EO) satellites have made numerous SAR images available to dynamically monitor the ocean with improved spatial resolution at shorter revisit time. Focusing on automatic target detection of ships with the specific aim of improving our Maritime Domain Awareness (MDA), this work assesses the capabilities of multi-frequency/multi-mission spaceborne Synthetic Aperture Radar (SAR) data. Specifically, Sentinel-1 (C-band), COSMO-SkyMed (X-band), and SAOCOM (L-band) missions have been considered in this analysis. The aim of the paper is to present an efficient approach for interpreting images acquired within small time gaps, ensuring fisheries and pollution control, anti-piracy actions, and surveillance over coastal/protected regions.

The paper shows the strong potentialities of multimission/multifrequency SAR data for improving the maritime situational awareness in coastal areas. Two main issues are analyzed: the detection of ships that are visible in SAR images and the identification of non-collaborative vessels, which are not visible in SAR images. In the first case, the multimission/multifrequency data guarantees: (a) smaller revisit time with respect to a single mission, enabling cross-check of the detection in several images and, thus, improving the detection rate, and (b) the availability of images covering large areas at low resolution as well as smaller swath observed with higher resolution. This is crucial in particular for the coastal areas where local phenomena can strongly affect the detection performance. In the second case, the multimission/multifrequency data enables innovative approaches exploiting the different appearance of ship and its wake at different frequencies.

The paper focuses on the concept of a formation-flying synthetic aperture radar (FF-SAR) bistatic system composed of a set of compact, low-weight satellite receivers in close formation (within 1 km) placed in the same low-Earth orbit at large distance (about 100 km) from a transmitter. Each receiver is conceived to fit a 12-unit CubeSat. A signal model adapted to the proposed formation geometry is also presented, and a corresponding processing scheme to achieve range swath widening and signal-to-noise ratio (SNR) improvement is illustrated and discussed.

This paper discusses a new receiving antenna for remote sensing applications to be mounted onboard a formation-flying synthetic aperture radar (FF-SAR) bistatic system based on the CubeSat standard. The formation works as a bistatic SAR collecting microwave signals coming from a transmitting SAR unit. The receiving antenna has been designed according to the acquisition modes of the formation, namely a stripmap mode for signal-to-noise ratio improvement and a High-Resolution Wide-Swath mode for the monitoring of large regions. In order to meet the very different requirements for both operating modes with the physical constraints imposed by the nanosat geometry, a large reflector with reconfigurable feed has been conceived and simulated. The results show that the proposed antenna accomplishes the design specifications.

This paper presents a segmentation algorithm for marine synthetic aperture radar (SAR) images. The proposed approach is based on the analysis of image sublooks along azimuth direction and exploits a novel indicator, called incoherent entropy, to divide the input targets into three classes, namely, ship, sea, and ambiguity. A global threshold detector is then implemented to discriminate between stable targets (ships), providing low incoherent entropy amplitude, and ambiguity or sea, implying very high and high values of the indicator, respectively. An integration of the segmentation algorithm into maritime surveillance systems is investigated, proposing its use as a discrimination tool to limit the false alarm rate of traditional prescreening algorithms. The main steps of a standard SAR-based ship detection system are thus implemented to provide a first screening of the candidate targets, which are, then, processed by sublook analysis using incoherent entropy to identify false detections. The proposed technique is tested on stripmap SAR images collected by the TerraSAR-X mission, over the Gulf of Naples, Italy. Algorithm detections are validated using ground-truth data, provided by automatic identification system. The results confirm the capability of the proposed discrimination approach to reject the vast majority of the false detections resulting from the prescreening algorithm.

Spaceborne synthetic aperture radar (SAR) can be considered an operational asset for maritime monitoring applications. Well-assessed approaches exist for ship detection, validated in several maritime surveillance systems. However, measuring vessel velocity from detected single-channel SAR images of ships is in general difficult. This letter contributes to this problem by investigating the possibility of retrieving vessel velocity by wake analysis. An original method for velocity estimation is developed for calm sea (Beaufort scale 1-2) and applied over seven X-band SAR images, gathered by COSMO-SkyMed mission over the Gulf of Naples, Italy. The algorithm exploits the well-known relation between the wavelength of the waves composing the Kelvin pattern and the ship velocity. But the proposed approach extends the applicability of the existing wake-based techniques since it foresees evaluation of the wavelength along a generic direction in the Kelvin angle. Promising results have been achieved, which are in good agreement with those of more assessed techniques for ship velocity estimation in SAR images.

A targets detection algorithm is proposed for maritime surveillance by single-channel SAR images. It foresees a preliminary prescreening step, carried out using an adaptive threshold algorithm, followed by a discrimination phase, performed by sub-look analysis. The latter discriminates the pixels detected by the former step in three classes, i.e. targets, sea, and azimuth ambiguity. The algorithm is tested on single channel StripMap TerraSAR-X data. Results indicate that the selected algorithm shows promising detection performance and ambiguity rejection capabilities.

Based on a recent renewed interest in the utilization of Moon as a platform for Earth remote sensing, this paper reviews the concept of a Moon-based Synthetic Aperture Radar (SAR). Such a system presents some features, which differentiate it from a conventional spaceborne SAR. Indeed process of antenna synthesis and the observation geometry are quite different. The platform, on which the observatory shall be build up, is not an orbiter or a space formation, but a whole celestial body. Earth-Moon relative motion generates the synthetic aperture and the properties of such a motion allow for the exploitation of very long synthetic antennas. Moreover two or more antennas can be located over lunar surface realizing a distributed SAR and enabling single-pass interferometric SAR applications, e.g. cross-track interferometry and tomography. System parameters and technological challenges of such a Moon-based observatory are also discussed.

This paper investigates the capability of a miniaturized radar sensor developed for Micro Aerial Vehicles (MAVs) to cope with complex mission scenarios that involve integrating and satisfying either Synthetic Aperture Radar (SAR) or Interferometric SAR and navigation and Sense-and-Avoid (SAA) requirements. A radar sensor based on Frequency Modulated Continuous Wave (FMCW) technology developed by IMST GmbH is exploited both for SAR and SAA acquisitions. The set of tests helps with understanding main issues and problems related with integration of different requirements and demonstrate that valuable data for each envisaged application can be saved with a single acquisition, thus paving the road for further and more detailed investigations.

This paper deals with the exploitation of Doppler centroid measurements for ship velocity estimation from focused single-look complex synthetic aperture radar (SAR) images. An algorithm is presented, which can be used as a discrimination tool to reduce the false alarm rate of standard adaptive threshold detectors and to complement the ship detection task with velocity estimation. The outputs are the indication of the presence of a moving target and the estimate of its slant range velocity. After a review of its theoretical background, algorithm features and performance are verified by application to TerraSAR-X data. The proposed method performs robust Doppler spectrum derivation for candidate ship targets and background pixels. The presented results show that the estimated radial velocity is in very good agreement (5% root-mean-square deviation) with that resulting from the azimuth offset method. Rejection of bright sea features and azimuth ambiguities is also demonstrated, taking advantage of the performed velocity analysis.

This paper discusses the performance of a novel millimeter wave radar sensor for UAS autonomous indoor operations. A sensor based on the interferometric Synthetic Aperture Radar (SAR) principle should be able to satisfy the stringent requirements set by indoor operations in terms of high-resolution three-dimensional mapping and autonomous navigation. A solution based on a Frequency Modulated Continuous Wave (FMCW) technology is proposed. The outlined nominal configuration serves as a basis to analyze the performance of the sensor in possible operational scenarios by means of a software simulator. Four different focusing algorithms are implemented and tested and capabilities of the novel sensor are finally discussed, demonstrating that high-resolution, high-quality observation of an assigned control volume can be achieved.

The present paper reports on some insights in the use of Synthetic Aperture Radars (SAR) for bathymetric data retrieval by exploiting variation in swell wave parameters approaching the shoreline. Since SAR signals are unable to penetrate sea surface and to reach seabed, echoed signals from sea surface are used to investigate underwater bathymetry in coastal area. A suitable data processing methodology is proposed to properly detect swell shoaling and refraction phenomena, and to accurately measure swell parameters. The described methodology is tested by using ALOS L-band SAR images over the Gulf of Naples, Italy. A Digital Elevation Model (DEM) of the investigated area is thus obtained. Results are consistent with the values reported in the Official Nautical Chart provided by the Italian Navy Hydrographic Institute.

The paper presents a method to discriminate ship targets from sea background in focused Single-Look Complex (SLC) Synthetic Aperture Radar (SAR) images. The method is based on Doppler Centroid analysis and it is able to generate an estimate ship velocity. Experimental results are presented showing the application of the method to TerraSAR-X data of the Gulf of Naples, Italy.

This paper analyzes the spatial resolution of bistatic synthetic aperture radar (SAR) in general hybrid configurations, such as air- and spaceborne systems moving along independent trajectories. The gradient method is utilized to point out the effects of the acquisition geometry, namely, position and velocity of both the transmitter and the receiver, on image resolution. This general approach is applied to different realizations of bistatic SAR, such as low-Earth-orbit monostatic-bistatic SAR, spaceborne-airborne bistatic SAR, and a bistatic system consisting of a high-altitude long-endurance illuminator and lower altitude airborne receivers. The main features of the method are then put in evidence, including the derivation of analytical tools to individuate adequate relative geometries for achieving satisfactory resolutions. A comparison to the other proposed techniques for computing the spatial resolution of bistatic SAR is also reported in order to highlight some peculiarities of all presented methodologies. Finally, the good agreement between the image resolution results achieved by recently carried out bistatic SAR experiments and the ones derived by the gradient method strengthens the potentialities of the proposed approach.

The study of a novel navigation system for Unmanned Airborne System (UAS) based on bistatic Synthetic Aperture Radar (SAR) is presented. The innovative bistatic configuration builds on spaceborne radar transmitters and airborne receivers, the latter mounted in a forward-looking geometry. Such approach, impossible or extremely demanding with a monostatic approach, allows one to achieve dual information with two different radar working modes: imaging capability can be in fact coupled with the possibility of moving target indication. The study is particularly suited on one of the most common UAS platforms: a close range, medium takeoff weight, with an endurance of roughly 7 hours and cruise speed of about 50m/s, whose requirements have been identified. The finalization of the study is achieved by the definition of a strawman system concept with different approaches. Four options are identified, with different performance and system complications/challenges. The study herein reported was carried out under ESA contract 22449/09/F/MOS.

This paper aims to investigate the performance of stereoradargrammetric methods applied to spaceborne monostatic-bistatic synthetic aperture radar (SAR) data for digital elevation model (DEM) generation. Stereoradargrammetric techniques for robust DEM generation were successfully experienced on monostatic repeat-pass SIR-A, SIR-B, SIR-C/X-SAR, ERS1/2, JERS-1, and Radarsat data. However, novel configurations achievable by modern spacecraft flying in formation will allow for the attainment of very large baselines between the antennas in a single-pass bistatic geometry so that the height determination accuracy can benefit from both stereo effect and simultaneous acquisition. Five models for relief reconstruction by monostatic-bistatic SAR stereoradargrammetry are presented, and an error budget is assessed for each of them. Results of the sensitivity analysis exhibit metric accuracy, and therefore, the technique could be applied for height reconstruction as a methodology complementary to SAR interferometry.