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Networked sensing refers to the capability of multiple wireless terminals to cooperate with the aim of enhancing specific figures of merit, e.g., positioning accuracy or imaging resolution. Regarding radio-based sensing, it is essential to understand when and how sensing terminals should cooperate, namely the best strategy that trades between performance and cost (e.g., energy consumption, communication overhead, and complexity). This tutorial paper revises networked sensing from a wavefield interaction perspective, aiming to provide a general theoretical benchmark to evaluate its imaging performance bounds and to guide the sensing cooperation accordingly. Diffraction tomography theory (DTT) is the method to quantify the imaging resolution of any radio sensing experiment from inspection of its spectral (or wavenumber) content. In networked sensing, the image formation is based on the back-projection integral, valid for any network topology and physical configuration of the terminals. The wavefield networked sensing is a framework in which multiple sensing terminals cooperate during the acquisition process to maximize the imaging quality (resolution and sidelobes suppression) by pursuing the wavenumber tessellation principle. We discuss all the coherent data fusion possibilities between sensing terminals and possible killer applications. Remarkably, we show the possibility that the proposed method allows obtaining high-quality images of the environment in limited bandwidth conditions, leveraging the coherent combination of multiple multi-static low-resolution images.

This paper is intended to summarize the research conducted during the first 2 years of the Dragon 5 project 59,332 (geophysical and atmospheric retrieval from Synthetic Aperture Radar (SAR) data stacks over natural scenarios). Monitoring atmospheric phenomena, encompassing both tropospheric and ionospheric conditions, holds pivotal significance for various scientific and practical applications. In this paper, we present an exploration of advanced techniques for estimating tropospheric and ionospheric phase screens using stacks of Synthetic Aperture Radar (SAR) images. Our study delves into the current state-of-the-art in atmospheric monitoring with a focus on spaceborne SAR systems, shedding light on their evolving capabilities. For tropospheric phase screen estimation, we propose a novel approach that jointly estimates the tropospheric component from all the images. We discuss the methodology in detail, highlighting its ability to recover accurate tropospheric maps. Through a series of quantitative case studies using real Sentinel-1 satellite data, we demonstrate the effectiveness of our technique in capturing tropospheric variability over different geographical regions. Concurrently, we delve into the estimation of ionospheric phase screens utilizing SAR image stacks. The intricacies of ionospheric disturbances pose unique challenges, necessitating specialized techniques. We dissect our approach, showcasing its capacity to mitigate ionospheric noise and recover precise phase information. Real data from the Sentinel-1 satellite are employed to showcase the efficacy of our method, unraveling ionospheric perturbations with improved accuracy. The integration of our techniques, though presented separately for clarity, collectively contributes to a comprehensive framework for atmospheric monitoring. Our findings emphasize the potential of SAR-based approaches in advancing our knowledge of atmospheric processes, thus fostering advancements in weather prediction, geophysics, and environmental management.

This paper explores the potential of an Integrated Sensing and Communication (ISAC) system to enhance search-and-rescue operations. While prior research has explored ISAC capabilities in Unmanned Aerial Vehicles (UAVs), our study focuses on addressing the specific challenges posed by modern communication standards (e.g., power, frequency, and bandwidth limitations) in the context of search-and-rescue missions. The paper details effective methods for processing echoed signals generated by downlink transmissions and evaluates key performance indicators, including Noise Equivalent Sigma Zero (NESZ) and channel capacity. Additionally, we utilize synchronization uplink signals transmitted by User Equipment (UE) to improve target detection and classification of possible victims by fusing SAR imagery with triangulation results from uplink signals. An experimental campaign validates the proposed setup by integrating SAR images of the environment with active localization results, both produced by a UAV equipped with a Software Defined Radio (SDR) payload. Our results demonstrate the system’s capability to detect and localize buried targets in avalanche scenarios, with localization errors ranging from centimeters to 10 m depending on environmental conditions. This successful integration highlights the practical applicability of our approach in challenging search-and-rescue missions.

Previous meta-analyses reported discordant results on the efficacy and safety of thrombopoietin receptor agonists (TPO-RA) as second-line treatment in patients with immune thrombocytopenia (ITP). We conducted a meta-analysis of primary ITP treatment with the TPO-RA Romiplostim, Eltrombopag and Avatrombopag, including additional studies and relevant endpoints. We searched MEDLINE, EMBASE and CENTRAL for randomized clinical trials (RCTs) and cohort studies on TPO-RA in ITP published until December 31, 2018. The primary endpoints were: risk ratio (RR) of treatment failure and bleeding of WHO grade ≥2; rate of remission after discontinuation of treatment. The principal safety outcome was RR and incidence of thrombotic events and liver damage. From 1044 identified records we selected 16 RCTs and 19 cohort studies. RCTs included 909 patients assigned to TPO-RA and 427 to the control arm. Treatment failure was observed in 21% TPO-RA-treated patients and 47% control arm patients (RR = 0.42, 95% CI 0.33–0.53) in RCTs during a median follow-up of 13 weeks, and in 29% TPO-RA-treated patients in cohort studies, during a median follow-up of 69 weeks. The incidence of remission after TPO discontinuation was 18% (5–36%). RR of WHO grade ≥2 bleeding was 0.58 (0.38–0.86) in TPO-RA-treated patients, compared to control arm patients. Adverse events were rare and not significantly different in the two groups of patients. All-cause mortality was significantly lower with TPO-RA (RR 0.21, 95% CI, 0.06–0.68). In conclusion, TPO-RA are effective and safe in patients with ITP, even in the long term.

The paper proposes a flexible and efficient wavenumber domain processing scheme suited for close formations of low earth orbiting (LEO) synthetic aperture radar (SAR) sensors hosted on micro-satellites or CubeSats. Such systems aim to generate a high-resolution image by combining data acquired by each sensor with a low pulse repetition frequency (PRF). This is usually performed by first merging the different channels in the wavenumber domain, followed by bulk focusing. In this paper, we reverse this paradigm by first upsampling and focusing each acquisition and then combining the focused images to form a high-resolution, unambiguous image. Such a procedure is suited to estimate and mitigate artifacts generated by incorrect positioning of the sensors. An efficient wave–number method is proposed to focus data by adequately coping with the orbit curvature. Two implementations are provided with different quality/efficiency. The image quality in phase preservation, resolution, sidelobes, and ambiguities suppression is evaluated by simulating both point and distributed scatterers. Finally, a demonstration of the capability to compensate for ambiguities due to a small across-track baseline between sensors is provided by simulating a realistic X-band multi-sensor acquisition starting from a stack of COSMO-SkyMed images.

This paper proposes a method for efficient and accurate removal of grating lobes in automotive Synthetic Aperture Radar (SAR) images. Grating lobes can indeed be mistaken as real targets, inducing in this way false alarms in the target detection procedure. Grating lobes are present whenever SAR focusing is performed using data acquired on a non-continuous basis. This kind of acquisition is typical in the automotive scenario, where regulations do not allow for a continuous operation of the radar. Radar pulses are thus transmitted and received in bursts, leading to a spectrum of the signal containing gaps. We start by deriving a suitable reference frame in which SAR images are focused. It will be shown that working in this coordinate system is particularly convenient since it allows for a signal spectrum that is space-invariant and with spectral gaps described by a simple one-dimensional function. After an inter-burst calibration step, we exploit these spectral characteristics of the signal by implementing a compressive sensing algorithm aimed at removing grating lobes. The proposed approach is validated using real data acquired by an eight-channel automotive radar operating in burst mode at 77 GHz. Results demonstrate the practical possibility to process a synthetic aperture length as long as up to 2 m reaching in this way extremely fine angular resolutions.

Case presentation: 77-year-old former smoker admitted because of fatigue and abdominal distention. Past medical history positive for two previous hospitalizations for pericardial and pleural effusions (no diagnosis achieved). At admission erythrocyte sedimentation rate was 122 mm per hour. Baseline investigations revealed ascitic, pleural and pericardial effusion. Effusions were tapped: neoplastic cells and acid-fast bacilli (AFB) were not identified, aerobic and mycobacterial culture resulted negative. QuantiFERON TB-Gold test was negative. Total body PET-CT and autoimmunity panel were negative. A neoplastic process was considered the most likely explanation. Before signing off the patient to comfort care, a reassessment was performed and an exposure to tuberculosis during childhood was documented. Because of constrictive pericarditis, pericardiectomy was performed: histologic examination showed chronic pericardial inflammation without granulomas, but Ziehl-Neelsen stain identified AFB and PCR was positive for Mycobacterium tuberculosis complex. Patient was started on anti-TB therapy with resolution of the effusions in the following months. Genes associated with defects in innate immunity were sequences and dentritic cells were studied, but no alterations were identified. Discussion: A Bayesian approach to clinical decision making should be recommended. Interpretation of diagnostic tests should take into account the imperfect diagnostic performance of the majority of these tests. Further studies to investigate genetic susceptibility to tuberculosis are needed. Keywords: Tuberculosis, Diagnostic performance, Bayes

Synthetic Aperture Radar (SAR) imaging is starting to play an essential role in the automotive industry. Its day and night sensing capability, fine resolution, and high flexibility are key aspects making SAR a very compelling instrument in this field. This paper describes and compares three algorithms used to combine low-resolution images acquired by a Multiple-Input Multiple-Output (MIMO) automotive radar to form an SAR image of the environment. The first is the well-known Fast Factorized Back-Projection (FFBP), which focuses the image in different stages. The second one will be called 3D2D, and it is a simple 3D interpolation used to extract the SAR image from the Range-Angle-Velocity (RAV) data cube. The third will be called Quick&Dirty (Q&D), and it is a fast alternative to the 3D2D scheme that exploits the same intuition. A rigorous mathematical description of each algorithm is derived, and their limits are addressed. We then provide simulated results assessing different interpolation kernels, proving which one performs better. A rough estimation of the number of operations proves that both algorithms can be deployed using a real-time implementation. Finally, we will present some experimental results based on open road campaign data acquired using an eight-channel MIMO radar at 77 GHz, considering the case of a forward-looking geometry.

In this paper, we discuss the possibility of generating high-resolution mapping of urban (or extra-urban) environments by the application of synthetic aperture radar (SAR) processing concepts to the data collected by mm-wave automotive radars installed on-board commercial vehicles. The study is motivated by the fact that radar sensors are becoming an indispensable component of the equipment of modern vehicles, being characterized by low cost, good performance, and affordable processing; therefore, in the future, nearly every single vehicle could be potentially equipped with radar devices capable of high-resolution imaging, enabled by application of SAR processing methodologies. Throughout this paper, we aim to discuss the role of SAR imaging in the automotive context under a theoretical and experimental perspective. First, we present the resulting benefits in terms of angular resolution and signal-to-noise ratio. Then, we discuss relevant technological aspects, such as suppression of angular ambiguities, fine estimation of platform motion, and SAR processing architectures, and we present a preliminary evaluation of the required computational costs. Finally, we will present a number of experimental results based on open road campaign data acquired using an 8-channel MIMO radar at 77 GHz, considering the cases of side-looking SAR, forward SAR, and SAR imaging of moving targets.

Atmospheric Phase Screens (APSs) derived from Interferometric Synthetic Aperture Radar (InSAR) observations contain the difference between the tropospheric water-vapor-induced delay of two acquisition epochs, i.e., the slave and the master (or reference) epochs. Using estimates of the atmospheric state coming from independent sources, for example numerical models and/or Global Navigation Satellite System (GNSS) observations, the APSs can be transformed into absolute maps of Tropospheric Delay (Zenith Total Delay or ZTD), related to the columnar atmospheric water vapor content. In this work, a systematic comparison between various APS and ZTD products aims to determine a convenient strategy to go from APSs to InSAR-derived absolute ZTD maps, highlighting the uncertainties and approximations introduced in the entire processing. The main problem to solve is the evaluation of a sufficiently accurate high-resolution master delay map. Different sources of data and two different approaches to derive the master are validated and compared to define the most suitable strategy for meteorological applications. Maps of ZTD obtained by an iterative interpolation of a global atmospheric circulation model values results in being more suited than those derived from the assimilation of GNSS observations into an NWP model. A time average approach to estimate the master map is more robust than the single epoch approach with respect to the choice of the master epoch. Still, the choice of a proper master epoch in the InSAR processing chain as well as that of the maps to be averaged crucially result in the estimate of the master.

The rapid change and expansion of human settlements raise the need for precise remote-sensing monitoring tools. While some Land Cover (LC) maps are publicly available, the knowledge of the up-to-date urban extent for a specific instance in time is often missing. The lack of a relevant urban mask, especially in developing countries, increases the burden on Earth Observation (EO) data users or requires them to rely on time-consuming manual classification. This paper explores fast and effective exploitation of Sentinel-1 (S1) and Sentinel-2 (S2) data for the generation of urban LC, which can be frequently updated. The method is based on an Object-Based Image Analysis (OBIA), where one Multi-Spectral (MS) image is used to define clusters of similar pixels through super-pixel segmentation. A short stack (

Dunes and sand sheets motion natural hazard affect many desertic areas worldwide and require careful assessment to develop effective mitigation plans to protect populated sites, infrastructure, and human activities. The study explores the suitability of Synthetic Aperture Radar (SAR) coherent methods to detect desert area instabilities and estimate sand accumulations displacements. The SAR methods have been applied to long time series of images provided by Sentinel-1. Moreover, the research introduces a novel robust index, named Temporal Stability Index, able to characterize the percentage of stability of a target with time. The work reports the experiments performed on the United Arab Emirates (UAE) and Egypt desertic areas and proves the usefulness of SAR coherent methods to support sand mitigation measures.

The paper addresses the temporal stability of distributed targets, particularly referring to vegetation, to evaluate the degradation affecting synthetic aperture radar (SAR) imaging and repeat-pass interferometry, and provide efficient SAR simulation schemes for generating big dataset from wide areas. The models that are mostly adopted in literature are critically reviewed, and aim to study decorrelation in a range of time (from hours to days), of interest for long-term SAR, such as ground-based or geosynchronous, or repeat-pass SAR interferometry. It is shown that none of them explicitly account for a decorrelation occurring in the short-term. An explanation is provided, and a novel temporal decorrelation model is proposed to account for that fast decorrelation. A formal method is developed to evaluate the performance of SAR focusing, and interferometry on a homogenous, stationary scene, in terms of Signal-to-Clutter Ratio (SCR), and interferometric coherence. Finally, an efficient implementation of an SAR simulator capable of handling the realistic case of heterogeneous decorrelation over a wide area is discussed. Examples are given by assuming two geostationary SAR missions in C and X band.

We study the dissipative propagation of quantized light in interacting Rydberg media under the conditions of electromagnetically induced transparency. Rydberg blockade physics in optically dense atomic media leads to strong dissipative interactions between single photons. The regime of high incoming photon flux constitutes a challenging many-body dissipative problem. We experimentally study in detail the pulse shapes and the second-order correlation function of the outgoing field and compare our data with simulations based on two novel theoretical approaches well-suited to treat this many-photon limit. At low incoming flux, we report good agreement between both theories and the experiment. For higher input flux, the intensity of the outgoing light is lower than that obtained from theoretical predictions. We explain this discrepancy using a simple phenomenological model taking into account pollutants, which are nearly stationary Rydberg excitations coming from the reabsorption of scattered probe photons. At high incoming photon rates, the blockade physics results in unconventional shapes of measured correlation functions.

This paper proposes a simple and fast method to estimate Atmospheric Phase Screens (APSs) by jointly exploit a stack of Synthetic Aperture Radar (SAR) images and a dataset of GNSS-derived atmospheric product. The output of this processing is conceived to be ingested by Numerical Weather Prediction Models (NWPMs) to improve weather forecasts. In order to provide wide and dense area coverage and to respect requirements in terms of spatial resolution of ingestion products in NWPMs, both Permanent Scatterers (PSs) and Distributed Scatterers (DSs) are jointly exploited. While the formers are by definition stable targets, but unevenly distributed, the latter are ubiquitous but stable only within a certain temporal baseline that can vary depending on the operational frequency of the radar. The proposed method is thus particularly suited for C, L, and P band missions with low temporal baseline between two consecutive acquisitions of the same scene: these conditions, that are both necessary to provide the dense space-time coverage required by meteorologists, allow for a reliable and robust estimation of APSs thanks to the intrinsic limitation of temporal decorrelation. The proposed technique integrates Zenith Total Delay (ZTD) products computed on a very sparse grid from a network of GNSS stations to correct for SAR orbital errors and to provide the missing phase constant from the derived APS map. In this paper, the complete workflow is explained, and a comparison of the derived APSs is performed with phase screens derived from state-of-the-art SAR processing workflow (SqueeSAR®).

This paper proposes a statistical model to evaluate the impact of the signal backscattered by low Earth orbiting (LEO) synthetic aperture radar (SAR) and received by GEO-stationary orbiting SAR. The model properly accounts for the bistatic backscatter, the number of LEO-SAR satellites and their duty cycles. The presence of many sun-synchronous, dawn-dusk satellites creates a 24 h periodic pattern in interference that should be considered in the acquisition plan of future geostationary SAR. The model, implemented by a numerical simulator, allows also the prediction of performance in future scenarios of many LEO-SAR. Examples and evaluations are made here for X band.

BackgroundAlthough re-assessment of proliferative activity by K67 evaluation during the course of neuroendocrine neoplasms (NENs) is recommended in selected patients, its impact on patients' management is not clear due to the lack of data supporting this practice.AimTo investigate Ki67 change at time of progressive disease (PD) in entero-pancreatic NENs (EP-NENs).Patients and methodsRetrospective analysis of sporadic EP-NENs which received histological re-assessment after PD once radiologically documented.ResultsForty-three patients were evaluated, including 24 pancreatic NENs (PNENs), and 19 small intestine NENs (SI-NENs). At time of initial histological evaluation, 19 patients had grade 1 (G1) NETs (44.2%), and 24 grade 2 (G2) NETs (55.8%), overall median Ki67 being 3% (range 1%-20%). At time of PD, 13 patients had G1 NETs (30.2%), 26 G2 NETs (60.5%), and 4 had grade 3 (G3) NECs (9.3%), thus resulting in a significant median Ki67 increase (8%, range 1%-70%; p = 0.0006), and a G upgrading in 12 patients (27.9%). A statistically significant Ki67 increase and G grading change at time of PD was observed in PNENs (p = 0.0005 and p = 0.028, respectively). Conversely, no statistically significant change occurred in non-PNENs.ConclusionsIn PNENs with documented PD, Ki67 increase occurs in a significant proportion of patients, providing useful information necessary to choose appropriate therapeutic options.