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This paper presents measurements of Radar Cross Section (RCS) of five Unmanned Aerial Vehicles (UAVs), comprising both consumer grade and professional small drones, collected in a semi-controlled environment as a function of azimuth aspect angle, polarization and frequency in the range 8.2-18 GHz. A first-order statistical analysis of the measured RCSs is firstly reported prior to assessing the radar detection performance on both measured and bespoke simulated data (leveraging the results of the developed statistical analysis), including, as benchmark terms, the curves for non-fluctuating and Rayleigh fluctuating targets.

Radar performance is strongly dependent on the transmitted waveform and its parameters which must be adapted to the surrounding environment, radar mission, goal, and task. Waveform diversity is a relatively new paradigm involving a continuous variation and adaptation of the transmitted signal to dynamically optimize the radar performance and fulfill the more and more stressing requirements. In this context, cognitive radar waveform design in spectrally dense environments is a very challenging and topical problem. This paper deals with the synthesis of signals optimizing radar capabilities while satisfying spectral compatibility constraints. Specifically, the design of radar waveforms, sharing appealing features and ensuring spectral coexistence with other Radio Frequency (RF) systems, is introduced and discussed according to a rigorous framework.

Object: Apelin is an endogenous ligand of the human orphan receptor APJ. Apelin is involved in the regulation of blood pressure, blood flow and central control of body fluid homeostasis in different organs. In placenta vasculogenesis, blood pressure and flow are dramatically important to allow a normal embryonic and fetal growth and development, the aim of the present study was to investigate the immunohistochemical distribution of apelin and APJ in normal placentae throughout pregnancy and in preeclamptic placentae. Methods: Samples from first trimester were obtained from uterine evacuations (n=15) with a gestational age from 5 to 14 weeks, samples from third trimester were obtained from cesarean sections (n=15) with a gestational age from 28 to 40 weeks. Samples of pregnant patients with pre-eclampsia were obtained from cesarean delivery (n=15) and gestational age ranged from 35 to 40 weeks. All the collected specimens were immediately fixed in formalin for immunohistochemistry. Results: We observed a decrease of apelin expression from first to third trimester of gestation in placental cells and stroma of placental villi, in contrast with an increased expression of APJ expression in the cytoplasm of cytotrophoblast cells and in the cytoplasm of endothelial cells. In contrast, in preeclampsia-complicated placentae we observed an intense expression of both apelin and APJ receptor in all placental compartments. Conclusions: Our data seem to confirm that apelin and APJ might play a role in the regulation of fetal development regulating a correct formation of human placenta during gestation. Moreover, their strong expression in preeclampsia-complicated placentae probably suggest their involvement in the onset of this pathology. © Copyright 2006, CIC Edizioni Internazionali, Roma.

The reaction of graphite nanoplatelets (GNPs) with elemental sulphur provides a mechanically stable spongy material characterized by good electrical conductivity and high surface development; such unique property combination makes these novel nanostructured materials very useful for applications in different technological fields. The carbon-sulphur reaction can be accurately investigated by thermal analysis (DSC and TGA) and energy-dispersive X-ray spectroscopy (EDS) combined to scanning electron microscopy (SEM). The thermal treatment required for the formation of electrically conductive mono-sulphur connections among the GNP unities has been investigated.

This paper is focused on the detection and resolution of Unmanned Aerial Vehicles (UAVs) via a multi-channel phased-array radar with emphasis on the challenging situation where multiple targets are unresolved in the range-Doppler domain and closely spaced in angle. An adaptive processor is devised which, after triggering a detection in a given range-Doppler cell, implements a binary decision about the presence of a single or multiple targets. In the former situation, the plain monopulse algorithm is used to estimate the target azimuth whereas, in the latter case, a super-resolution technique is activated to get the angular parameters of the UAVs. The performance of the signal processor is assessed both on simulated and on measured data (endowed by ground-truth) collected by a 12-channel phased-array radar operating in the C-band. The results highlight the capabilities of the architecture to detect the presence of targets, to discriminate the single from the multiple targets scenario, and to resolve the UAVs in angle domain when they are unresolved in range and Doppler.

Due to increasing demands for spectral resources in both communication and radar systems, the radio frequency electromagnetic spectrum is becoming more and more crowded with interfering nuisances. In order to tackle the scarcity of available spectral intervals, in recent years a multitude of sensing algorithms have been developed for improving spectrum sharing. Among these, two-dimensional (2-D) spectrum sensing can be used to obtain space-frequency electromagnetic spectrum awareness. Specifically, this approach makes it possible to optimize the spectrum usage of certain spectrum portions whose occupancy varies both temporally and spatially. In this article, we evaluate the effectiveness of certain space-frequency map recovery algorithms relying on the use of commercially available hardware. To this end, we employ an inexpensive four-channel coherent receiver, using software-defined radio components, for emitter localization. Hence, after proper calibration of the receiving system, the acquired samples are used to evaluate the performance of different signal processing strategies which exploits the inherent block-sparsity of the overall profile. At the analysis stage, results reveal the effectiveness of such algorithms.

Radar operation in a spectrally dense environment is nowadays a very challenging problem due to the increasing demand of spectral resources for defence/surveillance applications, remote sensing capabilities, and civilian wireless services. This article explores the technical feasibility of radar waveforms capable of ensuring spectral coexistence with overlaid emitters via a modern digital arbitrary waveform generator. To this end, a specific hardware-in-the-loop test bed is designed to mimic the perception-action cycle necessary for the agile management of the radio spectrum. Then, a spectrum analyzer (SA) and a digital oscilloscope (DO) are used to demonstrate the compliance of the synthesized waveforms with the theoretical counterparts. In particular, the SA is used to establish if the synthesized waveforms fulfil the spectral requirements forced at the design stage. The DO, instead, is used to assess the adherence of synthesized signals ambiguity function (AF) with the theoretical one. For the considered case studies, results highlight that the synthesized waveforms enable spectral compatibility between radar and communication systems and exhibit desirable AF properties.

This article deals with the effects of power amplifiers (PAs) on radar waveforms designed to ensure spectral compatibility with other radio frequency wireless systems cohabitating in the same frequency band. To this end, a specific hardware-in-the-loop testbed composed of a personal computer, an arbitrary waveform generator, a nonlinear PA, and a signal analyzer is designed. It allows to gather measurements of the amplified signal and to grasp unwanted modifications of its spectral features due to the PA nonlinear distortion. Besides, it permits a quantitative assessment of the discrepancies between the nominal and the actual interference power injected by the radar in the shared frequency bandwidths. To alleviate the spectral distortions induced by the PA and improve spectral coexistence, the use of a digital predistortion (DPD) stage upstream the PA is investigated. Modeling techniques together with parameter inference are discussed and applied to the measured waveforms. The obtained experimental results highlight that pairing a suitable waveform design strategy with DPD processing represents a viable means to mitigate the PA distortions and to realize spectral coexistence.

Two-dimensional (2-D) spectrum sensing is addressed in the context of a cognitive radar to gather real-time space-frequency electromagnetic awareness. Assuming a sensor equipped with multiple receive antennas, a discrete-time sensing signal model formally accounting for multiple snapshots of observations is introduced. Hence, a new signal processing strategy exploiting the inherent block-sparsity of the overall profile is developed to glean a reliable 2-D occupancy awareness. Specifically, the proposed approach resorts to the regularized maximum likelihood estimation paradigm including a term promoting the block-sparsity of the 2-D profile so as to automatically foster this peculiarity in the profile evaluation. Some illustrative examples (both on simulated and measured data) are provided to compare the novel strategy with a relevant counterpart available in the open literature and highlight the effectiveness of the developed approach.

This paper considers the problem of censoring outliers from the secondary dataset in a radar scenario where the sample support is limited. To this end, the generalized regularized likelihood function (GRLF) criterion is used and the corresponding regularized maximum likelihood (RML) estimate of the outlier subset is derived. Since the exact RML estimate involves the solution of a combinatorial optimization problem, a reduced complexity but approximate RML (ARML) procedure is also designed. As to the selection of the regularization parameter, both the expected likelihood (EL) principle and the cross-validation (CV) technique are exploited. At the analysis stage, the performance of the RML and ARML procedure is evaluated based on simulated data in comparison with some previously proposed methods. The results highlight that the RML and ARML algorithm achieves, in general, a satisfactory performance level whereas the previously proposed techniques often experience some performance degradation when the volume of training data is dramatically limited.

This letter studies the conformity with the reciprocity theorem on the measured polarimetric synthetic aperture radar (SAR) data. The problem is formalized via a binary hypothesis test where the reciprocity assumption is tested versus its alternative (absence of reciprocity). The generalized likelihood ratio (GLR) is used as design criterion and the resulting decision rule ensures the constant false alarm rate (CFAR) property. At the analysis stage, the performance of the GLR statistic is analyzed on the simulated data as well as on two different measured data sets (collected by two systems) thus highlighting the effectiveness of the approach.