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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.

Maximum-Power Extrapolation (MPE) techniques adopted for 4G and 5G signals are applied to systems using Dynamic Spectrum Sharing (DSS) signals generated by a base station and transferred to the measurement instruments through an air interface adapter to obtain a controlled environment. This allowed to focus the analysis on the effect of the frame structure on the MPE procedure, excluding the random effects associated to fading phenomena affecting signals received in real environments. The analysis confirms that both the 4G MPE and the proposed 5G MPE procedure can be used for DSS signals, provided that the correct number of subcarriers in the DSS frame is considered.

Structural health monitoring aims to reduce life-cycle costs as well as design constraints of composites due to unforeseen events like impacts with objects. Guided waves are effectively employed in this process because they show a great sensitivity to flaws in the structure and are able to provide a continuous monitoring. However, the complexity of wave propagation in composites suggests a detailed analysis of the diagnostic methodology in every critical aspect to achieve an effective and reliable implementation of the monitoring system. This paper presents the results of the experimental characterization of a methodology for damage identification and localization where permanently-installed sensors are employed to create a network for structural health monitoring. A statistical approach is adopted to select the nodes in the network that are affected by the emerging flaw. Different techniques have then been compared to locate the damage. Results are generally in good agreement with the actual location of the damage, although the best performance is obtained with a density-based algorithm applied to the nodes affected by the damage. Furthermore, measurement uncertainty strongly affects measurement of the damage position, and it is shown that its value depends on the specific detection and localization strategy. Moreover, we show the effect of the identification threshold on the localization procedure, and provide an optimal value.

This paper presents a multivariate analysis of Long Term Evolution (LTE) cellular network physical layers parameters. Supporting a Multiple Input Multiple Output (MIMO) configuration three types of approaches were explored: partitional clustering through k-means algorithm, hierarchical clustering and density-based clustering through DBSCAN. Collected data were clustered with unsupervised blind machine learning methods. Techniques were applied on the same dataset depicting LTE radio layer quantities. Aim of the research is to find similarities among the implementation of the different cluster algorithms used to characterise the performance of the network.

A method based on the use of electromagnetic radiation (EMR) in the radiofrequency band was experimented to eliminate heterotrophic organisms from biofilms encrusting linen canvasses used for paintings. Artificial biofilms were used for exposure to EMR. Biofilms were grown on fragments of canvasses sampled from the backside of a painting. The fragments, after sterilization, were inoculated with several heterotrophic microorganisms previously isolated from other canvasses used for paintings and identified by molecular analyses as the bacteria Bacillus mycoides and Bacillus subtilis, and the microfungi Aspergillus versicolor, Cladosporium cladosporioides, Cladosporium oxysporum and Fusarium oxysporum. The newly formed biofilms resulted to contain the same microorganisms used for the inocula. They were exposed to EMR obtained by an amplitude-modulating radiofrequency sine wave with a train of rectangular pulses with 200 ns repetition time and 10% duty cycle. The exposure protocol consisted of three applications of two hours each, every other day. Denaturing gradient gel electrophoresis analyses carried out on the EMR-treated biofilms showed that all the microorganisms disappeared after the third application. The amplitude of the adopted EMR was not high enough to cause any significant increase in the temperature of the substrates. Therefore, the methodology showed to be non-invasive for the artefacts and its exposure levels not hazardous for operators and the environment compared to other techniques adopted in the field of conservation of cultural heritage. Among the latter techniques, the most common one is based on the use of biocides that, although effective, present problems in all the above-described areas.

Strength of wideband electromagnetic radiations (EMRs) generated by telecommunication systems is a time-varying process typically characterized by a seasonal behavior due to daily and weekly variations of traffic in mobile networks summed to a stationary background generated by constant-power broadcasting systems. Besides a few papers showing the existence of peak and off-peak hours in the daily exposure, there is a significant lack of scientific literature investigating how exposure changes over time, although this is key to the three main objectives: 1) to determine the time intervals when exposure levels are expected to be the highest, 2) to assess worst case exposure and ensure that measurements are run in a conservative scenario to comply with limits enforced by national laws and European guidelines, and 3) to highlight variations in traffic to allocate network resources dynamically to optimize performance. We present a time-series analysis model that makes use of measured data to build a predictor of the exposure to wideband EMR. The main result is that exposure can be predicted by a model composed of three components capturing the average exposure, the daily and half-daily periodicity (seasonal behavior), and the correlations among residuals [modeled by an AR(2) for weekdays and Sunday, and by an AR(1) for Saturday, respectively]. We observed the strength of the periodic components differs more on weekdays compared to weekends. The forecasting model can be particularly useful to predict when exposure is expected to be the highest during the day, so that measurements carried out at that time will be conservative with respect to measurements run at other times of the day, and will therefore serve as the worst case for the assessment of compliance with exposure limits.

The fifth-generation (5G) New Radio (NR) cellular network has been launched recently. The assignment of new spectrum bands and the widespread use of Massive MIMO (MaMIMO) and beamforming techniques for better radio coverage are two major features of the new architecture. They imply both opportunities and challenges, one of the most daring one among the latter ones is the research for methods to assess human exposure to electromagnetic fields radiated by the base stations. The long-term time-varying behavior and spatial multiplexing feature of the MaMIMO antennas, along with the radio resource utilization and adoption of Time-Division Duplexing (TDD), requires that the assessment of exposure to electromagnetic fields radiated by 5G systems is based on a statistical approach that relies on the space and time distribution of the radiated power. That, in turn, is determined through simulations based on the actual maximum transmitted power - defined as the 95th percentile of the empirical distribution obtained from historical data of radiated power - rather than on the nominal one. To ensure that exposure limits are never exceeded, a monitoring and control system (usually referred to as Power Lock (PL)) that limits the transmitted power can be used. In this paper we propose a methodology, independent from the specific technical solution implemented by the manufacturer, to characterize such control systems and determine their capability to limit the average power transmitted over a given time interval to a value that keeps the corresponding average exposure to electromagnetic fields below a specified value. Experimental results show the effectiveness of the methodology and that it can also be used to identify when the PL interacts with the higher levels of the MaMIMO system architecture.

Long-term evolution (LTE) architecture has recently been enhanced by means of the introduction of multi-antenna systems that make use of multiple input multiple output (MIMO) technology, both at the base transceiver station (eNodeB) and user equipment (UE). MIMO can deploy transmission diversity to achieve more robust transmission in poor propagation conditions and spatial multiplexing to increase throughput and thus LTE performance from an end-user perspective. The most recent version of the standard (Release 10) makes up to eight antennae available for the downlink transmission channel. The paper focuses on the most relevant physical-layer parameters used by LTE to optimise a MIMO system. Performance at different frequencies and bandwidths is investigated over a wide urban area in order to study the network behaviour in actual propagation conditions and to verify whether standard prescriptions are satisfied by a fully operational LTE mobile communication system.

One of the challenging tasks for Long Term Evolution (LTE) with Multiple Input Multiple Output (MIMO) configuration is to improve network performance. To efficiently optimize radio layer functionalities, quality characterization of physical parameters is performed with an experimental multivariate analysis. Partitional clustering techniques are used, in particular K-means is implemented to experiment with a non-overviewed, non-hierarchical algorithm. The analysis is carried out adopting R and its interface R study. Data are retrieved with a smart-phone based methodology during a drive test campaign. Measurements are eventually compared to 3rd Generation Partnership Project (3GPP) standard to evaluate the network and its behaviour.

In this paper, a selective laser post-deposition on pure grade II titanium coatings, cold-sprayed on AA2024-T3 sheets, was experimentally and numerically investigated. Morphological features, microstructure, and chemical composition of the treated zone were assessed by means of optical microscopy, scanning electron microscopy, and energy dispersive X-ray spectrometry. Microhardness measurements were also carried out to evaluate the mechanical properties of the coating. A numerical model of the laser treatment was implemented and solved to simulate the process and discuss the experimental outcomes. Obtained results highlighted the key role played by heat input and dimensional features on the effectiveness of the treatment.

A novel technique, effective in eliminating biodeteriogens from biofilms encrusting terracotta artifacts, is presented here. This method is based on the use of high-strength electromagnetic radiation (EMR) in the radiofrequency band. Shards of terracotta from historical pots at the Botanical Garden of Naples, Italy, were used. The shards, after sterilization, were inoculated with several phototrophic microorganisms previously isolated from whole terracotta pots. The newly formed biofilms were exposed to EMR amplitude modulated by a train of rectangular pulses with Tr = 200 ns repetition time and 10% duty cycle. The exposure protocol consisted of three applications of 2 h each, every other day. Denaturing gradient gel electrophoresis analyses conducted on the newly formed biofilms showed that, after the first exposure to EMR, all species in the biofilms but one were still alive. The second exposure resulted in the disappearance of 9 out of 13 species that were initially present on the samples. After the third exposure, all species disappeared. Superficial layers of terracotta from the exposed samples, transferred to a culture medium at 24 °C for 72 h, did not show any re-growing of organisms. Petrographic analyses of the sampleswere carried out before and after the treatments; they showed that exposure to EMR did not cause structural alterations in the treated substrates. Moreover, the amplitude of the EMR that samples were exposed to was not high enough to cause any significant increase in the temperature of the substrates; that is, no thermal effect, which is the most relevant effect when matter or organisms containing water are exposed to EMR, was observed. Finally, the field strength of the EMR showed to be non-invasive for the artifacts and non-dangerous for operators and the environment as compared to other techniques adopted in the field of conservation of cultural heritage.

Radar operation in a spectrally dense environment is nowadays a very challenging problem due to the increasing demand of spectral resources for defense/surveillance applications, remote sensing capabilities, and civilian wireless services. This paper explores the technical feasibility of radar waveforms capable of ensuring spectral coexistence with overlaid radiators via a modern digital Arbitrary Waveform Generator (AWG). To this end, a specific hardware-in-the-Ioop test bed is designed to mimic the perception-action cycle necessary for the agile management of the available radio spectrum. Then the AWG synthesized waveform is measured with a Spectrum Analyzer (SA) in order to demonstrate its compliance with the spectral constraints forced by the design algorithm as well as its fidelity with the computer simulated theoretical counterpart.

Wireless sensor and actuator networks are gaining momentum in the era of Industrial Internet of Things IIoT. The usage of the close-loop data from sensors in the manufacturing chain is extending the common monitoring scenario of the Wireless Sensors Networks WSN where data were just logged. In this paper we present an accurate timing synchronization for TDMA implemented on the state of art IoT radio, such as LoRa, that is a good solution in industrial environments for its high robustness. Experimental results show how it is possible to modulate the drift correction and keep the synchronization error within the requirements.

In the last several years, an increasing number of attacks targeting services running on computing systems have been designed and deployed. Such attacks typically tend to overuse some of the system resources, e.g., CPU, memory, or storage. Current solutions are attack specific, i.e., they are designed for a specific malware or a specific set of malware that share the same resource usage profile and are mainly based on the underlying hypothesis that it is possible to measure the amount of resources used by each service under control. Such possibility is clearly available within modern operating systems, but using such measuring tools is nontrivial and limits their applicability. The advent of user-level virtualization systems may change this attitude. In this paper, we propose and validate a methodology for simplifying the measurements of resources used by a software service. Our approach uses the isolation properties of a containerized virtualization system in order to properly measure all the resources used by a specific service, even if it splits itself into different workers. At the same time, using the resource limitation functionalities provided by the virtualization system, we propose a methodology that can be used to limit the effects of malware by limiting the amount of resources that can be accessed on a system. In order to demonstrate the effectiveness of our approach, we consider the specific case of attacks targeting the overuse of power consumption.

The paper presents the experimental characterization of the maximum electromagnetic field generated by the GSM system measured by two methodologies, with the aim to provide a critical approach to the procedure indicated in the standards for exposure assessment. Results show that maximum exposure is unexpectedly variable over time and that the relative error between the two methodologies depends on the measurement conditions. Based on the experimental evidence, the standard assessment procedure may turn out to underestimate the peak exposure, thus leading to a less conservative estimate of the peak exposure than it is sough for.

Long Term Evolution (LTE) technology gives access to higher bandwidth and assures efficiency at network level for telecommunication operators, providing a reliable and continuous data traffic flow that allows data transmission at extremely high bit-rates. The aim of this paper is to evaluate LTE network performance in an actual urban environment, with emphasis on the downlink channel throughput. The use of statistical methods shows how standard expectations are too high with respect to a real scenario. Also, an analysis is carried out with reference to key parameters for radio optimization that are not defined in the standard and are implemented and defined differently by each vendor.

The paper presents the results of an experimental activity aimed at investigating the statistical properties of the exposure to electromagnetic radiation generated by the GSM cellular system. Many channels radiated by sources at different distance from the measurement point were monitored for seven days to obtain long-term samples of the peak and average rms strength over six minutes. The purpose of the research is to shed new light on the time patterns and amplitude distribution of the exposure level, with the intent to study: (1) the relationship between peak and average strength so that the worst case exposure can related to the average exposure, which is the quantity that measurement standards focus on; (2) variations of exposure with traffic conditions.

Accurate estimation of the vehicle sideslip angle is fundamental in vehicle dynamics control and stability. In this paper two different methods for vehicle sideslip estimation, based on Principal Component Analysis (PCA) and Neural Networks (NN), are presented comparing the procedure responses with full-scale vehicle acquired test data. The estimation algorithms use driver's steering angle, lateral and longitudinal accelerations, wheel angular velocities and yaw rate measured from sensors integrated in a test vehicle, and are validated by comparison with the measurements of the sideslip angle provided by an optical Correvit sensor suitably mounted on board, serving as the reference system in terms of accuracy of slip-free measurement of longitudinal and transverse vehicle dynamics. The procedure results, based on both the original (RAW) and the reduced (PCA) data sets, are compared to the acquired sideslip angle, using the estimated channel as an input for the TRICK tool to evaluate the accuracy of the results and the potential of the estimation process in terms of tire interaction curves.

The paper deals with a new measurement method for through-the-wall detection and tracking of hidden targets (e.g. human bodies in rescue missions) in two-dimensional scenes, by using radiofrequency signals. In particular, the method is based on a multisensor system and exploits an advanced imaging technique, which takes advantages from a regularized linear inversion scheme. Several numerical tests are conducted to assess the performance and capabilities of the method; satisfying values of the difference between estimated and nominal target position are experienced for different investigation domains, number of targets and signal-to-noise ratios. Moreover, experiments in actual measurement conditions and involving a prototype of the multisensor system (based on eleven antennas operating both as transmitting and receiving elements) are also presented, which show the reliability of the method as well as the effectiveness of the implemented measurement strategies.

Structural health monitoring (SHM) based on guided waves (GW) shows great sensitivity to the appearance of damage allowing to assess the structural integrity. However, due to the complexities of GW propagation in composite components and its sensitivity to the measurement instrumentation and technique, a useful implementation of a GW-based monitoring system requires an accurate analysis of the reconstruction methodology and of the collected data as well. This paper deals with the experimental characterization a previously proposed SHM system for the identification of small emerging delaminations in composites using a sparse array of surface ultrasonic transducers. The ultrasonic-GW tomographic technique is presented and experimental tests carried out on a typical composite structure demonstrates the effectiveness of the damage reconstruction and localization. A metrological investigation is then carried out to highlight potential criticalities in the proposed methodology as a preliminary step towards reduction of the measurement uncertainty. Such characterization is based upon statistical analysis of repeated measurements to analyze repeatability of the methodology with the aim to improve the system's decision-making procedure.

In order to assess the performance of digital to analog converters (DAC) the attention is generally focused on the integral nonlinearity (INL). Useful diagnostic tools to detect the causes of poor linearity are the linearity and intermodulation errors, which can be evaluated from INL measurements. Linearity and intermodulation errors highlight and quantify erroneous calibration and unwanted interactions between current sources inside the DAC hardware. Unfortunately, their estimates, especially those related to high order intermodulation errors are characterized by high uncertainty. On the base of their very uncertain value it is difficult to establish if interactions represent relevant factors or not. It is shown that by means of the analysis of variance (ANOVA) the relevance of intermodulation errors can be assessed from a limited set counting a minimum of two INL measurements. ANOVA is in fact capable of distinguishing if the variance in INL measurements has to be addressed to active factors or noise, even if the effect of each factor is widespread upon different elements of the INL array and in different combinations with the other factors.

Regulations and laws about exposure to electromagnetic fields (EMFs) require that it constantly remains below some fixed limits. It is demanded therefore that the experimenter make a decision about the conformity of measured values to such limits. The statement may indeed be reliable only up to a certain degree because of the uncertainty that affects the available measurements; thus, the possibility that the wrong decision is made because of the limited amount of knowledge available about the process must be considered. Ultimately, the task is to determine the most reliable condition of the EMF while minimizing the cost caused by a wrong decision. Based on a distributed system of mobile probes, a fuzzy logic approach to a decision-making procedure is presented in this paper and applied to the results obtained during a measurement campaign.

Frequency measurement of sinusoidal signals corrupted by noise is dealt with. A new time-domain, digital signal processing method, based on an enhanced version of the zero-crossing technique, is in particular proposed. To obtain the desired frequency value, the method exploits the histogram of time intervals between consecutive zero-crossing events, and works with success in the presence of zero-mean additive noise. Several tests conducted on simulated and actual sinusoidal signals highlight the good performance of the method also in critical noise conditions, which make high-end measurement instruments like digital counters poorly fail. Moreover, the obtained results concur with those granted by competitive digital signal processing proposals operating in the frequency domain. With respect to these latter, the main advantage of the method relies on the limited computational resources required, which suggests its implementation even in low-performance processing devices for the realization of cost-effective measurement instruments.

The first fundamental step within a research project aiming at the 3D reconstruction and rendering of the accident scenes involving motor vehicles is accounted for. More specifically, the paper deals with the problem of accurately locating and georeferencing both the considered scenario and all involved elements (such as cars, debris, peeling out and so on) of interest for Road Safety experts. A new method, based on Kalman filtering, is presented for enhancing the preliminary estimates, obtained through low-cost GPS devices, of the position of proper scene markers. To this aim, the distances between the markers is measured through a low-accuracy device (as an example, an ultrawideband radar) and the achieved results are used as feedback to improve the estimate of markers positions. Preliminary results, obtained in numerical tests, are presented to prove the feasibility of the method, thus suggesting its implementation in an actual measurement station

Radiated emissions from arcing between pantograph and overhead wire in electrical transportation systems extend up to the frequency bands currently used for telecommunications and may therefore affect quality of telecommunication systems. The paper investigates on the time and frequency characteristics of the disturbances. Transient amplitude, rise time and pulse duration were measured in the time domain to obtain the associated empirical distributions; the power spectrum and the frequency content were calculated in the bands of interest; finally a time–frequency representation has been used to observe the evolution of the power spectrum over time and determine the location of the main contributions. Measurement of the channel power has also been carried out to investigate on the relevance of the disturbance power for some bands of interest for telecommunication services.