Aniello Buonanno

A New Measurement Method Based on Music Algorithm for Through-the-Wall Detection of Life Signs

A new measurement method for through-the-wall detection of life signs is proposed hereinafter. The method analyzes the phase modulation that a sinusoidal signal, generated by means of a proper continuous-wave microwave transceiver, undergoes when reflected by the chest periodic displacement associated with breathing. It takes advantage of a suitable spatial smoothing decorrelation strategy applied to the traditional algorithm for MUltiple SIgnal Classification (MUSIC), mandated to single out the spectral components of the received phase signal. With respect to other measurement solutions, already available in the literature and exploiting either the traditional discrete-time Fourier transform, or matched filters, or standard singular value decomposition, the proposed method assures competitive performance in detecting the respiratory activity from the received microwave signal and effective noise/clutter rejection. The results of several tests both in simulated and actual scenarios, i.e., people behind walls in a furnished room, prove the efficacy and reliability of the method also in the presence of critical measurement conditions such as low signal-to-noise ratios and chest displacement associated with shallow breathing.

DESIGN CONSIDERATIONS FOR RADIO FREQUENCY ENERGY HARVESTING DEVICES

Radio Frequency Energy harvesting is a research topic of increasing interest, related to sustainability, which could become a promising alternative to existing energy resources. The paper will show all the activities addressed to design a wideband system to recover wideband energy from electromagnetic sources present in the environment. The main idea is to develop battery-free wireless sensors able to capture the available energy into the mentioned bandwidth. The flnal goal is to realize self-powered Wireless Networks based on Ultra Lower Power | ULP sensors minimizing the need of dedicated batteries. This last feature is particularly attractive in difierent kind of applications, ranging from military to civil cases. A flrst system prototype is shown and discussed. Conclusion follows.

Large Phased Arrays Diagnostic via Distributional Approach

Abstract—A deterministic method for detecting faulty elements in phased arrays is proposed and tested against experimental and numerical data. The solution approach assumes as input the amplitude and phase of the near-field distributions and allows to determine both positions and currents of radiating elements. The corresponding non linear inverse problem is properly solved by exploiting the distributional approach, which allows to cast the initial problem to the solution of a linear one, whose solution is made stable by adopting a proper regularization scheme based on the Truncated Singular Value Decomposition tool. The results fully confirm accuracy of the proposed technique.

Imaging Small PEC Spheres by a Linear

The problem of localizing small inhomogeneities from the knowledge of their scattered field is dealt with. In particular, the case of small perfect electric conducting spheres is of concern, with the scattered field data collected under multistatic/multifrequency/single-view or multistatic/single-frequency/multiview far zone configurations. The multiple scattering between the spheres is neglected, and their locations are represented as the supports of the Dirac delta functions. This allows one to cast the problem as the inversion of a linear integral operator, with the delta functions being the unknowns of the problem. The inversion of this linear integral operator is achieved by means of the truncated singular value decomposition. The performance of the linear inversion algorithm against the model error (i.e., for situations where the multiple scattering is not negligible) is investigated by numerical simulations. Furthermore, the effect of noise is also analyzed by corrupting the data by an uncorrelated additive white Gaussian process.

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A general solution strategy for detecting faulty elements in phased arrays of arbitrary geometries is suggested. The proposed deterministic approach assumes as input data the amplitude and phase of near-field distributions and allows to determine the positions of the faulty elements. In particular, the method is founded on the well known Multiple Signal Classification (MUSIC) method, i.e., a spectral estimation technique. The proposed algorithm is also compared with a recently published method by the same authors, against experimental and numerical data. The results fully confirm the usefulness of the proposed technique, highlighting the advantages and the disadvantages of both methods.

Approach

The problem of developing alternative methods for large arrays indoor testing is discussed. The key point is to generate plane waves across the antenna aperture such to simulate an incoming signal from the far field zone. The main contribution of this communication (with respect to previous publications from the same authors) deals with the realization of a plane wave generator over a 2D antenna under test domain.

A Novel Strategy for the Diagnosis of Arbitrary Geometries Large Arrays

The need to reduce the number of active elements in radar arrays claims for developing new synthesis approaches able to reduce the control points, i.e., the number of transmit/receive modules (TRM) needed to fulfill the design constraints, is presented. As the large part of the TRM costs are related to the active parts (HPA-high power amplifier), a hybrid method for reducing the number of amplitude controls is proposed. This allow the design of new array architectural solutions where the scanning capabilities only rely on phase controls.

Reducing Complexity in Indoor Array Testing

The development of intelligent surveillance systems is an active research area of increasing interest. In recent years, autonomous or semi-autonomous mobile robots have been adopted as useful means to reduce fixed installations and number of devices needed for surveillance of a given area. In this context SELEX Sistemi Integrati is investigating the possibility to use robots-sensors systems to improve the monitoring of large and populated indoor areas. In particular, the joint use of the Swarm Logic and heterogeneous sensors, some installed at strategic points of the infrastructure and other installed on mobile robots, allows the creation of a very dynamic network of cooperating sensors, that is able to ensure a high level of protection and a fast reaction to threats. In this paper an integrated intelligent system based on swarm logic to improve monitoring performance of large critical infrastructures such as airport terminals, warehouses, railway stations, production facilities is presented. The adopted system architecture, consisting of two hierarchical levels, is introduced and discussed. In each of these levels novel aspects, developed by the team, are present.

Reducing the Number of Amplitude Controls in Radar Phased Arrays

The paper deals with the implementation of a suitable technological support to improve the success likelihood of Urban Search and Rescue (USAR) missions. In particular, the adoption of an heterogeneous sensors network for situation awareness and security applications is suggested. The sensor network consists of two types of sensor, mandated, respectively, to through-the-wall radar (TTW) imaging and a vital sign detection (VSD) sensor. Information and measurement data collected by the network are sent to a command and control center for optimal decision making. More specifically, after a brief introduction about the considered network architecture and the TTW radar, the authors present hereinafter a new measurement method, based on Doppler effect and eigenvalue decomposition, for VSD. In particular, thanks to the application of a preliminary demodulation scheme to the received measurement signal, the method is capable of detecting and measuring the phase modulation associated human chest movement. A number of tests, both in simulated and actual measurement conditions, has highlighted satisfying performance in terms of accuracy and reliability, thus suggesting the method as an ideal candidate for the implementation of the VSD sensor.

Mobile sensor networks based on autonomous platforms for homeland security

The paper deals with the problem of detecting, localizing and tracking individuals through the walls by means of radio-frequency based imaging techniques. The authors presents hereinafter a new imaging method for locating and tracking the position of hidden targets (e.g. human bodies in rescue missions) thanks to the use of a multi-sensor approach. A model-based signal processor has been also developed and tested. Numerical examples confirm the effectiveness of the proposed approach and procedures.