Performance analysis of reconstruction algorithms for breast microwave imaging

The problem of localizing a scatterer, which represents a tumor, in a homogeneous circular domain, which represents a breast, is addressed. A breast imaging method based on microwaves is considered. The microwave imaging involves to several techniques for detecting, localizing and characterizing tumors in breast tissues. In all such methods an electromagnetic inverse scattering problem exists. For the scattering detection method, an algorithm based on a linear procedure solution, inspired by MUltiple SIgnal Classification algorithm (MUSIC) and Time Reversal method (TR), is implemented. The algorithm returns a reconstructed image of the investigation domain in which it is detected the scatterer position. This image is called pseudospectrum. A preliminary performance analysis of the algorithm vying the working frequency is performed: the resolution and the signal-to-noise ratio of the pseudospectra are improved if a multi-frequency approach is considered. The Geometrical Mean-MUSIC algorithm (GM- MUSIC) is proposed as multi-frequency method. The performance of the GMMUSIC is tested in different real life computer simulations. The performed analysis shows that the algorithm detects the scatterer until the electrical parameters of the breast are known. This is an evident limit, since, in a real life situation, the anatomy of the breast is unknown. An improvement in GM-MUSIC is proposed: the Eye-GMMUSIC algorithm. Eye-GMMUSIC algorithm needs no a priori information on the electrical parameters of the breast. It is an optimizing algorithm based on the pattern search algorithm: it searches the breast parameters which minimize the Signal-to-Clutter Mean Ratio (SCMR) in the signal. Finally, the GM-MUSIC and the Eye-GMMUSIC algorithms are tested on a microwave breast cancer detection system consisting of an dipole antenna, a Vector Network Analyzer and a novel breast phantom built at University of Bologna. The reconstruction of the experimental data confirm the GM-MUSIC ability to localize a scatterer in a homogeneous medium.

Mission synthesis of sine-on-random excitations for accelerated vibration qualification testing

In most real-life environments, mechanical or electronic components are subjected to vibrations. Some of these components may have to pass qualification tests to verify that they can withstand the fatigue damage they will encounter during their operational life. In order to conduct a reliable test, the environmental excitations can be taken as a reference to synthesize the test profile: this procedure is referred to as “test tailoring”. Due to cost and feasibility reasons, accelerated qualification tests are usually performed. In this case, the duration of the original excitation which acts on the component for its entire life-cycle, typically hundreds or thousands of hours, is reduced. In particular, the “Mission Synthesis” procedure lets to quantify the induced damage of the environmental vibration through two functions: the Fatigue Damage Spectrum (FDS) quantifies the fatigue damage, while the Maximum Response Spectrum (MRS) quantifies the maximum stress. Then, a new random Power Spectral Density (PSD) can be synthesized, with same amount of induced damage, but a specified duration in order to conduct accelerated tests. In this work, the Mission Synthesis procedure is applied in the case of so-called Sine-on-Random vibrations, i.e. excitations composed of random vibrations superimposed on deterministic contributions, in the form of sine tones typically due to some rotating parts of the system (e.g. helicopters, engine-mounted components, …). In fact, a proper test tailoring should not only preserve the accumulated fatigue damage, but also the “nature” of the excitation (in this case the sinusoidal components superimposed on the random process) in order to obtain reliable results. The classic time-domain approach is taken as a reference for the comparison of different methods for the FDS calculation in presence of Sine-on-Random vibrations. Then, a methodology to compute a Sine-on-Random specification based on a mission FDS is presented.