A Novel Hybrid Approach for Far-Field Characterization From Near ...

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 53, NO. 6, JUNE 2005

A Novel Hybrid Approach for Far-Field Characterization From Near-Field Amplitude-Only Measurements on Arbitrary Scanning Surfaces Sandra Costanzo, Member, IEEE, Giuseppe Di Massa, Senior Member, IEEE, and Marco Donald Migliore, Member, IEEE

Abstract—A novel hybrid procedure is proposed in this paper for far-field reconstruction from phaseless near-field data. A basically interferometric approach is adopted to retrieve the near-field phase from amplitude-only measurements, which are collected by a simple microstrip circuit used in conjunction with two identical probes moving on the scanning surface. A certain number of sets of complex near-field data is obtained, apart from constant phaseshifts to be computed, one for each set. A nonredundant representation based on the introduction of the reduced field is then adopted to evaluate these shifts, with an accurate and fast convergence to the solution. In order to validate the proposed technique, an X-band prototype using two flanged WR-90 waveguides is successfully designed and tested on a cylindrical geometry for a standard pyramidal horn. Index Terms—antenna measurements, near-field to far-field (NF-FF) transformation, phaseless near-field methods.

I. INTRODUCTION

F

AR-FIELD determination from near zone measurements is a powerful tool for antenna testing and diagnostics [1]. Standard approaches require the knowledge of complex near-field distribution on a prescribed scanning surface, which is collected by a vector receiver and numerically processed to efficiently evaluate far-field patterns [1]. Near-field to far-field (NF-FF) transformation performances essentially rely on the precision of the measurement setup and positioning system, with increasing complexity and cost when dealing with electrically large antennas. As a matter of fact, precise phase measurements are very difficult to obtain at millimeter and sub-millimeter frequency ranges, unless expensive facilities are used. To overcome this problem, new advanced techniques have been recently developed which evaluate the far-field pattern from the knowledge of near-field amplitude over one or more testing surfaces [2]. These methods are extremely advantageous even if an accurate phase evaluation is possible, i.e., at microwave frequencies, since low cost cables and simple receivers can be adopted [3]. However, more complex algorithms and measurement strategies must be considered. Generally speaking, two classes of phaseless methods can be Manuscript received June 17, 2004; revised October 22, 2004 S. Costanzo and G. Di Massa are with Department of Elettronica, Informatica and Sistemistica (DEIS), Universitá della Calabria, 87036 Rende (CS), Italy (e-mail: [email protected]). M. D. Migliore is with the Department of Automation, Electromagnetics, Information Engineering and Industrial Mathematics (DAEIMI), Universitá di Cassino, Cassino, Italy (e-mail: [email protected]). Digital Object Identifier 10.1109/TAP.2005.845218

distinguished, the one based on a functional relationship within a proper set of amplitude-only data, the other adopting interferometric techniques. Concerning the first class of procedures, the most common set of data is given by the voltage amplitude at the output of the probe collected on two surfaces [4], but other sets are possible, such as those including the voltage measured by two different probes on the same testing surface [5]. The determination of the antenna far-field is in practice reduced to a nonlinear estimation problem and stated as the minimization of an amplitude based functional, which however can exhibit some local minima, due to its intrinsic nonconvexity [6]. The effectiveness is therefore related to all available a priori information concerning the source and/or the radiated field [6], [7]. A new formulation has been proposed in [8] which uses the square amplitude distributions over two distinct surfaces as available data, so defining a cost functional which reduces the occurrences of local minima [8]. However, this method requires large computational efforts. Interferometric techniques are based on the algorithm first proposed by Gabor in microscopy [9], and require a reference antenna [10] to be used for transmitting the phase reference to the receiving antenna, wherein the reference signal interferes with that transmitted by the antenna under test (AUT). Simple and fast algorithms are required to evaluate the phase of the AUT signal. Furthermore, the accuracy of standard interferometric techniques is limited by the overlapping between the spectrum of the AUT and the reference antenna [11]. A novel hybrid procedure is developed in this paper which combines all the best features of the recalled phaseless methods. A basically interferometric approach is adopted, but avoiding the use of a reference antenna as in standard interferometry. The phase reference is directly obtained from the field radiated by the AUT, which is collected by two probes on two different points along the scanning curve to interfere by means of a simple microstrip circuit [12]. The proposed methodology leads in principle to the evaluation of the near-field phase on the scanning surface apart from an inessential constant, but some problems arise in the practical application of this novel technique. In fact, difficulties are encountered while fixing the distance between the two interference points along the measurement curve. The Nyquist requirement would prescribe a separation equal to , the usually adopted sampling step in the NF-FF transis, however, formation. A larger distance equal to or required in practice to reduce mutual coupling effects between the scanning probes at a negligible level. This implies a certain

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COSTANZO et al.: NOVEL HYBRID APPROACH FOR FF CHARACTERIZATION FROM NF

number of sets of retrieved near-field phase, resulting from the application of the proposed interferometric technique. Each set includes phase values on different measurement points, apart from a constant phase shift to be determined. The union of these sets gives all near-field phase information along the scanning curve, but a complete characterization obviously requires the evaluation of all unknown phase shifts, one for each set. This problem is solved in [16] for a particular scanning geometry (the plane-polar one) by taking advantages of the analytical properties of the field radiated by the AUT [13], [14]. In particular, a nonredundant representation is adopted which is based on the introduction of the reduced field [15], obtained from the original field after extracting a proper phase function and introducing a suitable parameterization along the observation curve. Following this approach, the radiated field on each scanning line is easily identified from the knowledge of the dimension and shape of the AUT. The procedure is repeated along a proper number of observation curves to cover the whole measurement surface. Again, the phase is known apart from a constant shift along each curve. The evaluation of this unknown shift is straightforward for some scanning geometries, such as the plane-polar one [16], wherein a common measurement point exists for all radial lines. When considering other geometries, such as the cylindrical one, adopted in this paper for experimental validations, the phase shifts can be reconstructed by applying the proposed method to a curve intersecting all others having a common shift. The proposedapproachisahybridprocedureplaced“halfway” between interferometric techniques and functional relationship based methods. In particular, it takes advantages of the interferometric approach to significantly reduce the number of unknowns inthephaseretrievalalgorithm.Althoughthefunctionaltobeminimized is highly nonlinear, the lower number of unknowns, given by the phase shifts, allows an accurate and fast convergence to the solution, acting to decrease the occurrence of local minima. Any problem of false solutions has been experienced in the numerical and experimental elaborations. However, the study of cost functional minimization is an open point and it will be the subject of future investigations. Another important advantage of the proposed procedure is related to the absence of a reference antenna, which gives a simpler and more compact measurement setup. The two probes approach, first proposed in [12] and [16] for a single frequency and the planar/plane-polar scanning geometries, is extended in this work to an arbitrary scanning surface and improved to cover the entire X-band, as it will be outlined in detail. This paper is organized as follows: Section II is devoted to the explanation of hybrid technique; in Section III the experimental setup is described-in particular, a wideband microstrip circuit is used to obtain the interference signal between pairs of measurement points, while two flanged WR-90 waveguides are adopted as probes; in Section IV some experimental data of an extensive investigation are shown, with reference to a cylindrical scanning geometry; conclusions are finally reported in Section V.

Fig. 1.

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Observation curve C with probes positions.

separation between two adjacent interference points, being an integer greater than one. Two identical probes simultaneously moving along the measurement curve (Fig. 1) are used to obtain four amplitude information, namely [12] (1) where

are the complex signals on a pair of interference points along C. Intensity data (1) are processed to give the phase shift (2) by means of the following interferometric formula [12] (3) Let (4) be the field radiated by the AUT on the observation curve C, where parameter s denotes the curvilinear abscissa along C (Fig. 1). For the sake of simplicity, only one component is considered for the radiated field, but an extension to more components can be easily obtained. If we suppose measurement points ( even) are scanned, the application of (3) gives a number of sets of complex near-field data equal to , namely

II. HYBRID TECHNIQUE Let us consider an observation curve C over an arbitrary scanand a ning geometry (Fig. 1), with a sampling step

.. . (5)

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Fig. 2.


Phase-shifts illustration for the case i = 3.

wherein

.. . Fig. 3. Observation curve C for a source included in a sphere of radius a.

(6) where are known quantities and phase shifts are the unknowns to be determined, whose existence is related to the required distance between the probes. Fig. 2 illustrates the meaning of the above phase shifts for the case , which implies the existence of two unknowns, namely and , where refers to the phase value at position given by j-th element of set . Field vector (5) at sampling points is written under the assumption of ideal probes, which makes the field proportional to the output voltage at the probes. , (5) give the If we change set of all fields compatible with measured data

(7)

The reduced field is a (almost) bandlimited function having [14], where is the effective field bandbandwidth width and is an enlargment factor slightly larger than unity which fixes the representation error. A proper choice of paramand leads to approximate the reduced field by a eters simple basis along open curves, or Dirichlet function of sambasis along closed curves, with a minimum number ples. Consequently, the set of all possible fields radiated by the AUT can be approximated by a finite dimensional set, let be , whose dimension is almost equal to the dimension of the optimal basis, i.e., the basis having the minimum number of dimension with a given representation error [14]. Parameters assuring such minimum redundant representation are reported in [15] for the most common scanning surfaces and source geometries. In this paper, we consider a source bounded by a sphere of radius a (Fig. 3), but more general convex surfaces enclosing the AUT can be considered [15]. The reduced field (9) can be represented along the observation curve C (Fig. 3) by a cardinal series of the kind

where represents the possible measured data. The field radiated by the AUT is so given by the intersection [17] (8) is the set of all fields that the AUT can radiate. where In order to solve (8) with respect to the unknown phase shifts , a model for the set is adopted which is based on a nonredundant field representation. This approach substitutes the original field (4) with the reduced field [13]–[15]

(10) where

is the

function or the Dirichlet function, are the positions of nonredundant represents the number of nonredunsampling points, while dant samples falling in the measurement interval. measureThe above relation, discretized in the , can be written in matrix form as ment points, say

(9) (11) and obtained after extracting a proper phase function along the observaintroducing a suitable parameterization tion curve.

where is the array of field values in the nonredundant sampling positions,


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is the corresponding array of field values at the measureis the matrix whose elements ment points and are defined as (12) The range of is the set , i.e., the set of values of all the reduced field that can be radiated by a source of overall dimenmeasurement points. Due to the repsion , evaluated at the resentation error and the presence of noise usually corrupting measurements, data do not belong in general to the range of madoes not trix , or equivalently the intersection point exist. Consequently, the following generalized solution must be adopted: (13) Fig. 4. Measured coupling level between the probes.

In (13), the term “inf” is used as an abbreviation for infimum (i.e., greatest lower bound), while is the distance between the two sets. The proposed solution is the least square approximation of (8), which can be easily evaluated by introducing the . A common way to compute the proprojector onto the set jection onto the range of matrix is to extract its singular value decomposition (SVD) (14) where is the matrix whose columns are the left singular vectors, is the matrix whose columns are the right singular vectors and is a matrix whose nonzero elements are the singular of matrix . The apex in (14) stands for values Hermitian conjugate. onto the range of is defined as The projector (15) is the pseudoinverse of and is where the inverse of matrix , whose nonzero elements are the values . As a consequence of the outlined procedure, near-field phase retrieval involves the finding of

(16) which can be easily performed on a PC. III. X-BAND EXPERIMENTAL SETUP In order to validate the proposed technique, a multifrequency prototype is designed which includes two flanged X-band along each WR-90 waveguides placed at a distance scanning line of the near-field measurement surface. The above distance between the probes is the minimum one which reduces mutual coupling at a negligible level (Fig. 4), while introducing a limited number of unknowns in the minimization scheme. The adoption of a shorter distance is mechanically prevented by the presence of flanges. Waveguides outputs are directly

Fig. 5. Microstrip circuits with interconnected hybrids.

connected to microstrip circuits in Fig. 5, realized on a Diclad mm and dielectric 870 substrate having thickness . Tee junctions with appropriate matching constant transformers are used to exactly have the input signal at the three terminations of each microstrip circuit, with a 90 phase shift along only one branch of the second circuit. The first two square amplitude data in (1) are obtained by directly connecting two measuring diodes to one output of each microstrip circuit, while the latter quantities are probed by two other diodes placed at the appropriate outputs of two hybrids used to interconnect each other the remaining terminations of the circuits (Fig. 5), so performing the sums both in phase and in quadrature. In order to have reliable results on the entire X-band, microstrip circuits have been completely redesigned with respect to the first single frequency prototype in [12], [16]. Furthermore, patch antennas first used in the original formulation [12], [16] have been substituted by two X-band rectangular waveguides in order to satisfy bandwidth requirements. The operational features have been successfully tested by measuring the amplitude and phase of transmission coefficients at the three terminations of each circuit. In the setup configuration, the circuit input is connected to port 1 of Anritsu 37 269C Network Analyzer and the output to be tested is connected to port 2 of the same deis measured by terminating vice. Transmission coefficient

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Fig. 8. Amplitude behavior of outputs from circuit 2. Fig. 6.

Amplitude behavior of outputs from circuit 1.

Fig. 9. Fig. 7. Phase behavior of outputs from circuit 1.

the other two outputs with a pair of 50 matched loads. An excellent agreement between both amplitude and phase of outputs from circuit 1 can be observed in Figs. 6 and 7, with measurements performed in the frequency range from 7 GHz up to 12 GHz. An analogous comparison is illustrated in Figs. 8 and 9 for outputs of circuit 2, with a constant 90 phase shift observed at one termination on the same frequency range.

IV. EXPERIMENTAL RESULTS The effectiveness of the multifrequency probe has been experimentally tested on a standard X-band pyramidal horn having a square radiating aperture of size 5 cm 5 cm. Two rectangular waveguides of aperture dimensions 2.286 cm 1.016 cm have been used as scanning probes. Near-field amplitude-only measurements have been performed on a cylindrical surface of racm, following the scanning movements along and dius shown in Fig. 10. For this scanning geometry, the phase func, the parameterization and the effective bandwidth tion

Phase behavior of outputs from circuit 2.

of the reduced field along the observation curve (a cylinder generatrix) are given as [15]

(17) wherein is the radial distance of the observation point in a spherical coordinate system centered on the sphere of radius a (Fig. 3) and is the free space propagation constant. The radius of the sphere enclosing the AUT has been fixed to cm, has been considered. and an enlargment factor has been chosen between the probes A distance in (5) and (6), so having two phase (Fig. 10) by setting shifts, namely and , to be determined. In order to validate X-band features of the multifrequency probe, two measurements have been considered at distinct freGHz and GHz. For the frequency quencies GHz, a cylindrical grid has been scanned with 37 points along -axis spaced by a quantity cm and azimuthal points at a sampling step .


Fig. 12. Fig. 10.

Cylindrical scanning geometry.

Fig. 11.

Near-field amplitude at one output of the probe.

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Near-field phase at one output of the probe.

Fig. 13. Comparison between exact and retrieved near-field phase along the cylinder generatrix = 90 at f = 8 GHz.

The contour plot of the near-field directly measured at one output of the probe is reported in Figs. 11–12 for both amplitude and phase. Interferometric formula (3) used in conjunction with the two variables minimization procedure (16) has been applied to obtain the retrieved near-field phase, whose agreement with the exact one is illustrated in Fig. 13 for the cylinder generatrix at . The correctness of the minimization procedure is easily demonstrated by the objective functional behavior, plotted in and . Fig. 14 with respect to the unknown variables As a matter of fact, the existence of a unique global solution is proved by the presence of a single minimum. In order to correctly retrieve the near-field phase also in the azimuthal direction, a further measurement has been performed along the circumference lying on the azimuthal plane at , i.e., a curve intersecting all cylinder generatrices. In this case, we have

(18)

Fig. 14.

Objective functional behavior at f = 8 GHz.

while the phase function is constant and can be chosen equal to at from the second relation in (17).

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Fig. 17. Comparison between exact and retrieved near-field phase along the cylinder generatrix = 90 at f = 10 GHz. Fig. 15. Retrieved near-field phase at f = 8 GHz.

Fig. 18.

Fig. 16. Comparison between far-field obtained from exact and retrieved near-field phase (H-plane of E component) at f = 8 GHz.

The retrieving algorithm has been applied to obtain the near-field phase on this curve, so aligning the phase distribution along each generatrix. From the contour plot reported in Fig. 15 it can be easily observed that a good reconstruction is obtained in the central zone of the radiated field, where the signal to noise ratio is sufficiently large. Once retrieved the near-field phase information, complex data have been processed to obtain the radiated far-field. The cylindrical NF-FF transformation procedure based on the cylindrical wave expansion [18] has been implemented by an efficient use of the fast Fourier transform (FFT). The agreement between the far-field obtained from the retrieved and directly measured near-field phase is shown in Fig. 16 for the H-plane. Observe that the retrieved phase becomes noisy with field amplitudes approximately below dB. This is strictly related to the noise level of measurement chamber, which identifies an angular region of validity of about 90 , as can be seen from the near-field amplitude values in Fig. 11. The accuracy of the retrieval scheme can be obviously improved by reducing the background noise level of quiet zone into the anechoic chamber.

Objective functional behavior at f = 10 GHz.

Following a similar procedure, phaseless near-field measureGHz within ments have been performed at a frequency a cylindrical grid of 47 85 points along and , respectively. cm and have Sampling steps been used. The retrieved near-field phase results also in this case to be in excellent agreement with the measured one, as it can be (Fig. 17). The observed for the cylinder generatrix at behavior of the objective functional, showing the unicity of solution, is reported under Fig. 18. Complex near-field data from both measurements and retrieval procedure have been processed by the cylindrical NF-FF transformation to obtain the radiated component) for the H-plane and field reported in Fig. 19 ( successfully compared with result provided by direct near-field phase measurements. V. CONCLUSION A novel near-field phaseless approach is presented in this paper for antenna far-field characterization. Two identical probes simultaneously moving over an arbitrary measurement surface are connected to a simple microstrip circuit for obtaining the necessary amplitude information to be subsequently processed by a simple interferometric algorithm. Depending on the distance between the probes, a certain number of sets


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REFERENCES

Fig. 19. Comparison between far-field obtained from exact and retrieved near-field phase (H-plane of E component) at f = 10 GHz.

of complex near-field measurements is obtained, apart from constant phase-shifts to be determined, one for each set. A nonredundant representation based on the introduction of the reduced field is adopted for defining a proper objective functional to be minimized with respect to the unknown constant shifts. The proposed technique takes advantages of the interferometric approach to significantly reduce the number of unknowns in the functional based phase retrieval algorithm. Although the intrinsic high nonlinearity, an accurate and fast convergence is obtained, without any problem of local minima or false solutions experienced. Furthermore, the absence of a reference antenna gives a more compact and simpler measurement setup. Experimental results are presented with reference to a cylindrical scanning geometry by considering an X-band measurement setup using two flanged WR-90 waveguides together with a properly designed microstrip circuit. A standard X-band pyramidal horn is considered as test antenna for validating the proposed procedure at two different frequencies. Observe that the application of the proposed procedure to antenna testing on a wide frequency range does not require the distance between the scanning probes for each frequency to be changed. The only difference among the sets of complex near-field data (5) at various frequencies is related to their positions (6), which obviously are taken into account for the changed sampling step. for all frequencies as This quantity will not be equal to in the example reported in this paper, but the distance between , where is the probes will be set to a value the wavelength relative to the maximum frequency, in order to satisfy Shannon’s theorem. Even if we have considered a cylindrical geometry, the method can be equivalently applied to other types of scanning surfaces, such as the spiral and spherical ones.

ACKNOWLEDGMENT The authors would like to thank Prof. O. M. Bucci for his useful suggestions.

[1] R. C. Johnson, H. A. Ecker, and J. S. Hollis, “Determination of far-field antenna patterns from near-field measurements,” Proc. IEEE, vol. 61, no. 12, pp. 1668–1694, 1973. [2] O. M. Bucci, G. D’Elia, G. Leone, and R. Pierri, “Far-field pattern determination by amplitude only near-field measurements,” in Proc. 11th ESTEC Workshop on Antenna Measurements, Gothenburg, Sweden, 1988. [3] M. D. Migliore, F. Soldovieri, and R. Pierri, “Far-field antenna pattern estimation from near-field data using a low-cost amplitude-only measurement setup,” IEEE Trans. Instrum. Meas., vol. 49, no. 1, pp. 71–76, Feb. 2000. [4] T. Isernia, G. Leone, and R. Pierri, “Radiation pattern evaluation from near-field intensities on planes,” IEEE Trans. Antennas Propag., vol. 44, no. 5, pp. 701–710, May 1996. [5] R. Pierri, G. D’Elia, and F. Soldovieri, “A two probes scanning phaseless near-field far-field transformation technique,” IEEE Trans. Antennas Propag., vol. 47, no. 5, pp. 792–802, May 1999. [6] O. M. Bucci, G. D’Elia, G. Leone, and R. Pierri, “Far-field pattern determination from the near-field amplitude on two surfaces,” IEEE Trans. Antennas Propag., vol. 38, no. 11, pp. 1772–1779, Nov. 1990. , “Far-field computation from amplitude near-field data on two sur[7] faces: Cylindrical case,” in Proc. Inst. Elect. Eng., vol. 139, 1992, pp. 143–148. [8] T. Isernia, G. Leone, and R. Pierri, “New approach to antenna testing from near-field phaseless data: The cylindrical scanning,” in Proc. Inst. Elect. Eng., vol. 139, 1992, pp. 363–368. [9] D. Gabor, “Microscopy by reconstructed wavefronts,” in Proc. Royal Soc., vol. A, 197, London, U.K., 1949, pp. 454–487. [10] J. C. Bennet, A. P. Anderson, P. A. Mcinnes, and A. J. T. Whitaker, “Microwave holographic metrology of large reflector antennas,” IEEE Trans. Antennas Propag., vol. 24, no. 3, pp. 295–303, May 1976. [11] M. D. Migliore and G. Panariello, “A comparison among interferometric methods applied to array diagnosis from near-field data,” in Proc. Inst. Elect. Eng., vol. 148, 2001, pp. 261–267. [12] S. Costanzo and G. Di Massa, “An integrated probe for phaseless nearfield measurements,” Measurement, vol. 31, pp. 123–129, 2002. [13] O. M. Bucci and G. Franceschetti, “On the degrees of freedom of scattered fields,” IEEE Trans. Antennas Propag., vol. 37, no. 7, pp. 918–926, Jul. 1989. , “On the spatial bandwidth of scattered fields,” IEEE Trans. An[14] tennas Propag., vol. 36, no. 12, pp. 781–791, Dec. 1988. [15] O. M. Bucci, C. Gennarelli, and C. Savarese, “Representation of electromagnetic fields over arbitrary surfaces by a finite and nonredundant number of samples,” IEEE Trans. Antennas Propag., vol. 46, pp. 351–359, 1998. [16] S. Costanzo, G. Di Massa, and M. D. Migliore, “Integrated microstrip probe for phaseless near-field measurements on plane-polar geometry,” Electron. Lett., vol. 37, no. 16, 2001. [17] O. M. Bucci, G. D’Elia, and M. D. Migliore, “An effective near-field farfield transformation technique from truncated and inaccurate amplitudeonly data,” IEEE Trans. Antennas Propag., vol. 47, no. 9, pp. 1377–1385, Sep. 1999. [18] G. M. Golub, Matrix Computation. Baltimore, MD: John Hopkins Univ. Press, 1983. [19] W. M. Leach and D. T. Paris, “Probe compensated near-field measurements on a cylinder,” IEEE Trans. Antennas Propag., vol. 21, pp. 435–445, 1973.

Sandra Costanzo (M’00) received the Laurea degree (summa cum laude) in computer engineering from the University of Calabria, Rende, Italy, and the Ph.D. degree in electronic engineering from the University of Reggio Calabria, Reggio Calabria, Italy, in 1996 and 2000, respectively. Since 1996, she has been with the Research Group in Applied Electromagnetics at the University of Calabria, where she is an Assistant Professor teaching remote sensing and propagation and transmission of electromagnetic waves. Her research interests are focused on near-field far-field techniques, antenna measurement techniques, numerical methods in electromagnetic scattering, antenna analysis and synthesis. Dr. Costanzo received the “Telecom” prize for the Best Laurea Thesis in 1996. In 2001, she was the Conference Chairman of Antenna Measurement Techniques Session at the IEEE AP-S International Symposium.

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Giuseppe Di Massa (M’86–SM’92) was born in Barano d’Ischia, Italy, in 1948. He received the Laurea degree as a Doctor in electronic engineering from the University of Naples, Naples, Italy, in 1973. From 1978 to 1979, he was a Professor of Antennas at the University of Naples. In 1980, he joined the University of Calabria, Rende, Italy, as a Professor of Electromagnetic Waves, where, in 1985, he served as an Associate Professor and, since 1994, has been a Full Professor. From 1985 to 1986, he was a Scientific Associate at CERN, Geneva. In 1988, he was a Visiting Professor at Brookhaven National Laboratory, Long Island, NY. From 1997 to 2002, he was the Dean of the Department of Elettronica, Informatica and Sistemistica and the President of Programming Committee at the University of Calabria. At present, he is the Chairman of the Course in Telecommunication Engineering at University of Calabria, he is the Italian Delegate in the European COST 284 “Innovative Antennas for Emerging Terrestrial and Space-based Applications” and he is the WP leader in the Network of Excellence “Antenna Centre of Excellence” of European Commission. His main research interests are focused on applied computational electromagnetics, microstrip antennas, microwave integrated circuits, Gaussian beam solutions, millimeter wave antennas, near field measurements.

Marco Donald Migliore (M’04) received the Laurea degree (honors) in electronic engineering and the Ph.D. degree in electronics and computer science from the University of Napoli “Federico II,” Naples, Italy, in 1990 and 1994, respectively. He was a Researcher at the University of Napoli “Federico II” until 2001. He is currently an Associate Professor in the Department of Automation, Electromagnetics, Information Engineering and Industrial Mathematics (DAEIMI), University of Cassino, Cassino, Italy, where he teaches adaptive antennas, radio propagation in urban area and electromagnetic fields. He is also a Temporary Professor at University of Napoli “Federico II,” where he teaches microwaves. In the past, he taught antennas and propagation at the University of Cassino and microwave measurements at the University of Napoli “Federico II”. He is also a Consultant to industries in the field of advanced antenna measurement systems. His main research interests are medical and industrial applications of microwaves, antenna measurement techniques, and adaptive antennas. Dr. Migliore is a Member of the Antenna Measurements Techniques Association (AMTA), the Italian Electromagnetic Society (SIEM), the National Inter-University Consortium for Telecommunication (CNIT) and the Electromagnetics Academy. He is listed in Marquis Who’s Who in the World and in Who’s Who in Electromagnetics.