Synthetic Bandwidth Radar for Ultra-Wideband Microwave Imaging Systems

698 IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 62, NO. 2, FEBRUARY 2014

Synthetic Bandwidth Radar for Ultra-WidebandMicrowave Imaging Systems

Yifan Wang, Amin M. Abbosh, Senior Member, IEEE, Bassem Henin, and Phong Thanh Nguyen

Abstract—A synthetic bandwidth radar as an approach to buildultra-wideband (UWB) imaging systems is presented. The methodprovides an effective solution to mitigate the challenges of UWBantenna’s implementation with ideal performance. The proposedmethod is implemented by dividing the utilized UWB into severalchannels, or sub-bands, and designing an antenna array that in-cludes a number of antennas equal to the number of channels. Eachof those antennas is designed to have excellent properties acrossits corresponding channel. As part of the proposed approach, atwo-stage calibration procedure is used to accurately estimate theeffective permittivity of a heterogeneous imaged object at differentangles and the phase center of each antenna for accurate delay timeestimation. When imaging an object, each of the antennas trans-mits and captures signals only at its channel. Those captured sig-nals are properly combined and processed to form an image of thetarget that is better than the current systems that use array ofUWBantennas. The presented method is tested on breast imaging usingthe band 3–10 GHz via simulations and measurements on a real-istic heterogeneous phantom.

Index Terms—Microwave antenna, microwave imaging, syn-thetic bandwidth, ultra-wideband (UWB).

I. INTRODUCTION

R ECENT years have witnessed an increased interest inusing wideband microwave techniques to obtain internal

images of various dielectric objects [1]–[6]. One of the exten-sively researched areas is the ultra-wideband “breast radar”aiming at the detection of breast’s tumor by using the bandfrom around 3 to 10 GHz [5], [6]. The traditional approach inthose systems is to use an antenna or array of antennas that isdesigned to operate across the whole band of interest.One of the critical components that decides the success, or

otherwise, of UWB imaging systems is the antenna that couplesthe microwave signal from the transmitter into breast tissues[6]. The characteristics of the UWB antenna strongly influencethe system’s reliability and imaging resolution. To guarantee ahigh quality image, the utilized UWB antenna should: 1) haveexcellent impedance match; 2) have fixed phase center anddistortion-less impulse response [7]; 3) have constant transmit

Manuscript received May 30, 2013; revised September 16, 2013; acceptedOctober 29, 2013. Date of publication November 06, 2013; date of current ver-sion January 30, 2014. This work was supported by the Australian ResearchCouncil in the form of the Grant FT0991479.The authors are with School of Information Technology and Electrical Engi-

neering, The University of Queensland, Brisbane, QLD 4072 Australia (e-mail:[email protected]).Color versions of one or more of the figures in this paper are available online

at http://ieeexplore.ieee.org.Digital Object Identifier 10.1109/TAP.2013.2289355

efficiency [8]; 4) have frequency-independent radiation pattern;and 5) be compact in structure. However, it is challenging todesign antennas that meet all those harsh requirements acrossmore than 100% fractional bandwidth as needed by UWBimaging systems. Thus, the utilized antennas in UWB imagingsystems are usually designed with compromised properties thatact as microwave filters and distort the transient radar pulse[9], [10]. Such weaknesses of antennas in the imaging systembring clutter within the resolution cell and lower the possibilityof a successful detection of early tumors [11]. The tradeoffsthat naturally exist among various antenna properties and theirdesign limitations are summarized in [12].To overcome the challenges in UWB antenna design, the syn-

thetic bandwidth approach is presented. It divides the utilizedUWB in several channels. An antenna is then designed to op-erate in one of those channels. The scattered signals from theimaged object at all the channels are then properly combinedand processed to produce an image that is equivalent to usingan ideal UWB antenna. The method is successfully tested on abreast imaging system that operates across the band from 3 to10 GHz.

II. SYNTHETIC BANDWIDTH RADAR CONCEPT

The synthetic bandwidth radar (SBR) technique refers tousing a number of narrowband antenna units to assemble anequivalent wideband antenna that cannot be realized by anyconventional design method. The technique aims to synthesizeseveral broadband antennas working separately over adjacentsub-bands to generate a UWB signal captured by a virtualequivalent antenna (VEA) working with ideal properties overthe whole UWB. By using this concept, the difficulties ofdesigning high-quality UWB antennas are alleviated as eachindividual antenna is optimized within a limited sub-band.The schematic diagram of the proposed synthetic bandwidth

technique is shown in Fig. 1. The whole frequency range fromto is divided into U adjacent channels. Each channel con-

tains an antenna unit connected to a preselection filter that op-erates within a sub-band from to . Bysuccessively placing the U- antenna units in a specified positionsurrounding the target, the signals received from the antennaunits are recorded, combined and then processed bya signal integration module. The module synthesizes these sig-nals and generates an integrated signal as if it is collectedfrom a virtual equivalent antenna (VEA) operating over the en-tire band. A signal integration mechanism to combine the threesub-channels is implemented during the image reconstructionprocess. Due to the different feeding-to-radiation delay between

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WANG et al.: SBR FOR UWB MICROWAVE IMAGING SYSTEMS 699

Fig. 1. (a) Bandwidth synthetic radar, and (b) system with channels.

Fig. 2. UWB imaging system using synthetic bandwidth method.

the antenna units, the inter-channel amplitude and phase distor-tions need to be compensated by a pre-test calibration procedureduring the signal integration process.

III. BREAST IMAGING SYSTEM USING SBR

Fig. 2 shows the configuration of a UWB breast imagingsystem using the concept of SBR. The whole working band-width is divided into three sub-bands . Three sub-bandantenna units (Ant-A, Ant-B, and Ant-C) surround the imagedbreast with angular intervals. The cylindricalscanning mechanical subsystem and other hardware infrastruc-ture employs the same developed model presented in [13], [14].Since no matching medium is used between the antennas andthe imaged object, a proper windowed processing method is em-ployed to cancel the effect of reflections at the skin-free-spaceinterface. Each antenna unit directs its mainbeam towards theimaged body, whereas their phase centers are positioned at a

Fig. 3. (a) Scan mechanism of the system using SBR, and (b) 3N scanningpositions surrounding the imaged body.

constant distance from the central axis of the rotationtable. The collected signals from the three adjacent sub-bandsare connected to Channel #1 to #3 of a vector network an-alyzer (VNA), which is R&S ZVA24 in our case. The mea-sured S-parameters ( , , and ) are stored as data forpostprocessing.Fig. 3 illustrates the scan mechanism of this imaging system.

Three parallel A-scans are implemented by collecting the sig-nals from the antenna units over three sub-bands in the fre-quency domain. The B-scans are implemented by rotating all an-tenna units and extracting the signals from 3N positions evenlydistributed along the circular track. The number of scanning po-sitions is assigned as an integer multiple (N) of the number ofchannels (U) so that all the antennas scan the same positionsaround the imaged object. Thus, the phase centers of each an-tenna units traverse 3N positions at :

(1)

The reflection coefficient measured at each scanning positionby the antenna unit operating in -channel is recorded as

in the vector format

(2)


TABLE IDESIGN PARAMETERS OF THE THREE ANTENNAS

IV. ANTENNA UNITS DESIGN

Three antenna units, Ant-A, Ant-B, and Ant-C, are designedto operate within the assigned low,medium, and high sub-bands.All the sub-band antennas are designed to achieve: a) morethan 20 dB return loss; b) moderate to high gain values in themainbeam direction; c) stable radiation pattern concerning thedirection of the mainbeam across the sub-band; d) flat groupdelay; and (e) fixed phase center. Their frequency coverage andchannel index are shown in Table I.Three tapered slot antennas (TSA) are designed to meet

the above requirements on the substrate Rogers RT6010LM(dielectric constant , thickness mm). Thedesigned Ant-B and Ant-C antennas employ a tapered slotstructure on one side of the substrate and a microstrip feederon the other side. The coupling between that feeder and theradiator is achieved using a suitable microstrip-to-slotlinetransition [15]. Ant-A employs an antipodal structure [16] thatis connected to a partial ground on one layer and a microstripfeeder at the other layer. The physical dimensions of antennasoperating at the upper channels (Ant-B and Ant-C) are furtherreduced by using double substrate layers covering both sidesof the radiator, which is also helpful to maintain a fixed phasecenter according to the study in [17].During the antennas’ optimization, their time-domain be-

havior is given a significant emphasis. The antenna’s completebehavior, including time-domain response, can be described bythe linear system theory. To that end, the frequency-domainsignal link suggested by the method in [8] is simulated withtwo identical antennas allocated face-to-face along a 180-mmdistance. The transmission coefficient between the two an-tennas is calculated and interpreted during the antennaoptimization process. Based on the simulation in eachsub-band , the normalized transmission loss

and relative group delay are definedas

(3.1)

(3.2)

is the mean group delay created by

(3.3)

To achieve distortionless properties for all the antennas, theoptimization aims to realize an even transmission loss and min-imized the variations in the group delay. The optimized dimen-sions of the antennas and their frequency allocations are listedin Table I.Fig. 4(a) shows the simulated and measured reflection co-

efficient of the antennas. They feature a 15 dB reflectioncoefficient over the entire operational UWB. As depictedin Fig. 4(b), the radiation pattern of each antenna demon-strates nearly frequency-independent characteristics across itssub-band. Fig. 4(c) illustrates that the gain of each antennavaries slightly with frequency. The gain for the three antennasvaries between 2 and 4 dBi. Fig. 4(d) shows a flat group delay ineach antenna with less than 0.2-ns peak–peak variation. Fig. 5illustrates the fabricated antennas with their phase centersindicated at the narrowest part of the slot as explained in [17].

V. TWO-STAGE CALIBRATION

To get accurate imaging results, the phase center of each an-tenna should be located. Moreover, the effective permittivity ofthe heterogeneous imaged object in different angular directionsand at all the utilized channels should be estimated. To that end,a two-stage calibration procedure is needed.A diagram showing one of the antennas operating at channel

and facing an imaged body with unknown permit-tivity value is depicted in Fig. 6. The phase center ofthat antenna is located at the point . The signal propagationlink includes the path inside ( to ) and outside ( to ) thebody. Since the conventional VNA calibration is conducted onthe feeder of the antenna, the time that signal travels in the struc-ture of the antenna unit needs to be separated from othertimed delays for an accurate estimation of the target’s position.If the reference signal for the th step-frequency pulse is

(4.1)

The reflected signal from hypothetic target after a round tripdelay can be represented as

(4.2)

where is the one-way-trip delay from the feeding portto the hypothetical point in the imaged region. Its value alsodepends on the channel index with which the reference pulseis emitted. Using the approach in [18] as well as the analysis ofthe feeding structure, the total one-way trip delay is

(5)

is the effective permittivity value of the imaged body de-fined by the mean group velocity over the sub-bandfrom to :

(6)


Fig. 4. (a) Reflection coefficients, (b) radiation patterns at different frequenciesin the E-plane, (c) gain, and (d) group delay of the antennas.

Obviously, the time-delay in (5) is not only a function of thehypothetical point position , but also depends on the channel

Fig. 5. Fabricated antennas. For Ant-B and Ant-C, superstrates are removed.

Fig. 6. Analytical model for SBR system including the structure of sub-bandantenna units in each channel.

Fig. 7. Two-stage calibration at each channel. (a) stage-I, (b) stage-II.

at which the system operates. With the given hypothetical pointposition, the corresponding time-delay cannot be determinedfrom (5) and (6) due to two unknown coefficients andin each channel . Due to the complexity of determining thesetwo coefficients for many factors, such as the non-straight pathfor the signal penetration inside the breast, the unknown delayin the feeding structure of the antenna, etc., a two-stage calibra-tion is necessary to estimate their values.As shown in Fig. 7, two calibrations in each channel are con-

ducted by mounting small calibration targets at two differentpositions. At stage-I, the target (RCS-1) is placed in front ofthe antenna’s aperture with a distance of to the antennaphase center. At stage-II, the target (RCS-1) is removed andthe target (RCS-2) is inserted behind the imaged breast with

distance from the phase center. To avoid any couplingbetween the calibration target and antenna’s body, both RCS-1and RCS-2 are small and positioned in the far-field region of theantenna.


To get the values of the time-delays from these two-stage cal-ibrations, the following five steps are performed on the time-do-main signals that are generated in practice in the VNA using theinverse Fourier transform IFT:1) Remove both targets RCS-1 and RCS-2 and collect thetime-domain signal .

2) Insert target RCS-1 and collect the time-domain signal.

3) Remove target RCS-1 and then insert target RCS-2, andcollect the time-domain signal .

4) Conduct the calculation:

(7.1)

(7.2)

(7.3)

(7.4)

is the Hilbert transfer of the time-domain signal,is the reflection from target RCS-1, and is the

reflection from target RCS-2.5) Record the time delay where reaches the max-imum and where reaches the maximum.

The estimated time-delays from these two-stage calibrationsare recorded as and in each channel. The relationsbetween the measured time-delay and the two un-known coefficients are

(8.1)

(8.2)

By solving these two equations, the two unknown coefficientsin (5) can be determined. To accurately estimate those param-eters at different angular directions, each calibration procedureis repeated at various orientations of the heterogeneous imagedbreast.

VI. IMAGING RECONSTRUCTION ALGORITHM

The value of electrical path from an arbitrary pointto the antenna feeding port in all channels can be calculated

from (5):

(9)

The image reconstruction algorithm is developed based onthe nonuniform IFTmethod reported in [14]. Beginning with thethree-dimensional signals collected as , the procedurefor image reconstruction is as follows:1) Find the data from the subtraction of adjacent-angle signals:

(10)

2) The amplitude of the signals is normalized to compensatefor the imbalance in the antenna gain in each channel:

(11)

3) Perform the calibration steps in Section V to obtain thetime-delay of the antennas and the average permittivity ofbreast phantom in each sub-band, and establish the equa-tion for the electrical distance .

4) Divide a square area including the cross-section of the im-aged body into cells having centers at .

5) By assuming that the target is located at, match-filter the normalized difference signals by

introducing the following correlations:

(12)

6) Once the multiplied signal is correlated with frequency,channels, and positions of circular scanning, theimage can be generated:

(13)

7) Plot the calculated function using variousintensity colors. High probability of the presence of a targetis indicated by a large value of .

By looking at (13), the signal integration among differentsub-bands (mentioned in Section II) is implemented duringthe correlation calculation. The signal collected from the SBRunits and the signal collected from the assembled VEA

have the relation

(14)

For the signal in the format of discrete frequency samplingin (2), (13) can be reshaped as

(15)

It is worth mentioning that the radar ranging calculations in(5), (6), and (8) is speculated assuming an ideal geometry, whichis not the accurate description of the signal transmit/scatteringbehavior under realistic environment, i.e., heterogeneous object


Fig. 8. (a) Heterogeneous breast voxel model in simulation environment, and(b) cross-section view of the breast slice where the tumor is located.

that varies the phase center of the antennas in different direc-tions slightly, with three-dimensional structure. Therefore, wenoticed that using the estimated parameters pro-duce a blurry image in some cases. To get a focused image, theestimated parameters are experimentally adjusted ( 10%)around the estimated values in the imaging algorithm.

VII. SIMULATIONS

To validate the proposed method, simulations are conductedusing a volume of a realistic breast model and the designedantennas in the full-wave simulation environment (Microwavestudio CST suite 2012). As shown in Fig. 8(a), the breast voxelmodel is imported from [19] with 25% glandular tissue andlong- and short- axis of 136mm and 96mm, respectively (BreastID: 071904). The breast model includes a roughly 1.5-mm-thickskin layer, and a 15-mm-thick subcutaneous fat layer at the baseof the breast. The heterogeneous tissue distribution and theirdispersive dielectric properties are assigned according to themeasured results in [19]. An object of 10-mm diameter polyhe-dron representing the cancerous tumor ( ;

S/m [6]) is inserted inside the voxel model at the indicatedposition. Fig. 8(b) illustrates a cross-section view of the breastvolume indicating the location of the cancerous tumor. In thesimulations, the volume of the breast model that includes thecancerous tumor was utilized in the computations.The simulation included antenna positions around

the imaged body in a circular track. The antennas phase cen-ters were positioned at the same distance mmfrom the central axis of the voxel model. Three different ex-cited signals were specified for each sub-band according to thefrequency allocations in Table I. The simulation was run with

iterations for each antenna unit at each posi-tion, and the computed signals were recorded for imaging re-construction. To emulate the realistic situation with noise back-ground, a Gaussian white noise was added to the signal for a10-dB signal-to-noise ratio (SNR). To compare the proposedSBR method with the conventional method that uses one UWBantenna, the simulations were repeated but in this time, a singleUWB antenna was used to capture the data. The antennas usedfor the comparison are tapered slot UWB antennas with bandcoverage of 3 to 10 GHz [20], [21].Using (9)–(15), the captured signals were processed and

the images were produced. Fig. 9(a)–(c) illustrates the re-constructed images. It can be observed that proposed method

produces an image with a better quality, lower clutters, andhigher contrast compared with using a single UWB antenna.The lower internal clutters in the image produced using theproposed SBR method means a lower rate for the false positivesthan using a single UWB antenna.To quantify the improvement in the produced image using the

proposed method compared with the traditional single-antennaapproach, the metrics suggested by [22] is utilized. The qualityfactor is defined as the ratio of the average intensity value ofpoints located in the tumor region over the points in normalbreast tissue surrounded. A higher value of Q implies the tumorintensity is more intensive than the background regions:

(16)

where denote the mean operation: ; .The calculated factor for the three images in Fig. 9 are

1.65, 1.39, and 1.43 for the SBR method, traditional methodusing antenna of [20] and antenna of [21], respectively. Thus,the improvement is around 15%. Of course, this improvementvalue increases or decreases depending on the utilized antenna

and the selected region .

VIII. EXPERIMENTAL RESULTS

To experimentally test the proposed method, an artificial het-erogeneous breast phantom (diameter of 108 mm) was fabri-cated using a mixture of materials (water, gelatin, oil, salt, andsurfactant) following the procedure in [23]. The fatty tissue ofthe phantom has the dielectric properties ( ;

) that change across the frequency band (3–10 GHz)according to Debye model [24]. To emulate the heterogeneousstructure, glands and other fatty types are created and distributedrandomly within the phantom. Those tissues have 50%–70%higher permittivity values than the main fatty layer. The in-serted tumor (diameter of 8 mm) has the average properties of( ; ) at 6.5 GHz [24].Fig. 10 shows the artificial phantom installed on the devel-

oped testbed. The three fabricated antennas are installed on threemechanical arms and used to scan this phantom fromcircular positions. An experiment using 48 positions is also per-formed to see the effect of increasing number of scanning posi-tions, or number of antennas, on the quality of the images. Thedistance between the antennas’ phase center and the axis of ro-tation is 85 mm. A 12-mm-diameter steel ball is used for thetwo-stage calibration.The reconstructed images from the experiments are shown

in Fig. 11(a), (c). For comparison, the images using the con-ventional single-antenna method covering the same total band(3–10 GHz) and employing the antenna designed according to[21] are shown in Fig. 11(b), (d)If the images obtained using36 scanning positions are compared with those obtained using48 positions, it would become clear that using a large numberof scanning positions results in a better quality for the imagewith less clutters. The improvement when using the proposedSBR method is significant as the image has one clear targetwhich is the tumor. The clutter that appears at the left handside of the image when using 36 scanning positions which may


Fig. 9. Reconstructed image using (a) SBR method, (b) conventional methodwith corrugated TSA, and (c) conventional method with elliptical-cut TSA.

cause a false positive, has much less contrast in the image ob-tained using 48 positions. It is to be noted that the improve-ment in using the proposed method compared with the tradi-tional approach is higher in the measurements (Fig. 11) thanthat in the simulations (Fig. 9). These results prove the robust-ness of the proposed method under realistic environment where

Fig. 10. Testbed for the SBR method.

Fig. 11. Constructed image using (a) SBR method with 48 antenna positions,and (b) conventional single-UWB antenna method with 48 antenna positions(c)SBR method with 36 antenna positions, and (d) conventional single-UWB an-tenna method with 36 antenna positions. White circles represent the exact loca-tion of tumor.

not all the aspects of such an environment are under control orwell-known.

IX. CONCLUSION

A UWB imaging approach using synthetic bandwidth radartechnique has been presented. Instead of designing a singleUWB antenna with compromised characteristics, several an-tennas are designed to operate at specific sub-bands that sumsto the required UWB. The design of those antennas is opti-mized to emulate the use of an ideal ultra-wideband antenna. Atwo-stage calibration method is proposed to cancel the errorsassociated with the change in the phase center of the antennasand to predict the average effective permittivity of the imaged


object at different angular positions. Compared with the con-ventional imaging system using a single-antenna approach, thedeveloped system archives better images that accurately detectthe tumor and its position in a heterogeneous phantom.

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Yifan Wang received the B.E.E. degree in electricalengineering from Donghua University, Shanghai,China, in 2006 and the Ph.D. degree from theUniversity of Queensland, Brisbane, Australia, in2013From 2006 to 2008, he served as an Information

System Architecture Specialist with InternationalBusiness Machines Corporation (IBM), China. In2012, he joined the University of California, LosAngeles (UCLA) as a visiting Ph.D. student. He isnow a postdoctoral research fellow of microwave

engineering a the University of Queensland. His research is in developingUWB microwave radar systems and components for biomedical applications.

Amin M. Abbosh (SM–08) received the M.Sc.degree in communication systems and the Ph.D. inmicrowave engineering, both from Mosul Univer-sity, Mosul, Iraq, in 1991 and 1996, respectively, theGrad Cert in higher education from the Universityof Queensland, Brisbane, Australia, in 2008, and theD.Eng. degree from the University of Queensland in2013.He is now carrying the prestigious ARC Future

Fellowship in the school of Information Technologyand Electrical Engineering, e University of Queens-

land. He authored more than 200 papers on wideband passive microwave de-vices, planar antennas, and microwave-based imaging systems.

Bassem Henin received the M.Sc. degree in elec-tromagnetics from Cairo University, Giza, Egypt, in2003 and the Ph.D. degree in electromagnetics fromThe University of Mississippi, University, MS, USA,in 2009.From 2009 to 2010, he was a Senior Research

Engineer in EMAG Technologies Inc., Ann Arbor,MI, USA. In 2011, he joined The University ofQueensland, Brisbane, Australia, as a PostdoctoralResearch Officer. His research interests includecomputational electromagnetics, microwave devices

and antenna design, UWB wireless systems and microwave imaging formedical, and industrial applications.

Phong Thanh Nguyen received the B.M.E. degreein electronics and telecommunication engineeringfrom Ho Chi Minh City University of Technology,Ho Chi Minh City, Vietnam, in 2007 and the M.E.degree in electrical engineering from The Universityof Queensland, Brisbane, Australia, in 2010. He iscurrently pursuing the PhD degree at The Univer-sity of Queensland. His main research interest ismicrowave engineering in biomedical applications.

Synthetic Bandwidth Radar for Ultra-Wideband Microwave Imaging Systems

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