Transcript This is my Final Presentation Slides
Design of a 3D Microwave Imaging System
Drew Jaworski Advisor: Dr. Yong Zhou Fall 2011 – Senior Design I
Why Microwave Imaging?
Electromagnetic Imaging Systems Vision Nature doesn’t always know best!
X-Ray Ionizing radiation Infrared (“thermal”) Limited to surfaces MRI (quantum mechanics) Expensive Microwave Non-ionizing, penetrating, less expensive!
Applications Medical imaging (cancerous tumors, etc) Industrial scanning (forging defects, etc)
Project Specifications
Design of a 3-dimensional microwave imaging system
Vector network analyzer signal analysis Automated data acquirement and processing Biomedical focus, but adaptable for other imaging applications Multiplexed antenna array
Project Constraints
Size
Entire system less than 1[m]*1[m]*1[m]
Budget
$300 from department + personal funds
FCC Regulations
Medical device band: 3.1[GHz] –10.6 [GHz]
Many others related to trying to manage the above constraints
Electromagnetic Overview
Plane-wave approximation Imaging subject located in far-field of antenna array, perpendicular to propagation of waves Simplifies analysis at expense of system size Scattering through media A result of multiple layers of diffraction and refraction, in the case of the complex human body.
Images courtesy of: http://en.wikipedia.org/wiki/File:Linear.Polarization.Linearly.Polarized.Light_plane.wave.svg
http://commons.wikimedia.org/wiki/File:Huygens_brechung.png
Vector Network Analyzer
Measures a Two Port Network Returns S-Parameters (Scattering Parameters) S11 – Return Loss S21 – Insertion Loss Parallel antennas connected to VNA ports Calibrate response Place object between antennas Result is how the object affected the electromagnetic radiation between the two antennas Results can be manipulated with software algorithms to give dielectric properties of the object!
Inverse Scattering Solution
Repeat with multiple antennas (4x4 array, in this case) Rotate object between antenna arrays Result is a set of matrixes of scattering parameters for a 32-port network (for a range of frequencies!) Can be manipulated to produce a discretized graphical representation of the dielectric properties in different regions between antenna arrays Inverse Scattering Problem – Microwave Tomography We know the forward transmitted radiation (aka Incident Fields) We have information about the received fields (aka Scattered Fields) Now we want to know what made them change!
Very complex calculations that are demanding of computing resources Fortunately, much research has been published that has mathematically and/or computationally simplified the solution process (relatively)
Automated Data Analysis
Labview Automate collection of data Several colleagues have worked out the details Rotation mechanism –
Juan Nava
,
Miguel Rivera
TTL communication (for multiplexer) –
Julio Vasquez
Matlab Process data Numerous published algorithms can be implemented and tested
Frequency Selection
Often limited by hardware technology (switch/antenna bandwidth) Biomedical focus – human tissues Estimates vary, best to come up with your own and justify accordingly Begin with what spectrum is available FCC
“Medical Systems: These devices must be operated in the frequency band 3.1-10.6 GHz. A medical imaging system may be used for a variety of health applications to “see” inside the body of a person or animal. Operation must be at the direction of, or under the supervision of, a licensed health care practitioner.”
http://transition.fcc.gov/Bureaus/Engineering_Technology/Orders/2002/fcc02 048.pdf
Begin with properties of human body Database of dielectric properties of numerous types of tissue available from Italian National Research Council site: http://niremf.ifac.cnr.it/tissprop/
Dielectric Properties Database
Skin (wet and Dry), Muscle, Fat, and Bone Major constituents most body parts 0.14
0.12
0.1
0.08
0.06
0.04
Lowest λ 0.02
0 Highest λ intersection
Wavelength and Attenuation Constant versus Frequency
Highest alpha Lowest alpha 4 3.5
3 2.5
2 1.5
1 intersection 0.5
0
Frequency [GHz]
Wavelength [cm] – SkinWet Wavelength [cm] SkinDry Wavelength [cm] – Muscle Wavelength [cm] – Fat Wavelength [cm] – BoneCortical Attenuation Coefficient [1/cm] – SkinWet Attenuation Coefficient [1/cm] – SkinDry Attenuation Coefficient [1/cm] – Muscle Attenuation Coefficient [1/cm] – Fat Attenuation Coefficient [1/cm] – BoneCortical
Antenna Array Multiplexer
Julio Vasquez
’s RF multiplexer design intended for this project Overlapping semesters meant his prototype was not yet completed and could not be used immediately Microstrip antenna array with integrated multiplexer switch hierarchy Avoids requirement of numerous expensive and tangled SMA patch cables Integrates network of SPDT switches into antenna array 4x4 microstrip antenna array 1 SMA connector (patched to VNA) 15 SPDT RF switches (operating up to 8[GHz]) 16 microstrip patch antennas 8 TTL-level (5V) control lines
Antenna Array with Multiplexer
RF Layout Guidelines
Line Widths 3.08[mm] 50 Ω impedance Curves Ideally smooth curves radius >= 3*lineWidth Ground fills Not completely necessary Relatively noise-free environment Noise reducing padding around experiment setup Not feasible for hand-produced prototype Tapered impedance tranformers Linear (“triangular”) is best for wideband operation (Pozar) λ/4 ~ λ used in design (as long as could be reasonably fit)
Multiplexer
versus
Switch Network
Fully featured DC-12[GHz] multiplexer $700 ~ $1700 Single SPDT RF switch IC $1 ~ $3 M/A-COM technology solutions MASW-007107 Pros Large variety of models available Distributed by Mouser Cons Small package size (GaAs DIE ~ 4[mm]*4[mm]
MASW-007107
Obtained from IC Datasheet: http://www.macomtech.com/DataSheets/MASW-007107.pdf
MASW-007107
(continued)
Switch Network Hierarchy
UWB Microstrip Antenna
Two-port network theory (one-port input network, in this case) S 11 measures “return-loss” [dB] Lower is better, -10[dB] indicates half of the input power is lost in the network Return Loss is power radiated from antenna (hopefully) and other losses.
Bandwidth is measured where S 11 -10[dB] point crosses the Design is UWB when (BW / F center ) >= 25%
UWB Microstrip Antenna
(continued)
There are many published designs for UWB microstrip antennas
Most use complex ground geometries Usually explain it as something to keep the phase response level across the useable band
After trying several designs, I began modifying the geometries in an attempt to find something new
UWB Microstrip Antenna
(continued) BW = 979[MHz] F center = 5.595[GHz] -10[dB] BW => 17.52% (close, but not UWB)
UWB Microstrip Antenna
(continued) Fractal and/or self-symmetry based designs Intended to induce multiple resonance frequencies 0.00
-5.00
-10.00
-15.00
-20.00
XY Plot 1 patchAntennaV1 ANSOFT Curve Info dB(S(1,1)) Setup1 : Sw eep $feedW='1.4mm' $patchHeight='15mm' $patchWidth='20mm' -25.00
-30.00
3.50
4.00
4.50
5.00
5.50
Freq [GHz] 6.00
6.50
7.00
Inspired by:
Miniaturized UWB Monopole Microstrip Antenna Design by the Combination of Guisepe Peano and Sierpinksi Carpet Fractals, IEEE AWPL, 2011
7.50
Budget (proposed)
Double-sided FR-4 boards (2x)
$12.66 + shipping
MASW007107 RF Switches (50x)
$37.50 + shipping
Commercially Manufactured PCBs
$150
All other supplies already in possession
Gantt Chart – SD1
Select Frequency Operation Range Decide Switching Design/Product Learn HFSS Decide Antenna Design Layout Array PCB Design Simulate Design Explicitely Modify PCB Design Accordingly Produce Protoype Board
9/1 9/15 9/16 9/30 10/1 10/15 10/16 10/31 11/1 11/15 11/16 11/30 12/1 12/15 12/15 12/30
Gantt Chart – SD2 (proposed)
Layout Final Design Send Layout Out for Manufacturing Test New Boards Establish Mathematics of System Program Algorithms Test System and Collect Data Prepare for Research Symposium Final Report and Presentation
1/1 1/15 1/15 1/31 2/1 2/15 2/16 2/29 3/1 3/15 3/16 3/31 4/1 4/30 5/1 5/31
Future Work
Finalize UWB antenna candidate design RF Layout of antenna array Produce a prototype (using materials on hand) Export Gerber file and have it manufactured commercially $1 per square inch (min. 150 square inch order) Develop mathematics of Imaging System
Microwave Imaging (2011)
, Matteo Pastorino Begin making microwave images!