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Efficient algorithms for three-dimensional near-field synthetic aperture radar imaging [Elektronische Ressource] / by Joaquim Fortuny

156 pages
Ajouté le : 01 janvier 2001
Lecture(s) : 9
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EUROPEAN COMMISSION Institute for the Protection and Security of the Citizen
JOINT RESEARCH CENTRE Humanitarian Security Unit
I-21020 Ispra, Italy
Efficient Algorithms for
Three-Dimensional Near-Field
Synthetic Aperture Radar Imaging
PhD Dissertation from
Faculty of Electrical Engineering
University of Karslruhe, Germany
Joaquim Fortuny
2001 EUR 19942 ENEfficient Algorithms for Three-Dimensional
Near-Field Synthetic Aperture Radar Imaging
Zur Erlangung des akademischen Grades eines
von der Fakult¨at fur¨
der Universit¨at Karlsruhe
Ing. Joaquim Fortuny
aus Tarragona (Spanien)
Tag der mundlic¨ hen Prufung:¨ 21.5.2001
Hauptreferent: Prof. Dr.-Ing. Werner Wiesbeck
Korreferenten: Prof. Dr.-Ing. Martti T. Hallikainen
Dr. rer.nat. Alois J. SieberPreface
This Thesis arises from the work done at the European Microwave Signature Laboratory
(EMSL), a large scale facility of the Directorate General Joint Research Center (JRC) of
theEuropeanCommission(EC)locatedinIspra,NorthernItaly. Thewholeprojectstarted
when two members of the EMSL Advisory Committee (Prof. Dr.-Ing. Werner Wiesbeck,
Director of the Institute for Microwaves and Electronics, Karlsruhe University, Germany,
and Prof. Dr.-Ing. Martti Hallikainen, Head of the Laboratory of Space Technology,
Helsinki University of Technology, Finland) encouraged me to initiate this PhD Thesis.
ForemostIwanttoexpressmygratitudetomysupervisor,Prof. Dr.-Ing.WernerWies-
beck, who offered me the opportunity to defend this Thesis at his faculty. His continuous
assistance and encouragement has been crucial to the successful completion of this work.
I also thank the Board of the Faculty of Electrical Engineering, Karlsruhe University, for
allowing me to write and defend this Thesis in English.
I should also express my thanks to Prof. Dr.-Ing. Martti Hallikainen, for critically
reviewing this work, and for the many constructive comments.
Sincere thanks in particular are due to my unit head at JRC, Dr. Alois Sieber, for his
active involvement and guidance throughout this project.
A very special mentioning is reserved for Dr.-Ing. Juan-Manuel L´opez-S´anchez, Ali-
canteUniversity, Spain, forhisfriendship, inthefirstinstance, andthenforthesignificant
contribution given to the development of the imaging techniques presented in Chapter 3.
thesuccessfulpreparationoftheradarexperimentspresentedinthisThesis. Inparticular,
I want to thank Dott. Giuseppe Nesti and Dipl.-Ing. Eggert Ohlmer for the continuous
supportandexcellentadvise. SpecialthanksareduetoDott. DarioTarchiandDott. Ing.
Davide Leva for the preparation of the experiment with the ground based SAR system of
theunit. IamverygratefultoElenadiGioia,secretaryoftheHumanitarianSecurityUnit,
for her constant assistance. Yet, I want to thank Dr. Gareth Lewis for the proofreading
of the Preface
I want to express my gratitude to Dr.-Ing. Hans Rudolf and Dipl.-Ing. Bj¨orn Dietrich
for their help, encouragement and friendship.
SincerethanksareduetoDipl.-Ing. ChristianFischerfromtheInstitutforMicrowaves
and Electronics at Karlsruhe University for his continual assistance during my series of
visits to Karlsruhe.
Finally, I would also like to thank my parents for their sacrifice, encouragement, and
supportthroughoutmystudies. Lastbutnotleast,sincethiswasaneffortmostlyallocated
outside the normal working hours at JRC and during my holidays, I thank my wife, Mar´ıa
Jos´e, and my children, Carlos and Marta, for their inspiration, encouragement and endless
patience.Executive Summary
operating in a controlled environment offers a unique opportunity to define optimally the
operational parameters (e.g., the frequency, the polarization and the viewing geometry)
of future SAR systems for a given application. The scanning geometries commonly used
with indoor 3-D SAR systems are planar, cylindrical, and spherical. For these scanning
geometries, a set of efficient near-field algorithms especially suited for these systems is
presently missing.
Inthisthesis, asetoffive3-Dnear-fieldimagingalgorithmsisintroduced, eachsatisfy-
ing different requirements in terms of computational cost, quality of the resulting imagery,
type of the scanning geometry, and implementation complexity. These algorithms are all
tested by means of numerical simulations and, most important, radar measurements in
the European Microwave Signature Laboratory (EMSL).
At first, a novel 3-D near-field radar imaging technique based on the range migration
algorithm (RMA), which requires frequency domain backscatter data acquired on a two-
dimensional (2-D) planar aperture, is presented. The formulation of this algorithm is
derived by using the method of stationary phase (MSP). The 3-D RMA cannot be directly
appliedwithcylindricalandsphericalscanninggeometries. Forthesescanninggeometries,
a new imaging algorithm based on the backpropagation of the backscattered data onto a
planar aperture followed by the 3-D RMA is introduced.
The use of the proposed backpropagation technique with targets electrically very large
is computationally costly. Two alternative solutions are suggested. First, a space-variant
matched filter imaging algorithm especially tailored for spherical scanning geometries,
which accounts precisely for the wavefront curvature and the free space propagation loss.
Second, a polar format algorithm (PFA) with an image rectification. This solution allows
the use of FFT-based focusing algorithms normally used under the far-field condition.
The resulting geometric distortion due to the short observation distance is successfully
corrected by applying a rectification algorithm.
Finally, a subsurface sensing algorithm that corrects for the effects of refraction and
dispersion is outlined. This imaging algorithm is especially tailored for a forward-looking
stand-off platform. In addition, a simple and effective characterization technique is used
to retrieve the dielectric permittivity of the medium surrounding the subsurface objects.List of Acronyms
1-D: One-Dimensional
2-D: Two-Dimensional
3-D: Three-Dimensional
APL: Anti-Personnel Landmine
CCRS: Canada Centre for Remote Sensing
CW: Continuous Wave
dBsm: dB Square Meter
DFT: Discrete Fourier Transform
EC: European Commission
EMSL: European Microwave Signature Laboratory
FFT: Fast Fourier Transform
FT: Fourier Transform
GPR: Ground Penetrating Radar
HF: High Frequency
HSU: Humanitarian Security Unit
IFFT: Inverse Fast Fourier Transform
IPSC: Institute for the Protection and Security of the Citizen
ISAR: Inverse Synthetic Aperture Radar
JRC: Directorate General Joint Research Centre
LISA: Linear SAR System
MF: Matched Filter
MSP: Method of the Stationary Phase
NF: Near Field
PFA: Polar Format Algorithm
PFA-IR: Polar Format Algorithm with Image Rectification
RCS: Radar Cross Section
RF: Radio Frequency
RMA: Range Migration Algorithm
RMA-FReD: Frequency Domain Replication and Down-Sampling
RMA-FT: Range Migration Algorithm with Fields Translation
SAFT: Synthetic Aperture Focusing Technique
SAR: Synthetic Aperture Radarx List of Acronyms
SNR: Signal to Noise Ratio
SVMFIA: Space-Variant Matched Filter Imaging Algorithm
SVMF-SSA: A Space-Variant Matched Filter Subsurface Sensing
Tx/Rx: Transmit/Receive
UXO: Unexploded Ordnance
VNA: Vector Network Analyzer