TY - GEN
T1 - Near-field SAR imaging with dynamic metasurface antennas using an adapted range migration algorithm
AU - Diebold, Aaron V.
AU - Pulido-Mancera, Laura
AU - Sleasman, Timothy
AU - Boyarsky, Michael
AU - Imani, Mohammadreza F.
AU - Smith, David R.
N1 - Funding Information:
This work was supported by Air Force Office of Scientific Research (AFOSR, Grant No. FA9550-12-1-0491).
Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018
Y1 - 2018
N2 - Synthetic aperture radar (SAR) is a well-established approach for retrieving images with high resolution. How- ever, common hardware used for SAR systems is usually complex and costly, and can suffer from lengthy signal acquisition. In near-field imaging, such as through-wall-sensing and security screening, simpler and faster hardware can be found in the form of dynamic metasurface antennas (DMAs). These antennas consist of a waveguide-fed array of tunable metamaterial elements whose overall radiation patterns can be altered by DC signals. By sweeping through a set of tuning states, near-field imaging can be accomplished by multiplexing scene information into a collection of measurements, which are post-processed to retrieve scene information. While DMAs simplify hardware, the post-processing can become cumbersome, especially when DMAs are moving in a fashion similar to SAR. In this presentation, we address this problem by modifying the range migration algorithm (RMA) to be compatible with DMAs. To accommodate complex patterns generated by DMAs in the RMA, a pre-processing step is introduced to transform the measurements into an equivalent set corresponding to an effective multistatic configuration, for which specific forms of the algorithm have been derived. As we are operating in the near field of the antennas, some approximations made in the classical formulation of RMA may not be valid. In this paper, we examine the effect of one such approximation: the discarding of amplitude terms in the signal-target Fourier relationship. We demonstrate the adaptation of the RMA to near field imaging using a DMA as central hardware of a SAR system, and discuss the effects of this approximation on the resulting image quality.
AB - Synthetic aperture radar (SAR) is a well-established approach for retrieving images with high resolution. How- ever, common hardware used for SAR systems is usually complex and costly, and can suffer from lengthy signal acquisition. In near-field imaging, such as through-wall-sensing and security screening, simpler and faster hardware can be found in the form of dynamic metasurface antennas (DMAs). These antennas consist of a waveguide-fed array of tunable metamaterial elements whose overall radiation patterns can be altered by DC signals. By sweeping through a set of tuning states, near-field imaging can be accomplished by multiplexing scene information into a collection of measurements, which are post-processed to retrieve scene information. While DMAs simplify hardware, the post-processing can become cumbersome, especially when DMAs are moving in a fashion similar to SAR. In this presentation, we address this problem by modifying the range migration algorithm (RMA) to be compatible with DMAs. To accommodate complex patterns generated by DMAs in the RMA, a pre-processing step is introduced to transform the measurements into an equivalent set corresponding to an effective multistatic configuration, for which specific forms of the algorithm have been derived. As we are operating in the near field of the antennas, some approximations made in the classical formulation of RMA may not be valid. In this paper, we examine the effect of one such approximation: the discarding of amplitude terms in the signal-target Fourier relationship. We demonstrate the adaptation of the RMA to near field imaging using a DMA as central hardware of a SAR system, and discuss the effects of this approximation on the resulting image quality.
KW - Computational imaging
KW - Image reconstruction techniques
KW - Metamaterials
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U2 - 10.1117/12.2305067
DO - 10.1117/12.2305067
M3 - Conference contribution
AN - SCOPUS:85049527793
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Computational Imaging III
A2 - Ashok, Amit
A2 - Petruccelli, Jonathan C.
A2 - Mahalanobis, Abhijit
A2 - Tian, Lei
PB - SPIE
T2 - Computational Imaging III 2018
Y2 - 15 April 2018 through 17 April 2018
ER -