Naren Viswanathan

ORCID: 0000-0002-7520-533X
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About
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Research Areas
  • Microwave Imaging and Scattering Analysis
  • Sparse and Compressive Sensing Techniques
  • Millimeter-Wave Propagation and Modeling
  • Advanced SAR Imaging Techniques
  • Terahertz technology and applications
  • Soil Moisture and Remote Sensing
  • Medical Imaging Techniques and Applications
  • Radio Astronomy Observations and Technology
  • Wireless Networks and Protocols
  • Superconducting and THz Device Technology
  • Advanced Fluorescence Microscopy Techniques
  • Advanced MIMO Systems Optimization
  • Random lasers and scattering media

University of Utah
2015-2020

We present a sparse synthetic-aperture, active imaging system at W-band (75 - 110 GHz), which uses sub-harmonic mixer modules. The employs mechanical scanning of the receiver module position, and fixed transmitter module. A vector network analyzer provides back end detection. full-wave forward model allows accurate construction image transfer matrix. solve inverse problem to reconstruct scenes using least squares technique. demonstrate far-field, diffraction limited 2D 3D objects achieve...

10.1364/oe.24.008317 article EN cc-by Optics Express 2016-04-08

We present two techniques for optimizing the position of transmitter and receiver modules on a sparse aperture millimeter-wave computational imaging system. The first technique uses an easily computable spatial representation array, called coarray, to ideally distribute frequency components probed by setup. second approach involves maximizing information added complete measurement scene This is analogous system capacity maximization frequently employed in wireless communication. show that...

10.1109/tap.2020.3030946 article EN IEEE Transactions on Antennas and Propagation 2020-10-21

Computational imaging techniques that rely on a compressed set of measurements and exploit prior information such as target size, scene sparsity, transceiver radiation pattern, etc are rapidly gaining popularity in areas medical security imaging, remote sensing, automotive radar they can significantly reduce SWAP-C (Size, Weight, Power, Cost) hardware modules, especially at millimeter-wave frequencies. In this article, we propose using the covariance matrix large ensemble representative...

10.1117/12.2559385 article EN 2020-05-18

Millimeter wave (mmw) imaging is gaining popularity in surveillance systems as it provides good tradeoff between high resolution (optical/IR imaging) and penetration depth (microwave). Conventional mmw Fourier transform based holographic (D.M. Sheen et. al., MTT, IEEE Transactions on, vol.49, no.9, Sep 2001) require many measurements the required space-bandwidth product (M) of target image. However, compressed (Guy Lipworth JOSA A, Vol. 30, Issue 8, 2013), apriori knowledge object to be...

10.1109/usnc-ursi.2015.7303304 article EN 2015-07-01

We present a sparse synthetic aperture system at W-Band (75 – 110 GHz) using sub-harmonic mixer modules. The active consists of scanned transmitter module, fixed receiver module and vector network analyzer as the back end. For this we construct complete analytical forward model solve inverse problem to reconstruct scene least squares technique. demonstrate standoff diffraction limited imaging 2D 3D targets achieve cross range resolution 3 mm depth 4 respectively. Furthermore, also show that...

10.1364/aoms.2015.jt5a.17 article EN Imaging and Applied Optics 2015-01-01

An ensemble of representative targets contains apriori correlation information, quantified by the intervoxel covariance matrix. Thresholding according to eigenvalues his matrix and reconstructing only those eigenmodes, a faster, more accurate reconstruction is obtained.

10.1364/cosi.2018.ctu2e.5 article EN 2018-01-01
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