Ultrawideband noise radar imaging of impenetrable cylindrical objects using diffraction tomography

Hee Jung Shin, Ram M. Narayanan, Muralidhar Rangaswamy

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Ultrawideband (UWB) waveforms achieve excellent spatial resolution for better characterization of targets in tomographic imaging applications compared to narrowband waveforms. In this paper, two-dimensional tomographic images of multiple scattering objects are successfully obtained using the diffraction tomography approach by transmitting multiple independent and identically distributed (iid) UWB random noise waveforms. The feasibility of using a random noise waveform for tomography is investigated by formulating a white Gaussian noise (WGN) model using spectral estimation. The analytical formulation of object image formation using random noise waveforms is established based on the backward scattering, and several numerical diffraction tomography simulations are performed in the spatial frequency domain to validate the analytical results by reconstructing the tomographic images of scattering objects. The final image of the object based on multiple transmitted noise waveforms is reconstructed by averaging individually formed images which compares very well with the image created using the traditional Gaussian pulse. Pixel difference-based measure is used to analyze and estimate the image quality of the final reconstructed tomographic image under various signal-to-noise ratio (SNR) conditions. Also, preliminary experiment setup and measurement results are presented to assess the validation of simulation results.

Original languageEnglish (US)
Article number601659
JournalInternational Journal of Microwave Science and Technology
Volume2014
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Radiation
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Ultrawideband noise radar imaging of impenetrable cylindrical objects using diffraction tomography'. Together they form a unique fingerprint.

Cite this