Ultrawideband Noise Radar Imaging of Impenetrable Cylindrical Objects Using Diffraction Tomography

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 24, 2014
Source ID
10.1155/2014/601659

Entities

People

  • Hee Jung Shin
  • Muralidhar (Murali) Rangaswamy
  • Ram M Narayanan

Organizations

  • Air Force Office of Scientific Research
  • Air Force Research Laboratory
  • Pennsylvania State University

Tags

Fields of Study

  • Engineering
  • Physics

Readers

  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Image Processing and Computer Vision.
  • Radio communications and signal processing.