Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


osu1338330434.pdf (2.03 MB)

ETD Abstract Container

Abstract Header

Compressive Sensing for Tomographic Echo Imaging in Two Dimensions

Williams, Taylor P.
http://rave.ohiolink.edu/etdc/view?acc_num=osu1338330434

Abstract Details

2012, Master of Science, Ohio State University, Electrical and Computer Engineering.
We present a framework that leverages compressive sensing (CS) for tomographic echo imaging in two dimensions, a specific type of imaging problem that is of interest to both military and civilian researchers. We establish CS guarantees for certain types of far-field tomographic imaging of sparse scenes. Typically, CS guarantees for common tomographic systems can be difficult to establish because of the structure imposed by uniform sampling of echoes. This introduces a high level of coherence between measurements from different nearby reflectors. We overcome these difficulties by introducing randomness in the placement of several monostatic radar sites surrounding the scene and by making simplifying assumptions based on practical engineering constraints. We use a wideband signal to interrogate the scene, allowing for high-resolution imaging. Our main result shows that with high probability, the system model satisfies the restricted isometry property (RIP) under a certain set of assumptions and restrictions. The number of radar sites required to meet RIP is a function of the desired imaging resolution and the RIP parameters. We compare this result to empirical trials and show that there are significant limitations to the practical use of the bounds proven. However, there is value in the novel approach to proving RIP for this type of two-dimensional system. Our results indicate that we can produce a similar image using less sensors with CS compared to more sensors with traditional imaging algorithms that assume no information about the unknown scene.
Lee Potter, PhD (Advisor)
Emre Ertin, PhD (Committee Member)
Phillip Schniter, PhD (Committee Member)
57 p.
Applied Mathematics; Electrical Engineering
Compressive Sensing; Radar Tomography;

Recommended Citations

Citations

  • Williams, T. P. (2012). Compressive Sensing for Tomographic Echo Imaging in Two Dimensions [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338330434

    APA Style (7th edition)

  • Williams, Taylor. Compressive Sensing for Tomographic Echo Imaging in Two Dimensions. 2012. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1338330434.

    MLA Style (8th edition)

  • Williams, Taylor. "Compressive Sensing for Tomographic Echo Imaging in Two Dimensions." Master's thesis, Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338330434

    Chicago Manual of Style (17th edition)

osu1338330434
533
© 2012, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.