Off-campus UNL users: To download campus access dissertations, please use the following link to log into our proxy server with your NU ID and password. When you are done browsing please remember to return to this page and log out.

Non-UNL users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Ultra-wideband random noise synthetic aperture radar imaging

Dmitriy Sergeyevich Garmatyuk, University of Nebraska - Lincoln

Abstract

Random noise radars have been analyzed extensively over the past forty years. They were noted for their attractive LPI (low probability of intercept), LPIin (low probability of identification), and LPD (low probability of detection) characteristics. Using ultra-wideband noise as a radar transmit signal has the added benefit of achieving high-resolution imagery, in both down-range and cross-range dimensions using synthetic aperture radar (SAR) technique. ^ A coherent ultra-wideband random noise radar system operating in the 1–2 GHz frequency range has been developed at the University of Nebraska-Lincoln. A unique signal processing procedure based upon heterodyne correlation techniques preserves phase coherence within the system, thereby enabling it to be used for synthetic aperture radar imaging. Original experimental setup facilitates a simple and low-cost mobile SAR implementation, best suited for short-range quasi-stripmap SAR imaging. This dissertation develops the theoretical formulation and addresses practical implementation of UWB random noise SAR. It also investigates the potential of a coherent continuous-wave (CW) bandlimited random noise radar as an inexpensive, electronic counter-countermeasure (ECCM) capable, radio-frequency interference (RFI) resistant imaging instrument. ^

Subject Area

Engineering, Electronics and Electrical

Recommended Citation

Garmatyuk, Dmitriy Sergeyevich, "Ultra-wideband random noise synthetic aperture radar imaging" (2001). ETD collection for University of Nebraska - Lincoln. AAI3022629.
http://digitalcommons.unl.edu/dissertations/AAI3022629

Share

COinS