This dissertation analyzes the capability of multiple-input, multiple-output (MIMO) radar techniques to improve the image quality and area-coverage rate of synthetic aperture imaging systems. A signal processing architecture for MIMO radar is used to understand the applicability of MIMO for synthetic aperture radar (SAR) and synthetic aperture sonar (SAS) systems. MIMO SAR/SAS is shown to be a natural extension of standard multichannel synthetic aperture imaging techniques to exploit transmit degrees of freedom in addition to those used on receive. Degradation in range sidelobe performance and the associated impact on image quality is identified as a key impediment to MIMO SAR/SAS. A novel mismatched filtering approach is presented to mitigate this issue. New results in sampling theory are derived that allow the aliasing that occurs when a wide-sense stationary random process is non-uniformly sampled to be quantified. These results are applied to the case of recurrent sampling and used to quantify the impact of azimuth ambiguities on MIMO SAR/SAS image contrast.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/53566 |
| Date | 08 June 2015 |
| Creators | Davis, Michael Scott |
| Contributors | Lanterman, Aaron D. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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