Super Precision Adaptive Array Processing and Systolic Array Structures
| dc.contributor.advisor | Wong, K.M. | en_US |
| dc.contributor.author | Dahanayake, Wickramaratna Bandula | en_US |
| dc.contributor.department | Electrical and Computer Engineering | en_US |
| dc.date.accessioned | 2014-06-18T16:37:14Z | |
| dc.date.available | 2014-06-18T16:37:14Z | |
| dc.date.created | 2010-05-21 | en_US |
| dc.date.issued | 1987 | en_US |
| dc.description.abstract | <p>Adaptive array processing is considered as a task of bearing estimation and beamforming.</p> <p>The use of the subspace decomposition in bearing estimation is studied. Operator decomposition approach is used to provide a more basic and unified framework to the spectrum representation. This unified approach is then utilized to study the geometric relationships between the conventional, high resolution, and super resolution spectrum estimation techniques.</p> <p>Bearing estimation under coherent signal environment is considered. A methodology is developed to estimate the number of incoming signals and the optimum number of subarrays concurrently.</p> <p>Beamforming is presented in a more general framework. The concept of beamforming as a process of joint bearing estimation and interference cancellation is proposed.</p> <p>Finally, a restart to the array processing and digital signal processing problems in general, is initiated.</p> | en_US |
| dc.description.degree | Doctor of Philosophy (PhD) | en_US |
| dc.identifier.other | opendissertations/2180 | en_US |
| dc.identifier.other | 2719 | en_US |
| dc.identifier.other | 1323495 | en_US |
| dc.identifier.uri | http://hdl.handle.net/11375/6876 | |
| dc.subject | Electrical and Computer Engineering | en_US |
| dc.title | Super Precision Adaptive Array Processing and Systolic Array Structures | en_US |
| dc.type | thesis | en_US |
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