This thesis presents a novel spatial spectrum estimation technique, ∂-MUSIC, for discriminating between two closely spaced sources which are highly correlated. The ∂-MUSIC algorithm is tested, modified, and compared to the MUSIC algorithm using a point source simulation. Various power levels, samples sizes and angle separations are used on a linear and a planar array for correlated and uncorrelated sources. The algorithm is found to be relatively insensitive to correlation and can separate targets to one-half of the angular separation threshold of ∂-MUSIC. The ∂-MUSIC algorithm is tested using a simulation that generated terrain scattered interference representative of a propagation scenario involving multiple paths. The simulation shows that ∂-MUSIC is able to resolve the direct path and image at less than one-fourth of a beam width, with a ten degree angle to the surface, whereas MUSIC finds a single angle which is biased toward the image.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/278617 |
| Date | January 1996 |
| Creators | Scholes, Richard Burton, 1968- |
| Contributors | Delaney, Pamela A. |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Thesis-Reproduction (electronic) |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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