Efficient Array Processing for Partial Signal Coherence
Rao, Anil M.
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Permalink
https://hdl.handle.net/2142/80718
Description
Title
Efficient Array Processing for Partial Signal Coherence
Author(s)
Rao, Anil M.
Issue Date
2001
Doctoral Committee Chair(s)
Jones, Douglas L.
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
Abstract
With the growing use of antenna arrays for enhancing signal detection, estimation, interference cancellation, and position location comes the need to better understand the spatial properties of the received signals. To allow for simple and efficient implementation required in real-time processing applications, conventional array processing algorithms assume perfect coherence of the signal wavefronts. Unfortunately this assumption is clearly inappropriate, because many kinds of dispersion phenomena make the received signals exhibit a limited spatial coherence. The causes of such spatial coherence degradation can be attributed to either complex multipath propagation or to mechanical deformations in the array itself. Optimally dealing with partial signal coherence typically requires modeling the array response as random, leading to complicated combining schemes to achieve optimal performance. The optimal detector is uniquely different than conventional detectors in that it involves both matrix combining and beamsteering of the matched-filter outputs. We show that the discrete Fourier transform can simultaneously serve as an asymptotically optimal spatial combiner and beamsteering tool for uniform linear arrays suffering from partial coherence. Simulation results show that the proposed combining scheme provides not only a significant gain in performance over conventional methods, but near-optimal performance at significantly less computation, even for arrays of modest size. Hence this thesis provides an important advance in statistical signal array processing by providing an efficient and versatile technique for coping with partial spatial signal coherence.
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