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Ultra wideband antenna array processing under spatial aliasing

Given a certain transmission frequency, Shannon spatial sampling limit de¯nes
an upper bound for the antenna element spacing. Beyond this bound, the exceeded
ambiguity avoids correct estimation of the signal parameters (i.e., array manifold
crossing). This spacing limit is inversely proportional to the frequency of transmis-
sion. Therefore, to meet a wider spectral support, the element spacing should be
decreased. However, practical implementations of closely spaced elements result in a
detrimental increase in electromagnetic mutual couplings among the sensors. Further-
more, decreasing the spacing reduces the array angle resolution. In this dissertation,
the problem of Direction of Arrival (DOA) estimation of broadband sources is ad-
dressed when the element spacing of a Uniform Array Antenna (ULA) is inordinate.
It is illustrated that one can resolve the aliasing ambiguity by utilizing the frequency
diversity of the broadband sources. An algorithm, based on Maximum Likelihood
Estimator (MLE), is proposed to estimate the transmitted data signal and the DOA
of each source. In the sequel, a subspace-based algorithm is developed and the prob-
lem of order estimation is discussed. The adopted signaling framework assumes a
subband hopping transmission in order to resolve the problem of source associations
and system identi¯cation. The proposed algorithms relax the stringent maximum
element-spacing constraint of the arrays pertinent to the upper-bound of frequency
transmission and suggest that, under some mild constraints, the element spacing can be conveniently increased. An approximate expression for the estimation error has
also been developed to gauge the behavior of the proposed algorithms. Through con-
¯rmatory simulation, it is shown that the performance gain of the proposed setup
is potentially signi¯cant, speci¯cally when the transmitters are closely spaced and
under low Signal to Noise Ratio (SNR), which makes it applicable to license-free
communication.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-1495
Date15 May 2009
CreatorsShapoury, Alireza
ContributorsSerpedin, Erchin
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Dissertation, text
Formatelectronic, application/pdf, born digital

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