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Wideband direction of arrival estimation techniques for a class of arbitrary array geometries

Mahmud Reza Dehghani

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Abstract

Array signal processing is an established field with a number of available advanced powerful technologies for detecting and locating signals that arrive at a set of sensors in the presence of noise. The focus of this thesis is on development of direction of arrival (DOA) estimation techniques for both narrowband and wideband signal sources. For narrowband signals, the multiple signal classification (MUSIC) and weighted subspace fitting (WSF) algorithms based on subspace decomposition techniques are considered. These subspace methods are subsequently extended to the more challenging and interesting wideband signals by incorporating advanced algorithms such as incoherent signal subspace method (ISM) and coherent signal subspace method (CSM). Extension of the WSF algorithm to a framework based on CSM is also investigated.

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What this paper is about

Array signal processing is an established field with a number of available advanced powerful technologies for detecting and locating signals that arrive at a set of sensors in the presence of noise. The focus of this thesis is on development of direction of arrival (DOA) estimation techniques for both narrowband and wideband signal sources. For narrowband signals, the multiple signal classification (MUSIC) and weighted subspace fitting (WSF) algorithms based on subspace decomposition techniques are considered. These subspace methods are subsequently extended to the more challenging and interesting wideband signals by incorporating advanced algorithms such as incoherent signal subspace method (ISM) and coherent signal subspace method (CSM). Extension of the WSF algorithm to a framework based on CSM is also investigated.

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Available abstract

Array signal processing is an established field with a number of available advanced powerful technologies for detecting and locating signals that arrive at a set of sensors in the presence of noise. The focus of this thesis is on development of direction of arrival (DOA) estimation techniques for both narrowband and wideband signal sources. For narrowband signals, the multiple signal classification (MUSIC) and weighted subspace fitting (WSF) algorithms based on subspace decomposition techniques are considered. These subspace methods are subsequently extended to the more challenging and interesting wideband signals by incorporating advanced algorithms such as incoherent signal subspace method (ISM) and coherent signal subspace method (CSM). Extension of the WSF algorithm to a framework based on CSM is also investigated.

Key concepts: Signal subspace, Narrowband, Wideband, Direction of arrival, Subspace topology, Algorithm, Computer science, SIGNAL (programming language)

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