2005Unpublished venueRequires access

Signal Subspace Projection Methods of Adaptive Sensor Array Processing

D.O. Carhoun

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Abstract

Reduced-rank subspace projection methods are used indirectly in frequency and angle-of-arrival estimation algorithms such as MUSIC and its relatives, but they are not commonly used directly in least-squares detection applications. The author has been exploring their use for the processing of underwater acoustic receiver array data for detection and matched-field localization. He describes and illustrates several techniques that have been developed and applied to signals recorded from different types of arrays. >

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Reduced-rank subspace projection methods are used indirectly in frequency and angle-of-arrival estimation algorithms such as MUSIC and its relatives, but they are not commonly used directly in least-squares detection applications. The author has been exploring their use for the processing of underwater acoustic receiver array data for detection and matched-field localization. He describes and illustrates several techniques that have been developed and applied to signals recorded from different types of arrays. >

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Available abstract

Reduced-rank subspace projection methods are used indirectly in frequency and angle-of-arrival estimation algorithms such as MUSIC and its relatives, but they are not commonly used directly in least-squares detection applications. The author has been exploring their use for the processing of underwater acoustic receiver array data for detection and matched-field localization. He describes and illustrates several techniques that have been developed and applied to signals recorded from different types of arrays. >

Key concepts: Subspace topology, Signal subspace, Projection (relational algebra), Computer science, Array processing, Signal processing, Sensor array, Rank (graph theory)

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