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Subspace tracking for nested arrays

Fountoulakis Emmanouil

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Summary

In radar, sonar, and mobile communications, the estimation of the directions from which multi-ple signals arrive at a point is called the direction of arrival (DoA) estimation problem and, overthe past decades, has been performed often through uniform linear arrays (ULAs) in conjunc-tion with high-resolution subspace-based algorithms. Such techniques, however, have limitedcapability of the number of directions they can estimate; if the ULA consists of N antennaelements, then high-resolution subspace-based algorithms can estimate the directions of up toN − 1 signals. To increase this number, a novel structure that consists of N antenna elementsand enables the estimation of O (N^2 ) signal directions has been developed recently. It lies onspecific nonuniform-array structures which are called nested arrays.In this thesis, we first overviewed the structure and properties of nested arrays and eval-uated their performance through computer simulations. We observed that the nested arrayswith conventional subspace-based signal-processing algorithms can offer high performance butrequire high complexity, which makes them impractical for real-time applications. Then, wedeveloped novel subspace tracking techniques for nested arrays that have lower complexity,are proven to converge to the optimal, subspace-based estimator, and are capable of trackingchanges in the directions of the arriving signals (for example, when a source is moving withrespect to the array receiver).

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