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<p>The collection of signals intelligence via passive direction finding and geolocation of radio frequency signals is of great concern to the military for its contribution to the development of battlespace awareness. Basic subspace direction finding techniques provide a method of determining the direction-of-arrival (DOA) of multiple signals on an array of receivers, but they have an inherent limitation in that they are narrowband by design. The impact of various signal frequencies, bandwidths, and signal to noise ratios present in the source signals received by a sparse array using the multiple signals classification (MUSIC) subspace direction-finding algorithm are evaluated in this thesis. Additionally, two performance enhancements are presented: one that reduces the MUSIC computational load and one that provides a method of utilizing collector motion to resolve DOA ambiguities.
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<br>Subjects: ambiguity; array; direction finding; geolocation; interferometry; MUSIC; multiple signals classification; sparse array; subspace methods; wideband</div>
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Straessle, Gregory C.</div>
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