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An ESPRIT Algorithm for Tracking Time-Varying Signals

dc.contributor.authorLiu, K.J. Rayen_US
dc.contributor.authorO'Leary, D.P.en_US
dc.contributor.authorStewart, G.W.en_US
dc.contributor.authorWu, Y-J.en_US
dc.description.abstractESPRIT is a successful algorithm for determining the constant directions of arrival of a set of narrowband signals on an array of sensors. Unfortunately, its computational burden makes it unsuitable for real time processing of signals with time-varying directions of arrival. In this work we develop a new implementation of ESPRIT that has potential for real time processing. It is based on a rank-revealing URV decomposition, rather than the eigendecomposition or singular value decomposition used in previous ESPRIT algorithms. We demonstrate its performance on simulated data representing both constant and time-varying signals. We find that the URV-based ESPRIT algorithm (total least squares variant) is effective for time- varying directions-of-arrival using either rectangular or exponential windowing techniques to diminish the effects of old information.en_US
dc.format.extent827749 bytes
dc.relation.ispartofseriesISR; TR 1992-54en_US
dc.subjectsignal processingen_US
dc.subjectcomputational complexityen_US
dc.subjectSystems Integrationen_US
dc.titleAn ESPRIT Algorithm for Tracking Time-Varying Signalsen_US
dc.typeTechnical Reporten_US

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