An ESPRIT Algorithm for Tracking Time-Varying Signals
Author(s) -
K. J. Liu,
Dianne P. O’Leary,
G. W. Stewart,
Yuan-Jye Wu
Publication year - 1992
Publication title -
digital repository at the university of maryland (university of maryland college park)
Language(s) - English
Resource type - Reports
DOI - 10.21236/ada445553
Subject(s) - tracking (education) , algorithm , computer science , artificial intelligence , psychology , pedagogy
: ESPRIT 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.
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