Title
Unitary ESPRIT: how to obtain increased estimation accuracy with a reduced computational burden
Abstract
ESPRIT is a high-resolution signal parameter estimation technique based on the translational invariance structure of a sensor array. Previous ESPRIT algorithms do not use the fact that the operator representing the phase delays between the two subarrays is unitary. The authors present a simple and efficient method to constrain the estimated phase factors to the unit circle, if centro-symmetric array configurations are used. Unitary ESPRIT, the resulting closed-form algorithm, has an ESPRIT-like structure except for the fact that it is formulated in terms of real-valued computations throughout. Since the dimension of the matrices is not increased, this completely real-valued algorithm achieves a substantial reduction of the computational complexity. Furthermore, Unitary ESPRIT incorporates forward-backward averaging, leading to an improved performance compared to the standard ESPRIT algorithm, especially for correlated source signals. Like standard ESPRIT, Unitary ESPRIT offers an inexpensive possibility to reconstruct the impinging wavefronts (signal copy). These signal estimates are more accurate, since Unitary ESPRIT improves the underlying signal subspace estimates. Simulations confirm that, even for uncorrelated signals, the standard ESPRIT algorithm needs twice the number of snapshots to achieve a precision comparable to that of Unitary ESPRIT. Thus, Unitary ESPRIT provides increased estimation accuracy with a reduced computational burden
Year
DOI
Venue
1995
10.1109/78.382406
IEEE Transactions on Signal Processing
Keywords
Field
DocType
Hermitian matrices,array signal processing,computational complexity,phase estimation,signal reconstruction,ESPRIT-like structure,Unitary ESPRIT,centro-symmetric array configurations,closed-form algorithm,computational complexity,correlated source signals,estimation accuracy,forward-backward averaging,high-resolution signal parameter estimation technique,impinging wavefronts,matrices,phase delays,phase factors,real-valued algorithm,real-valued computations,reconstruct,sensor array,snapshots,translational invariance structure,uncorrelated signals
Mathematical optimization,Matrix (mathematics),Sensor array,Unit circle,Unitary state,Estimation theory,Signal subspace,Signal reconstruction,Mathematics,Computational complexity theory
Journal
Volume
Issue
ISSN
43
5
1053-587X
Citations 
PageRank 
References 
180
20.92
15
Authors
2
Search Limit
100180
Name
Order
Citations
PageRank
M. Haardt149545.19
Josef A. Nossek2726112.24