Temporal Reference Algorithms versus Spatial Reference Algorithms forSmart Antennas
Wireless Personal Communications: An International Journal
Teletraffic Analysis of SDMA-Systems with Inhomogeneous MS Location Distribution and Mobility
Wireless Personal Communications: An International Journal
Maximizing the SDMA Mobile Radio Capacity Increase by DOA Sensitive Channel Allocation
Wireless Personal Communications: An International Journal
Joint Use of Supersolvable Frequency Estimates
Automation and Remote Control
Estimation of resonant frequencies and quality factors from time domain computations
Journal of Computational Physics
2-D unitary matrix pencil method for efficient direction of arrival estimation
Digital Signal Processing
Journal of VLSI Signal Processing Systems
Underdetermined blind source separation in echoic environments using DESPRIT
EURASIP Journal on Applied Signal Processing
New approaches for channel prediction based on sinusoidal modeling
EURASIP Journal on Applied Signal Processing
Conjugate unitary ESPRIT for real sources adapted to the coherent case
Signal Processing
Dynamic hardware-based optimization for adaptive array antennas
Proceedings of the 2006 conference on Integrated Intelligent Systems for Engineering Design
SVD-based joint azimuth/elevation estimation with automatic pairing
Signal Processing
Node localization algorithm based on matrix pencil for wireless sensor network
NTMS'09 Proceedings of the 3rd international conference on New technologies, mobility and security
Sinusoidal order estimation using angles between subspaces
EURASIP Journal on Advances in Signal Processing
Tensor-based spatial smoothing (TB-SS) using multiple snapshots
IEEE Transactions on Signal Processing
A reduced complexity approach to IAA beamforming for efficient DOA estimation of coherent sources
EURASIP Journal on Advances in Signal Processing - Special issue on advances in angle-of-arrival and multidimensional signal processing for localization and communications
Cross-ambiguity function domain multipath channel parameter estimation
Digital Signal Processing
Approximate maximum likelihood estimation of two closely spaced sources
Signal Processing
Hi-index | 35.69 |
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