Unitary ESPRIT: How to Obtain Increased Estimation Accuracy with a Reduced Computational Burden

IEEE Transactions on Signal Processing

Volumn 43, Issue 5, 1995, Pages 1232-1242

  Haardt, Martin ^a   Nossek, Josef A ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

HIGH RESOLUTION SIGNAL PARAMETER ESTIMATION TECHNIQUE; UNIFORM LINEAR ARRAY;

ALGORITHMS; ANTENNA ARRAYS; COMPUTATIONAL COMPLEXITY; COMPUTATIONAL METHODS; EIGENVALUES AND EIGENFUNCTIONS; MATHEMATICAL MODELS; MATHEMATICAL OPERATORS; MATRIX ALGEBRA; PARAMETER ESTIMATION; WAVEFRONTS;

SIGNAL PROCESSING;

EID: 0029307647     PISSN: 1053587X     EISSN: 19410476     Source Type: Journal    
DOI: 10.1109/78.382406     Document Type: Article

References (24)

1. C. H. Bischof and G. M. Shroff, “On updating signal subspaces,” IEEE Trans. Signal Processing, vol. 40, pp. 96-105, Jan. 1992.
2. T. F. Chan, “Rank revealing QR factorization,” Linear Algebra and its Applications, vol. 88, 89, pp. 67-82, 1987.
3. J. Götze and A. J. van der Veen, “On-line subspace estimation using a Schur-type method,” IEEE Trans. Signal Processing, Nov. 1993, submitted for publication.
4. M. Haardt and M. E. Ali-Hackl, “Unitary ESPRIT: How to exploit additional information inherent in the rotational invariance structure,” in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, Adelaide, Australia, Apr. 1994, pp. 229-232, vol. IV.
5. M. Haardt and J. Götze, “Unitary Schur-type subspace estimation,” Technical University of Munich, Inst, of Network Theory Circuit Design, Munich, Germany, Tech. Rep. TUM-LNS-TR-94-6, July 1994.
6. M. Haardt, P. Weismuller, and R. Killmann, “The identification of late fields: A multichannel high-resolution state space approach,” in Proc. 14th GRETSI Symp. Signal Image Processing, Juan-les-Pins, France, Sept. 1993, pp. 1251-1254.
7. Y. Hua and T. K. Sarkar, “On SVD for estimating generalized eigenvalues of singular matrix pencil in noise,” IEEE Trans. Signal Processing, vol. 39, pp. 892-900, Apr. 1991.
8. K. C. Huarng and C. C. Yeh, “A unitary transformation method for angle-of-anival estimation,” IEEE Trans. Signal Processing, vol. 39, pp. 975-977, Apr. 1991.
9. “Adaptive beamforming with conjugate symmetric weights,” IEEE Trans. Antenna. Propagat., vol. 39, pp. 926-932, July 1991.
10. A. Lee, “Centrohermitian and skew-centrohermitian matrices,” Linear Algebra and its Applications, vol. 29, pp. 205-210, 1980.
11. K. J. R. Liu, D. P. O’Leary, G. W. Stewart, and Y. J. J. Wu, “An adaptive ESPRIT based on URV decomposition,” in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, Minneapolis, MN, Apr. 1993, pp. 37-40, vol. IV.
12. B. Ottersten, M. Viberg, and T. Kailath, “Performance analysis of the total least squares ESPRIT algorithm,” IEEE Trans. Signal Processing, vol. 39, pp. 1122-1135, May 1991.
13. S. U. Pillai and B. H. Kwon, “Forward/backward spatial smoothing techniques for coherent signal identification,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 8-15, Jan. 1989.
14. B. D. Rao and K. V. S. Hari, “Weighted subspace methods and spatial smoothing: Analysis and comparison,” IEEE Trans. Signal Processing, vol. 41, pp. 788-803, Feb. 1993.
15. R. Roy and T. Kailath, “ESPRIT—Estimation of signal parameters via rotational invariance techniques,” in Signal Processing Part II: Control Theory and Applications (L. Auslander, F. A. Grünbaum, J. W. Helton, T. Kailath, P. Khargonekar, and S. Mitter, Eds.). Berlin, Vienna, New York: Springer-Verlag, 1990, pp. 369-411.
16. R. Roy, A. Paulraj, and T. Kailath, “ESPRIT—A subspace rotation approach to estimation of parameters of cisoids in noise,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-34, pp. 1340-1342, Oct. 1986.
17. R. H. Roy, “ESPRIT—Estimation of Signal Parameters via Rotational Invariance Techniques,” Ph. D. thesis, Stanford Univ., Stanford, CA, Aug. 1987.
18. G. W. Stewart, “An updating algorithm for subspace tracking,” IEEE Trans. Signal Processing, vol. 40, pp. 1535-1541, June 1992.
19. A. J. van der Veen, “A Schur method for low-rank matrix approximation,” SIAM J. Matrix Anal. Appl., 1994, accepted for publication.
20. A. J. van der Veen, E. F. Deprettere, and A. L. Swindlehurst, “Subspace-based signal analysis using singular value decomposition,” Proc. IEEE, vol. 81, pp. 1277-1308, Sept. 1993.
21. S. Van Huffel and J. Vandewalle, The Total Least Squares Problem: Computational Aspects and Analysis Frontiers in Applied Mathematics, Vol. 9. Philadelphia, PA: Soc. Ind. and Applied Math., 1991.
22. G. Xu, R. H. Roy, and T. Kailath, “Detection of number of sources via exploitation of centro-symmetry property,” IEEE Trans. Signal Processing, vol. 42, pp. 102-112, Jan. 1994.
23. M. D. Zoltowski, M. Haardt, and C. P. Mathews, “Closed-form angle estimation with rectangular arrays in element space or beamspace via Unitary ESPRIT,” IEEE Trans. Signal Processing, July 1994, submitted for publication.
24. M. D. Zoltowski, G. M. Kautz, and S. D. Silverstein, “Beamspace Root-MUSIC,” IEEE Trans. Signal Processing, vol. 41, pp. 344-364, Jan. 1993.