Browse > Article

Subspace-Based Adaptive Beamforming with Off-Diagonal Elements  

Choi Yang-Ho (강원대학교 전기전자정보통신공학부)
Eom Jae-Hyuck (강원대학교 전기전자정보통신공학부)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.29, no.1A, 2004 , pp. 84-92 More about this Journal
Abstract
Eigenstructure-based adaptive beamfoming has advantages of fast convergence and the insentivity to errors in the arrival angle of the desired signal. Eigen-decomposing the sample matrix to extract a basis for the Sl (signal plus interference) subspace, however, is very computationally expensive. In this paper, we present a simple subspace based beamforming which utilizes off-diagonal elements of the sample matrix to estimate the Sl subspace. The outputs of overlapped subarrays are combined to produce the final adaptive output, which improves SINR (signal-to-interference-plus-noise ratio) comapred to exploiting a single subarray. The proposed adaptive beamformer, which employs an efficient angle estimation is very roubust to errors in both the arrival angles and the number of the incident signals, while the eigenstructure-based beamforer suffers from severe performance degradation.
Keywords
Adaptive arrays; Subspace-based beamforming;
Citations & Related Records
연도 인용수 순위
  • Reference
1 R. A. Monzingo and T. A. Miller, Introduction to Adaptive Arrays. New York: Wiely, 1980
2 D. D. Feldman and L. J. Ghffith, 'A projection approach for robust adaptive beamforming,' IEEE Trans. Signal Processing, vol. SP-42, pp. 867-876, Apr. 1994   DOI   ScienceOn
3 C.-C. Yeh, Simple computation of projection matrix for bearing estimations, IEE Proc. F, vol. 134, pp. 146-150, Apr. 1987
4 Y.-H. Choi, Robust adaptive beamforming by self-correction of look direction errors, IEICE Trans. Commun., vol. E85-B, pp. 694-697, Mar. 2002
5 M. Wax and T. Kailath, Detection of signals by information theoretic criteria, IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-33, pp. 387-392, Aug. 1985   DOI
6 F. Szidarovszky, Principles and Procedures of Numerical Analysis. New York: Plenum Press, 1978
7 L. C. Godara, Application of antenna arrays to mobile communications-Part II: Beamforming and DOA considerations, Proceedings of the IEEE, vol. 85, No. 8, pp. 1195-1247, Aug. 1997   DOI   ScienceOn
8 Y.-H. Choi, Eigenstructure-based adaptive beamforming for coherent and incoherent interference cancellation, IEICE Trans. Commun., vol. E85-B, pp. 633-640, Mar. 2002
9 I. S. Reed, J. D. Mallet and L. E. Brennan, Rapid convergence rate in adaptive arrays, IEEE Trans. Aerosp. Electron. Syst, vol. AES-10, pp. 853-863, Nov. 1974   DOI   ScienceOn
10 M. Wax and Y. Anu, Performance analysis of the minimum variance beamformer, IEEE Trans. Signal Processing, vol. SP-44, pp. 928-937, Apr. 1996   DOI   ScienceOn
11 R. O. Schmidt, Multiple emitter location and signal parameter estimation, IEEE Trans. Antennas Propaga., vol. AP-34, pp. 276-280, Mar. 1986   DOI
12 L. Chang and C.-C. Yeh, Performance of DMI and eigenspace-based beamformers, IEEE Trans. Antennas Propagat, vol. AP-40, pp. 1336-1347, Nov. 1992   DOI   ScienceOn
13 Y.-H. Choi, Subspace method for angle estimation using off-diagonal elements, Etectron. Lett., 2000, vol. 36, No. 7, pp. 685-686, Mar. 2000   DOI   ScienceOn