Bi-capon beamforming for MIMO radar based on rank-reduced correlation matrix

doi:10.1016/S1005-8885(13)60012-6

Acta Metallurgica Sinica(English letters) ›› 2013, Vol. 20 ›› Issue (1): 85-90.doi: 10.1016/S1005-8885(13)60012-6

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Bi-capon beamforming for MIMO radar based on rank-reduced correlation matrix

1. School of Information Engineering, Chang’an University, Xi’an 710064, China 2. National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China 3. Department of Electrical and Computer Engineering, Mississippi State University, MS 39762, USA

Received:2012-06-06 Revised:2012-09-26 Online:2013-02-28 Published:2013-02-28
Contact: Jie He E-mail:cathyhejie@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (60971111), the Natural Science Foundation of Shaanxi Province (2011JQ8041).

Abstract

Abstract:

A bi-capon beamforming (BCB) algorithm for multi-input multi-output (MIMO) radar is developed on the basis of correlation domain. By vectorizing the echo matrix and its transpose, the conventional capon cost function is transformed into bi-capon quadratic functions. By calculating two lower dimensional weight vectors with sub-matrices of the correlation matrix, BCB can significantly decrease the computational complexity and the requirement of training samples. In the presence of short data records, BCB can achieve better interference suppression performance than fully adaptive capon algorithm. Simulation results are presented to demonstrate the effectiveness of the proposed method.

Key words:

MIMO radar, capon beamforming, correlation, complexity performance

HE Jie, FENG Da-zheng, Nicolas H. Younan, MA Lun. Bi-capon beamforming for MIMO radar based on rank-reduced correlation matrix[J]. Acta Metallurgica Sinica(English letters), 2013, 20(1): 85-90.

References

1. Bliss D W, Forsythe K W. Multiple-input multiple-output (MIMO) radar and imaging: degrees of freedom and resolution. Proceedings of the 37th Annual Asilomar Conference on Signals, Systems and Computers (ACSSC’03): Vol 1, Nov 79-12, 2003, Pacific Grove, CA, USA. Alamitos, CA, USA: IEEE Computer Society, 2003: 54-59

2. Fishler E, Haimovich A, Blum R, et al. Performance of MIMO radar systems: advantages of angular diversity. Proceedings of the 38th Annual Asilomar Conference on Signals, Systems and Computers (ACSSC’04): Vol 1, Nov 7-10, 2004, Pacific Grove, CA, USA. Alamitos, CA, USA: IEEE Computer Society, 2004: 305-309

3. Li J, Stoica P, Xu L, et al. On parameter identifiability of MIMO radar. IEEE Signal Processing Letters, 2007, 14(12): 968-971.

4. Xu L, Li J, Stoica P. Adaptive techniques for MIMO radar. Proceedings of the 4th IEEE Workshop on Sensor Array and Multichannel Processing, Jul 12-14, 2006, Waltham, MA,USA. Piscataway, NJ, USA: IEEE, 2006: 258-262

5. Bekkerman I, Tabrikian J. Target detection and localization using MIMO radars and sonars. IEEE Transactions on Signal Processing, 2006, 54(10): 3873-3883

6. Chen C Y, Vaidyanathan P P. MIMO radar space–time adaptive processing using prolate spheroidal wave functions. IEEE Transactions on Signal Processing, 2008, 56(2): 623-635

7. Ahmed S, Thompson J S, Petillot Y R, et al. Unconstrained synthesis of covariance matrix for MIMO radar transmit beampattern. IEEE Transactions on Signal Processing, 2011, 59(8): 3837-3849

8. Kong L J, Cui G L, Yang X B, et al. Adaptive detector design of MIMO radar with unknown covariance matrix. Journal of Systems Engineering and Electronics, 2010, 21(6): 954-960

9. Jiang H, Wang D F, Liu C. Joint parameter estimation of DOD/DOA polarization for bistatic MIMO radar. The Journal of China Universities of Posts and Telecommunications, 2010, 17(5): 32-37

10. Reed I S, Mallett J D, Brennan L E. Rapid convergence rate in adaptive arrays. IEEE Transactions on Aerospace Electronic Systems, 1974, 10(6): 853-863

11. LaSalle J P. The stability of dynamical systems. Philadelphia, PA, USA: SIAM Press, 1976

12. Li J, Stoica P, Wang Z S. Doubly constrained robust capon beamformer. IEEE Transactions on Signal Processing, 2004, 52(9): 2407-2423

13. Vorobyov S A, Gershman A B, Luo Z. Robust adaptive beamforming using worst-case performance optimization: A solution to the signal mismatch problem. IEEE Transactions on Signal Processing, 2003, 51(2): 313-324

14. Subbarma H ，Abend K. Interference suppression via orthogonal projections: A performance analysis. IEEE Transactions on Antennas Propagation, 1993, 41(9): 1187-1193

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Bi-capon beamforming for MIMO radar based on rank-reduced correlation matrix

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