Robust adaptive beamforming algorithm based on Bayesian approach

Abstract

The performance of adaptive array beamforming algorithms substantially degrades in practice because of a slight mismatch between actual and presumed array responses to the desired signal. A novel robust adaptive beamforming algorithm based on Bayesian approach is therefore proposed. The algorithm responds to the current environment by estimating the direction of arrival (DOA) of the actual signal from observations. Computational complexity of the proposed algorithm can thus be reduced compared with other algorithms since the recursive method is used to obtain inverse matrix. In addition, it has strong robustness to the uncertainty of actual signal DOA and makes the mean output array signal-to-interference-plus-noise ratio (SINR) consistently approach the optimum. Simulation results show that the proposed algorithm is better in performance than conventional adaptive beamforming algorithms.

References

1. Brennan L E, Mallet J D, Reed I S . Adaptive arrays in airborne MTI radar. IEEE Transactions on Antennas and Propagation, 1976, 24(5): 607–615. doi:10.1109/TAP.1976.1141412
2. Krolik J L . The performance of matched-field beamformers with Mediterranean verticalarray data. IEEE Transactions on SignalProcessing, 1996, 44(10): 2605–2611. doi:10.1109/78.539043
3. Gorodetskaya E Y, Malekhanov A I, Sazontov A G, et al.. Deep-water acoustic coherence at long ranges:theoretical prediction and effects on large-array signal processing. IEEE Journal of Oceanic Engineering, 1999, 24(4): 156–171. doi:10.1109/48.757268
4. Godara L C . Application of antenna arrays to mobile communications. Part II:beam-forming and direction-of-arrival considerations. In: Proceedings of the IEEE. 1997, 85(8): 1195–1245. doi:10.1109/5.622504
5. Wang J K, Song X, Wang H . Robust RLS adaptive beamforming algorithm. Journal of Northeastern University (Natural Science), 2005, 26(1): 29–31 (in Chinese)
6. Frost III O L . An algorithm for linearly constrained adaptive array processing. In: Proceedings. of the IEEE, 1972, 60(8): 926–935. doi:10.1109/PROC.1972.8817
7. Buckley K M, Griffiths L J . An adaptive generalized sidelobecanceller with derivative constraints. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 311–319. doi:10.1109/TAP.1986.1143832
8. Zhang S, Thng I L . Robust presteering derivativeconstraints for broadband antenna arrays. IEEE Transactions on Signal Processing, 2002, 50(1): 1–10. doi:10.1109/78.972477
9. Carlson B D . Covariance matrix estimation errors and diagonal loading in adaptivearrays. IEEE Transactions on Aerospaceand Electronic Systems, 1988, 24(4): 397–401. doi:10.1109/7.7181
10. Ganz M W, Moses R L, Wilson S L . Convergence of the SMI and the diagonally loaded SMIalgorithm with weak interference. IEEETransactions on Antennas and Propagation, 1990, 38(3): 394–399. doi:10.1109/8.52247
11. Carlson B D . Equivalence of adaptive array diagonal loading and omnidirectionaljamming. IEEE Transactions on Antennasand Propagation, 1995, 43(5): 540–541. doi:10.1109/8.384201
12. Li J, Stoica P, Wang Z . On robust Capon beamforming and diagonal loading. IEEE Transactions on Signal Processing, 2003, 51(7): 1702–1715. doi:10.1109/TSP.2003.812831
13. Capon J . High-resolutionfrequency-wavenumber spectrum analysis. In: Proceedings of the IEEE. 1969, 57(8): 1408–1418. doi:10.1109/PROC.1969.7278
14. Hodgkiss W S, Nolte L W . Optimal array processor performancetrade-offs under directional uncertainty. IEEE Transactions on Aerospace and Electronic Systems, 1976, 12(5): 605–615. doi:10.1109/TAES.1976.308263
15. Bell K L, Ephraim Y, Van Trees H L . Robust adaptive beamforming under uncertainty in sourcedirection-of-arrival. In: Proceedings ofthe 8th IEEE Signal Processing Workshop on Statistical Signal andArray Processing, Greece. IEEE, 1996, 546–549
16. Bell K L, Ephraim Y, Van Trees H L . A Bayesian approach to robust adaptive beamforming. IEEE Transactions on Signal Processing, 2000, 48(2): 386–398. doi:10.1109/78.823966