Non-Statistical Multi-Beamformer
- 1 Electrical Engineering and Computer Science Department, Texas A&M University-Kingsville, Kingsville, USA
- 2 Electrical Engineering and Computer Science Department, Syracuse University, Syracuse, USA
- 3 Electrical Engineering and Computer Science Department, Syracuse University, Syracuse, USA
- 4 Electrical Engineering and Computer Science Department, Texas A&M University-Kingsville, Kingsville, USA
Abstract
In this paper, a multiple beamforming technique is presented by using a direct data domain least squares (D3LS) approach. Direct data domain approach is very suitable for real time applications since it utilizes only a single snapshot of data as opposed to statistical approaches where multiple measurements have to be taken and the covariance matrix has to be formed. It is also very effective especially in the case of blinking jammers where the statistical approaches will fail or needs to perform additional tasks to overcome it. It has been previously shown that the D3LS can successfully handle only one or two Signal of Interests (SOI). Here, we have developed a new technique where multiple SOI can be handled simultaneously. Numerical simulations have shown that the new approach can maximize the signals from the direction of the SOI at the same time minimizing the jammers. The new approach can be successfully applied in the satellite communications, Over the Horizon Radars (OTHR) as well as wireless communications to detect or track multiple targets simultaneously.
- M. Chryssomallis, “Smart Antennas,” IEEE Antennas and Propagation Magazine, Vol. 42, No. 3, 2000, pp. 129-136. doi:10.1109/74.848965
- R. Schreiber, “Implementation of Adaptive Array Algorithms,” IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 342, No. 5, 1986, pp. 1038-1045. doi:10.1109/TASSP.1986.1164943
- I. Chiba, W. Chujo and M. Fujise, “Beamspace Constant Modulus Algorithm Adaptive Array Antennas,” Proceedings of the IEEE 8th International Conference on Antennas and Propagation, Edinburgh, 1993, pp. 975-978.
- S. Choi and T. Sarkar, “Adaptive Antenna Array Utilizing the Conjugate Gradient Method for Multipath Mobile Communications,” Signal Processing, Vol. 29, No. 3, 1992, pp. 319-333. doi:10.1016/0165-1684(92)90090-J
- A. El Zooghby, C. G. Christodoulou and M. Georgiopoulos, “Neural Network Based Adaptive Beamforming for One and Two Dimensional Antenna Arrays,” IEEE Transactions on Antennas and Propagation, Vol. 46, No. 12, 1998, pp. 18919-1893.
- S. Das, “Smart Antenna Design for Wireless Communication using Adaptive Beam-forming Approach,” TENCON 2008 IEEE Region Conference, Hyderabad, 19-21 November 2008, pp. 1-5.
- B. Widrow and S. D. Stearns, “Adaptive Signal Processing,” Pearson Education Asia, Second Indian Reprint, 2002.
- B. D. Van and K. M. Buckley, “Beamforming: A Versatile Approach to Spatial Filtering,” IEEE ASSP Magazine, Vol. 5, No. 2, 1988, pp. 4-24. doi:10.1109/53.665
- T. K. Sarkar, S. Park, J. Koh and R. A. Schneible, “A Deterministic Least Squares Approach to Adaptive Antennas,” Digital Signal Processing—A Review Journal, Vol. 6, 1996, pp. 185-194.
- W. Choi, T. K. Sarkar, H. Wang and E. L. Mokole, “Adaptive Processing Using Real Weights Based on a Direct Data Domain Least Squares Approach,” IEEE Transactions on Antennas and Propagation, Vol. 54, No. 1, 2006, pp. 182-191. doi:10.1109/TAP.2005.859753
- W. Choi and T. K. Sarkar, “Multiple Beamforming Technique Using Direct Data Domain Least Squares (D3LS) Approach,” IEEE Antennas and Propagation Society International Symposium, Albuquerque, 9-14 July 2006, pp. 3315-3318. doi:10.1109/APS.2006.1711322