Phased array antennas are a viable solution to a number of problems related to radio communications applications. In this work, the multi-objective stochastic MOPSO algorithm is used to optimize the spatial configuration of a symmetric phased linear array. The defined optimization goals were the suppression of the radiation pattern sidelobes at a specified maximum scan angle as well as the minimization of the induced voltages correlation at the receiver frontend in order to maximize diversity performance. Non-linear constraints were enforced on the solution set, related to the multi-antenna system aperture efficiency and related to the mismatching when the array is scanned. The obtained optimized configurations for an array composed of 16 dipoles resulted in reducing the sidelobes up to 2.5 dB, when scanned 60° away from broadside, compared to a linear array with elements spaced λ/2 apart. Furthermore, the optimized dipole arrays were characterized by a maximum element correlation of 0.12 to 0.43. The performance of obtained configurations was shown to be tolerant to feed phase variations that appear in realistic implementations. The arrays were analyzed employing the Method of Moments (MoM).
2. Li, W. T., X. W. Shi, and Y. Q. Hei, "An improved particle swarm optimization algorithm for pattern synthesis of phased arrays," Progress In Electromagnetics Research, Vol. 82, 319-332, 2008.
3. Donelli, M., R. Azaro, F. G. B. De Natale, and A. Massa, "An innovative computational approach based on a particle swarm strategy for adaptive phased arrays control," IEEE Trans. Antennas Propagat., Vol. 54, No. 3, 888-898, 2006.
4. Boeringer, D. W. and D. H. Werner, "Efficiency-constrained particle swarm optimization of a modified bernstein polynomial for conformal array excitation amplitude synthesis," IEEE Trans. Antennas Propagat., Vol. 53, No. 8, 2662-2673, 2005.
5. Jin, , N. B. and Y. Rahmat-Samii, "Parallel particle swarm optimization and finite-difference time-domain (PSO/FDTD) algorithm for multiband and wide-band patch antenna designs," IEEE Trans. Antennas Propagat., Vol. 53, No. 11, 3459-3468, 2005.
6. Coello, C. A. C., G. T. Pulido, and M. S. Lechuga, "Handling multiple objectives with particle swarm optimization," IEEE Trans. Evolutionary Comput., Vol. 8, No. 3, 256-279, 2004.
7. Jin, N. and Y. Rahmat-Samii, "Advances in particle swarm optimization for antenna designs: Real-number, binary, single-objective and multiobjective implementations," IEEE Trans. Antennas Propagat., Vol. 55, No. 3, 556-567, 2007.
8. Chamaani, S., M. S. Abrishamian, and S. A. Mirtaheri, "Multi-objective optimization of UWB monopole antenna," Progress In Electromagnetics Research C, Vol. 8, 83-94, 2009.
9. Bray, M. G., D. H. Werner, D. W. Boeringer, and D. W. Machuga, "Optimization of thinned aperiodic linear phased arrays using genetic algorithms to reduce grating lobes during scanning," IEEE Trans. Antennas Propagat., Vol. 50, No. 11, 1732-1742, 2003.
10. Zhu, Y. Z. , Y. J. Xie, Z. Y. Lei, and T. Dang, "A novel method of mutual coupling matching for array antenna design," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 8, 1013-1024, 2007.
11. Wallace, J. W. and M. A. Jensen, "Termination-dependent diversity performance of coupled antennas: Network theory analysis," IEEE Trans. Antennas Propagat., Vol. 52, No. 1, 98-105, 2004.
12. Broyde, F. and E. Clavelier, "Taking advantage of mutual coupling in radio-communication systems using a multi-port antenna array," IEEE Antennas Propag. Mag., Vol. 4, No. 4, 208-220, 2007.
13. Harrington, R. F., Field Computation by Moment Methods, Wiley-IEEE Press, 1993.
14. Orfanidis, S. J., Electromagnetic Waves and Antennas, Rutgers University, 2004.
15. Takamizawa, K., "Analysis of highly coupled wideband antenna arrays using scattering parameter network models,", 45-60, the Faculty of the Virginia Polytechnic Institute and State University, Virginia, 2002.
16. Pozar, D. M., Microwave Engineering, Wiley-India, 2009.
17. Weber, J. , C. Volmer, K. Blau, R. Stephan, and M. A. Hein, "Miniaturized antenna arrays using decoupling networks with realistic elements," IEEE Trans. Microwave Theory and Tech., Vol. 54, No. 6, 2733-2740, 2006.
18. Nebro, A. J., J. J. Durillo, J. Garcia-Nieto, C. A. C. Coello, F. Luna, and E. Alba, "SMPSO: A new PSO metaheuristic for multi-objective optimization," Proc. 2009 IEEE Symposium on Computational Intelligence in Multi-criteria Decision-making, 66-73, Mar. 30-Apr. 2, 2009.
19. Deb, K., Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley & Sons, 2001.