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International Journal of Antennas and Propagation
Volume 2015, Article ID 495879, 7 pages
http://dx.doi.org/10.1155/2015/495879
Research Article

An Opportunistic Array Beamforming Technique Based on Binary Multiobjective Wind Driven Optimization Method

1Key Laboratory of Radar Imaging and Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2College of Electronic Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China
3Centre for Communication Systems, Durham University, Durham DH1 3LE, UK

Received 10 May 2015; Revised 1 August 2015; Accepted 19 August 2015

Academic Editor: Stefano Selleri

Copyright © 2015 Zhenkai Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We present a novel binary version of multiobjective wind driven optimization (WDO) for emitted beamforming of opportunistic array radar, which is assumed as a multiobjective optimization problem. Firstly, the emitted signal model and objective functions of optimization are presented. Then the algorithm proposes a new definition of the position vector of air parcel, and brings a good discretization interpretation of continuous WDO. For multiobjective optimization, the grey relational grade (GRG) is then used to measure the similarity between the best two solutions for these two objectives. The best pressure locations with the maximum GRG will be recorded as the best two candidate solutions to the problem, and a final optimization result will be selected according to the importance of the two objectives. Finally, the proposed improved WDO has been applied for the optimal design of beamforming of the opportunistic antenna array, which needs a trade-off between the 3 dB main beam width and sidelobe level. The simulation results show that the proposed method outperforms conventional particle swarm optimization (PSO) in the optimal beamforming by achieving more reduction in the sidelobe level and saving more runtime.