Ram Gopi, Mandal Durbadal, Kar Rajib, Ghoshal Sakti Prasad
Department of Electronics and Communication Engineering, National Institute of Technology, Durgapur, India.
ScientificWorldJournal. 2013 Jul 22;2013:982017. doi: 10.1155/2013/982017. eCollection 2013.
A novel optimization technique which is developed on mimicking the collective animal behaviour (CAB) is applied for the optimal design of hyper beamforming of linear antenna arrays. Hyper beamforming is based on sum and difference beam patterns of the array, each raised to the power of a hyperbeam exponent parameter. The optimized hyperbeam is achieved by optimization of current excitation weights and uniform interelement spacing. As compared to conventional hyper beamforming of linear antenna array, real coded genetic algorithm (RGA), particle swarm optimization (PSO), and differential evolution (DE) applied to the hyper beam of the same array can achieve reduction in sidelobe level (SLL) and same or less first null beam width (FNBW), keeping the same value of hyperbeam exponent. Again, further reductions of sidelobe level (SLL) and first null beam width (FNBW) have been achieved by the proposed collective animal behaviour (CAB) algorithm. CAB finds near global optimal solution unlike RGA, PSO, and DE in the present problem. The above comparative optimization is illustrated through 10-, 14-, and 20-element linear antenna arrays to establish the optimization efficacy of CAB.
一种基于模拟群体动物行为（CAB）开发的新型优化技术被应用于线性天线阵列的超波束形成优化设计。超波束形成基于阵列的和波束与差波束方向图，每个方向图都提升到一个超波束指数参数的幂次。通过优化电流激励权重和均匀的阵元间距来实现优化后的超波束。与线性天线阵列的传统超波束形成相比，应用于同一阵列超波束的实编码遗传算法（RGA）、粒子群优化算法（PSO）和差分进化算法（DE）在保持超波束指数值不变的情况下，能够降低旁瓣电平（SLL），并使第一零束宽（FNBW）相同或更小。此外，所提出的群体动物行为（CAB）算法进一步降低了旁瓣电平（SLL）和第一零束宽（FNBW）。在当前问题中，与RGA、PSO和DE不同，CAB找到了接近全局最优的解。通过10元、14元和20元线性天线阵列展示了上述比较优化过程，以确立CAB的优化效果。
