Soft Computing Algorithms for Synthesis of Array Antennas
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Antennas are key components of any wireless system which allows for transfer of a signal to waves. Array pattern synthesis methods are significant in designing an antenna with highly directive characteristics, maximum side lobe level (SLL) suppression while preserving the beam width and specified nulls to reduce the interference effect. In this book, the antenna array synthesis has been viewed as an optimization problem. To achieve effective solution of this problem, a recent wind driven optimization algorithm and other nature and bio-inspired algorithms such as PSO, BFO, BEES Algorithm , PGSA...
Antennas are key components of any wireless system which allows for transfer of a signal to waves. Array pattern synthesis methods are significant in designing an antenna with highly directive characteristics, maximum side lobe level (SLL) suppression while preserving the beam width and specified nulls to reduce the interference effect. In this book, the antenna array synthesis has been viewed as an optimization problem. To achieve effective solution of this problem, a recent wind driven optimization algorithm and other nature and bio-inspired algorithms such as PSO, BFO, BEES Algorithm , PGSA, MTACO, IWO, Backtracking Search Algorithm (BSA), GA, COA, Fire fly Algorithm (FA), Bio-geography Based Optimization (BBO) and many others. They have been successfully implemented for solving multidimensional and multimodal problems such as the uniform linear array (ULA) and non-uniform circular array (NUCA) antenna pattern synthesis to ensure maximal SLL suppression, null control subject to constraint on beam width. This book is bound to attract readers towards utilizing WDO and other soft algorithms in antenna design and other engineering problems.
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