WSEAS Transactions on Communications
Print ISSN: 1109-2742, E-ISSN: 2224-2864
Volume 17, 2018
New Multi-Objective Particle Swarm Optimization for Linear Antenna Array Synthesis
Authors: ,
Abstract: Antenna arrays encompass a very vital job in processing and detecting signals received from diverse directions. They are preferred over single element antennas owing to the limitations that exist in the latter in directivity and bandwidth. These limitations are avoided by using the array antennas which associates every element of antenna to different geometrical and electrical configurations to facilitate its beam pattern to be modified with phase and/or amplitude distribution which are called the array weights. The most significant problems to be dealt with in an array antenna design are the control of nulls and the SLL reduction. Lots of researches have used the evolutionary algorithms for obtaining these two objectives. The approaches that were designed for this purpose tackle the objectives simultaneously by creating single objective functions and then taking weighted sum for the objective functions. In this paper, to evade the problems associated with the use of the weighted sum approach, a MO formulation of the problem and a recent approach called Roulette Wheel Multi-objective Particle Swarm Optimization are used. The goal is to obtain the “least standard side lobe level” and a “null reduce” at specific directions. These two goals are contradicting that’s why using the multi-objective optimization is suitable for solving this problem. To test the performance level of the applied method of the multi-objective approach, it is very important to get Pareto optimal which is the way of solving the multi-objective problems. In this paper, the MOPSO is introduced to obtain the Pareto optimal fronts for the two contradicting objectives to show the effectiveness of planned algorithm showing effective results. Improved results for reduced SLLs and null depth are obtained.
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Pages: 142-152
WSEAS Transactions on Communications, ISSN / E-ISSN: 1109-2742 / 2224-2864, Volume 17, 2018, Art. #17