Optimizing Linear Adaptive Broadside Array Antenna by Amplitude-Position Perturbations Using Memetic Algorithms

Abstract

AbstractThis paper presents an innovative implementation method of the broadside antenna by using adaptive array antenna. Compared with the conventional ones, its performance can be improved because it is possible to null the interfering signals adjustably and at the same time maximize the main lobe towards the array normal. Thus the optimal radiation pattern can be obtained. The conventional broadside array only can make a main lobe toward the array normal, but it can not cancel the interferences. So, it is easy to be seen for the significance of this proposed method. In many applications, it is required to have the maximum radiation of an array directed toward the array normal. An optimal radiation pattern design for an adaptive broadside array antenna is not only to derive the maximum power radiation at the array normal direction but also to suppress interference by placing nulls at the directions of the interfering sources. The signal to interference ratio (SIR) can be maximized. Memetic algorithm is used for the search of the optimal weighting of array factor of the optimal radiation pattern by amplitude-position perturbations.KeywordsLocal SearchRadiation PatternTravelling Salesman ProblemMemetic AlgorithmMain LobeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.