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International Journal of Antennas and Propagation
Volume 2017, Article ID 2563901, 7 pages
https://doi.org/10.1155/2017/2563901
Research Article

Synthesizing Sum and Difference Patterns with Low Complexity Feeding Network by Sharing Element Excitations

College of Electronics Engineering, Ninevah University, Mosul 41001, Iraq

Correspondence should be addressed to Jafar Ramadhan Mohammed; moc.oohay@marrafaj

Received 12 January 2017; Revised 6 April 2017; Accepted 11 April 2017; Published 20 April 2017

Academic Editor: Herve Aubert

Copyright © 2017 Jafar Ramadhan Mohammed. 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

In monopulse radar antennas, the synthesizing process of the sum and difference patterns must be fast enough to achieve good tracking of the targets. At the same time, the feed networks of such antennas must be as simple as possible for efficient implementation. To achieve these two goals, an iterative fast Fourier transform (FFT) algorithm is used to synthesize sum and difference patterns with the main focus on obtaining a maximum allowable sharing percentage in the element excitations. The synthesizing process involves iterative calculations of FFT and its inverse transformations; that is, starting from an initial excitation, the successive improved radiation pattern and its corresponding modified element excitations can be found repeatedly until the required radiation pattern is reached. Here, the constraints are incorporated in both the array factor domain and the element excitation domain. By enforcing some constraints on the element excitations during the synthesizing process, the described method provides a significant reduction in the complexity of the feeding network while achieving the required sum and difference patterns. Unlike the standard optimization approaches such as genetic algorithm (GA), the described algorithm performs repeatedly deterministic transformations on the initial field until the prescribed requirements are satisfied. This property makes the proposed synthesizing method converge much faster than GA.