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.
Highlights
Conventional approaches for synthesizing sum and difference patterns require the use of two separate element excitations for one monopulse radar antenna, for example, Taylor excitation [1] for sum pattern formation and Bayliss excitation [2] for difference pattern formation
These approaches require a feed network of considerable complexity [3,4,5]. This drawback of the conventional approaches can be overcome by using subarrays [6, 7] or another method known as common element excitations [8, 9]. These approaches allow a significant reduction in the complexity of the feeding network, they rely on the use of an optimization procedure, by either simulated annealing or genetic algorithm
This paper introduces a simple and fast algorithm for synthesizing sum and difference patterns with a number of common element excitations for the purpose of reducing the feeding network
Summary
Conventional approaches for synthesizing sum and difference patterns require the use of two separate element excitations for one monopulse radar antenna, for example, Taylor excitation [1] for sum pattern formation and Bayliss excitation [2] for difference pattern formation. These approaches require a feed network of considerable complexity [3,4,5]. It delivers results much faster as compared to standard optimization approaches
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