A Novel Elliptical-Cylindrical Antenna Array for Radar Applications

Abstract

With the advancement of radar technology, detecting objects, determining the structure of the target, and estimating the direction and the speed is prominently increasing. There is no doubt that small cross section targets are hardly identified and determined. This problem demands the need for antenna pattern synthesizing with a high gain and highly reduced sidelobe level (SLL). In this paper, an optimization technique called self-adaptive differential evolution (SaDE) that can be able to learn and behave intelligently is integrated to determine an optimal set of excitation weights in the design of elliptical–cylindrical antenna array (ECAA). In this work, the SaDE-optimized hyper beam is proposed to achieve qualified radar performances. Nonuniform excitation amplitudes of the individual array elements of ECAA are performed to obtain reduced SLL, high directivity, and flexible radiation pattern which are crucial in radar applications. With increased antenna gain, small cross section objects can be accurately identified and determined even in volatile environment where there are different natures of interferences. Besides, the proposed work enables steering electronically and it allows scanning very rapidly across a wide range of elevation and azimuth planes. To evaluate the improved performance of the proposed optimization scheme, comparison is done with genetic algorithm (GA), particle swarm optimization (PSO), biogeography-based optimization (BBO), and invasive weed optimization (IWO) against different parameters. In general, the proposed work of pattern synthesis has resulted in much better reduction in SLL and first null beamwidth (FNBW) than both the uniformly excited and thinned ECAA. The results of this study clearly revealed that the SLL is highly reduced at a very directive beamwidth. The proposed antenna array offers high system availability over wide range of radar applications.