Abstract
Salp Swarm Algorithm (SSA) is used to design an optimal non uniform circular antenna arrays. Salp Swarm Algorithm which mimics the swarming behavior of salps in oceans is a nature-inspired optimization method. As it is simple and easy to apply, it has been applied to many different problems in the literature. SSA method optimally determined the positions and amplitudes of the circular antenna array elements to obtain radiation patterns with a low maximum sidelobe level (MSL) and narrow half power beam width (HPBW). Different sizes of antennas with 8, 10 and 12 elements are discussed to demonstrate the capability of the SSA algorithm. The results of MSL and HPBW obtained by SSA for the synthesis of circular antenna arrays are better than other compared optimization methods.
Highlights
IN RECENT years, the interest in antenna arrays with highdirectionality and gain used in different areas such as wireless communication, mobile, sonar, radar has been increasing
If we examine the half power beam width (HPBW) value, it is seen that the value achieved with Salp Swarm Algorithm (SSA) is better than the results of Taguchi [7] method
The position and amplitude values of the nonuniform circular antenna arrays having 8, 12, and 20 isotropic elements are optimized by SSA method
Summary
IN RECENT years, the interest in antenna arrays with highdirectionality and gain used in different areas such as wireless communication, mobile, sonar, radar has been increasing. The communication systems performance used in many different applications is highly dependent on the design of the antenna array used. Antenna arrays can be in different structures such as circular, linear and elliptic depending on their geometric structure. Circular Antenna Arrays (CAAs) among these antenna types have become very popular especially in radar, wireless and mobile communication systems. CAAs are not affected by the mutual effect because they do not have edge elements [2]. Due to these advantages, the optimum design of CAAs is of great interest in the literature. In [6], seeker optimization algorithm used
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