Optimization of Sparse Randomly Spaced Linear Antenna Array using Hybrid Iteratively Reweighted Least Squares

Authors

  • Sarafadeen Ajibola Mustapha 1. Department of Electronics and Telecommunication Engineering, Ahmadu Bello University, Zaria, Kaduna State, NIGERIA. 2. NASENI Solar Energy Limited, Karshi
  • S. M. Sani Department of Electronics and Telecommunication Engineering, Ahmadu Bello University, Zaria, Kaduna State, NIGERIA.
  • K. A. Abu-Bilal Department of Electronics and Telecommunication Engineering, Ahmadu Bello University, Zaria, Kaduna State, NIGERIA.

Keywords:

uniformly spaced antenna array, randomly spaced antenna array, sidelobes level, mainlobe, iteratively reweighted least squares, sparsity

Abstract

Uniformly Spaced Antenna Array (USAA) with large radiating elements is characterized with complex feed network as well as high sidelobes level (SLL) leading to interference and power wastage. To solve these problems, research works have been carried out using different methodologies, to synthesize sparse Randomly Spaced Antenna Array (RSAA) to reconstruct the desired radiation pattern using fewer radiating elements and suppressed SLL. In this paper, a deterministic Iteratively Reweighted Least Squares (IRLS) algorithm based on the concept of compressed sensing was used to achieve better sparsity through thinning. The SLL was also suppressed using Convex Technique (CT). The performance of the synthesized array was evaluated in terms of sparsity and SLL. Simulation results showed that it has a higher sparsity of 12 elements with SLL of -39.44dB which are 14.29% and 28.72% improvements, respectively compared to previous research work with 14 elements and SLL of -30.64dB.

http://dx.doi.org/10.4314/njt.v40i2.16

Downloads

Published

2021-04-28

Issue

Section

Computer, Telecommunications, Software, Electrical & Electronics Engineering