IEEE Access (Jan 2024)

Evaluation of Kaiser Function-Based Linear Array Performance in Suppressing SLL and Its Experimental Approach

  • Hartuti Mistialustina,
  • Chairunnisa,
  • Achmad Munir

DOI
https://doi.org/10.1109/ACCESS.2024.3424237
Journal volume & issue
Vol. 12
pp. 94712 – 94732

Abstract

Read online

The power-weighted distribution method is used to satisfy radiation pattern requirements at a certain targeted sidelobe level (SLL) suppression. This article reports a detailed discussion of theoretical and experimental approaches for the application of the Kaiser function in power-weighted linear array prototypes. An exploration of the design and realization of a Kaiser function-based linear array was presented. Furthermore, performance evaluations were performed for several important factors in the Kaiser function-based linear array configuration. The performance evaluations include feeding network variations, number of element (N) variations, and inter-element distance (d) variations. The prototype of Kaiser function-based linear array was configured by a serial feeding type on the folded structure of a proximity-coupled feeding network. The Kaiser function parameter, $\beta $ , is used to determine the set of weighting coefficients. In the application of $\beta $ value of 2, the SLL suppression is 34.63 dB – 34.78 dB for simulation result, and 27.96 dB – 33.47 dB for measurement result. A performance comparison with a uniform linear array and a Chebyshev function-based linear array in an equal configuration is also shown. The Kaiser function utilization as a weighting coefficient in a linear array design shows a significant increase of 20 dB – 30 dB in SLL suppression compared to the one with a uniform distribution, and 5 dB – 8 dB in SLL suppression compared to the Chebyshev function-based linear array. The implementation of the power-weighted distribution method with Kaiser functions resulted in good results for the development of more complex designs with a larger number of antenna array elements.

Keywords