Synthesis of Linear Antenna Array with Optimal SLL and Beam Width
Grandhi Challa Ram1, D. Girish Kumar2, G. R. L. V. N. S. Raju3
1G. Challa Ram , Assistant Professor , Department of Electronics and Communication Engineering, Shri Vishnu Engineering College, A.P.
2D. Girish kumar, Assistant Professor , Department of Electronics and Communication Engineering, Shri Vishnu Engineering College, A.P.
3G. R. L. V. N. S. Raju, Professor and head , Department of Electronics and Communication Engineering, Shri Vishnu Engineering College, A.P.
Manuscript received on April 02, 2020. | Revised Manuscript received on April 15, 2020. | Manuscript published on May 30, 2020. | PP: 391-395 | Volume-9 Issue-1, May 2020. | Retrieval Number: A1612059120/2020©BEIESP | DOI: 10.35940/ijrte.A1612.059120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In many areas of wireless communications, there is a need for high directive radiating beams. To generate such a high directive beams, a linear array of antennas is preferred to that of using a single antenna. Generally a narrow beam width tends to have high directivity but specific to the applications there is also a need for wider beam widths. In case of a radar application it requires a narrow beam width when it is operating in target mode and on the other hand it requires wider beam width when it works under search mode. These optimal beam width variations can be obtained by using Optimization techniques. In this paper Biogeography based Optimization algorithm is used to generate narrow and wide beam widths for a Linear array antenna. While we try to optimize the beam widths of a linear array it will lead to an increase in the side lobe level which make it unavailable for practical applications. As a sensible antenna should always posses a very low side lobe levels a tradeoff should be made for both side lobe level and beam width. This tradeoff which has an optimal side lobe level along with directivity can be achieved by proposed fitness function optimization. The results obtained by using Genetic algorithm and Biogeography based optimization algorithm are compared.
Keywords: Biogeography Based Optimization (BBO), First Null Beam width (FNBW), Genetic Algorithm (GA), Side Lobe Level (SLL).
Scope of the Article: Genetic Algorithm