Design and Performance Analysis of a 2*2 Microstrip Patch Array Antenna at 2.45Ghz Using Machine Learning

Electronics and communication engineering

This project is about developing a 2*2 rectangular microstrip patch array antenna and making a primary analysis of the antenna and introduces the machine learning (ML) technique in order to enhance the antenna performance. The parameters of the antenna, namely, gain and S11 play the key role during the testing process and must be analyzed with the highest degree of accuracy. It is the design process which aims carefully at getting the desirable features to exercise the advantages, being poured in microstrips patch array. The random Forest Algorithm, again the extension, gains in popularity and is used as the part of machine learning to make the design process much better. By the assist of Antenna simulators we got the result in which we have gain and S11 parameters together which is a needed train dataset for the ML model. User interface has been created by using streamlit framework providing user with GUI from that allows inputs of parameters specific to an antenna and return instant responses regarding gain and S11.Machie Learning models are checked accuracy and efficiency in various testing which are known to be in agreement with simulated result. The uses of automation and machine learning are about more than merely speeding up the analysis process, but may also prove valuable in suggesting areas that require improvements or optimizations for future antenna designs.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.