Modeling an Optimized Adaptive Linear Antenna Array

Abstract

Results and Discussion: The simulation results provided showed that the proposed DOA algorithm had a better angular resolution which is comparable to higher resolution Multiple Signal Classification (MUSIC) algorithms without any specific number of snapshots and true angle of arrival of incident signals. The computational complexity found was less as it did not require covariance matrix and sub-space calculations. The estimation of computational time showed a good performance. Simulation result revealed that the main beam, null placement and beam steering ability of the proposed adaptive beamforming was better as compared with well known Least Mean Square (LMS) and Constant Modulus Algorithm (CMA) beamforming algorithms for low values of SNR. The proposed PSO based adaptive antenna system showed improvement of the performance for low strength of desired signal. Besides, fewer numbers of iterations were required to converge. newlineThe limitation of SPM in placing the user and the interferer position was resolved using MSPM and the problem of increased SLL is solved using the combination of MSPM and PSO. newlineConclusion: The progressive phase incident DOA estimation shows better resolution and lesser computational complexity. PSO based beamformer shows optimized radiation pattern with increased SINR for lower values of SNR. The array needed lesser time to make an adaptive beam. newlineIt was also found that as some of the roots were fixed in MSPM hence fewer numbers of variables were used in the optimization which reduces the complexity of the optimization algorithm. newline