Maximum Likelihood Direction of Arrival Estimation using GWO Algorithm
Anoop Raghuvanshi, Abhinav Sharma, Mukul Kumar Gupta · 2022
An important aspect in wireless communication is the estimation of the direction/angle of incident signals, which is the major concern for the researchers. There exist several algorithms based on spectral and eigen structure methods, which find the angle of the incoming signals. These techniques are not adequate in estimating the angle of the incident signals in low SNR (signal to noise ratio) and coherent channel environment. Maximum Likelihood (ML) is a standard direction of estimation (DOA) technique which accurately finds the direction of signals in varying conditions. ML is estimated by minimizing the complex nonlinear function with respect to indeterminable parameters. In this paper, author explored GWO (Grey Wolf Optimization) and SCA (Sine Cosine Algorithm) for optimizing ML function that can be utilized for estimation of angle of incident signal in low SNR environment for uniform linear array (ULA). The simulated results obtained shows that ML-GWO outperforms ML-SCA, spectral based and eigen structure techniques for the two parameters of concern which are Probability of Resolution (PR) and Root Mean Square Error (RMSE).