High-Resolution Direction Finding on Uniform Linear Arrays: A Comparative Evaluation of MUSIC Algorithm Derivatives

This paper investigates various Multiple Signal Classification (MUSIC) algorithms for Direction of Arrival (DoA) estimation, including 'Traditional MUSIC', 'Root MUSIC', 'Forward/Backward Spatial Smoothing (FBSS) MUSIC', and 'Improved/Modified MUSIC'. The study elaborates on the principles underlying each algorithm and explores the factors influencing the accuracy of DoA estimation, such as the number of array elements, antenna spacing, number of snapshots, Signal-to-Noise Ratio (SNR), and scanning angle resolution. Through extensive MATLAB simulations employing the Monte Carlo method, the performance of these algorithms is evaluated and compared in scenarios involving coherent, non-coherent, and single/dual-source incident signals. The Root Mean Square Error (RMSE) is calculated as a function of the aforementioned parameters to quantify estimation accuracy. Additionally, the computational efficiency of each algorithm is assessed by comparing their execution durations. The results provide valuable insights into the strengths and limitations of each MUSIC variant, offering guidance for their application in practical DoA estimation tasks.