Spatial Smoothing Algorithm for DOA Estimation of Circular Arrays

In this paper, we explore a spatial smoothing algorithm for DOA estimation specifically designed for circular arrays. This algorithm enhances DOA estimation accuracy by processing the time-varying characteristics of received signals. The implementation utilizes time delays and multipath effects during signal propagation to eliminate various interferences that may occur during transmission. The core algorithm involves partitioning the circular array into overlapping subarrays and computing covariance matrices for each subarray. Key functions include: - Subarray formation with configurable overlap parameters - Covariance matrix averaging across subarrays - Eigenvalue decomposition for signal subspace estimation - MUSIC (Multiple Signal Classification) algorithm implementation for peak detection Through sophisticated signal processing techniques, this algorithm provides improved estimation of signal arrival directions and angles, thereby enhancing the accuracy and reliability of signal processing systems. The code includes optimization for circular array geometry and handles coherent signal scenarios through spatial smoothing pre-processing.