Direction of Arrival Estimation Using Uniform Linear Arrays

In signal processing, Direction of Arrival (DOA) estimation using uniform linear arrays is a fundamental technique for effectively locating signal sources. To enhance DOA estimation accuracy, several optimization methods are typically employed. Spatial smoothing technique improves estimation robustness by decorrelating coherent signals through subarray averaging - implemented by dividing the array into overlapping subarrays and averaging their covariance matrices. The Toeplitz method utilizes matrix reconstruction techniques where the ideal covariance matrix structure is restored by enforcing Toeplitz properties through matrix averaging operations, enabling more precise source localization. The MUSIC (Multiple Signal Classification) algorithm employs eigenvalue decomposition of the covariance matrix to separate signal and noise subspaces, then identifies DOA peaks through spectrum analysis using orthogonal properties between subspaces. In practical implementation, these methods involve key MATLAB functions like eig() for eigenvalue decomposition, toeplitz() for matrix reconstruction, and spatial spectrum calculation using steering vectors. Ultimately, DOA estimation with uniform linear arrays represents a critical signal processing technology where various algorithmic enhancements significantly improve estimation accuracy and resolution.