Three DOA Estimation Algorithms: Beamforming, Capon, and MUSIC with MATLAB Implementation

In this documentation, I will provide MATLAB simulation source codes for three common Direction of Arrival (DOA) estimation algorithms: Beamforming, Capon, and MUSIC. The implementation includes generating 2D plots to visualize the correspondence between frequency and DOA, helping you better understand the working principles of these algorithms. The Beamforming algorithm implementation utilizes conventional delay-and-sum techniques with steering vector computation for spatial filtering. The Capon algorithm (Minimum Variance Distortionless Response) employs covariance matrix estimation and inversion to achieve superior resolution. The MUSIC (Multiple Signal Classification) algorithm implements eigenvalue decomposition of the covariance matrix and exploits the orthogonality between signal and noise subspaces for high-resolution DOA estimation. Key MATLAB functions used include: - Phased array toolbox functions for array geometry configuration - Covariance matrix estimation using xcorr or built-in matrix operations - Eigenvalue decomposition (eig function) for subspace separation - Peak detection algorithms for DOA estimation from spatial spectra - 2D plotting functions (mesh, contour) for frequency-DOA relationship visualization The code structure includes signal generation模块, array processing模块, algorithm implementation modules, and result visualization modules. Each algorithm is implemented with proper parameter configuration for fair comparison and performance analysis.