Enhanced MUSIC Algorithm for DOA Estimation in Smart Antenna System Subspace Methods

In smart antenna systems, DOA estimation serves as a critical task. The enhanced MUSIC algorithm within subspace methods represents a high-performance solution widely adopted for DOA estimation. By leveraging higher-order statistical information, this algorithm accurately estimates angular information of multipath propagation signals. Consequently, it outperforms traditional algorithms and demonstrates better adaptability to complex wireless signal environments. The implementation typically involves constructing a covariance matrix from received signals, performing eigenvalue decomposition to separate signal and noise subspaces, and utilizing the MUSIC pseudospectrum to identify DOA peaks. Key functions include signal preprocessing, covariance matrix computation, and spectral peak search algorithms. Compared to alternative approaches, this enhanced algorithm achieves higher precision with reduced computational complexity, making it practically advantageous for real-world applications where it has gained significant attention. The algorithm's efficiency stems from its optimized matrix operations and reduced requirement for exhaustive spectral scans.