Classic Capon Algorithm for DOA Estimation

Direction of Arrival (DOA) estimation is a key technology in array signal processing, used to determine the direction of incoming signals from sources. The classical Capon algorithm, also known as the Minimum Variance Distortionless Response (MVDR) algorithm, is a high-resolution DOA estimation method based on spatial spectrum estimation.

The core concept of the Capon algorithm involves constructing a filter that allows distortion-free passage of signals from specific directions while minimizing interference and noise from other directions. Its implementation comprises three critical steps: constructing the array covariance matrix (typically using sample covariance estimation from received data), computing the spatial spectrum function (through matrix inversion and steering vector operations), and identifying spectral peak positions (using peak detection algorithms).

Compared to traditional beamforming algorithms, the Capon algorithm provides superior spatial angular resolution, enabling discrimination between closely spaced signal sources. However, the algorithm has significant limitations: it is sensitive to source number estimation (overestimation causes severe performance degradation), exhibits reduced estimation performance with small snapshot numbers, and suffers substantial performance deterioration in coherent source scenarios.

To address these limitations, researchers have proposed various improvements including subspace decomposition-based enhancements, sparse reconstruction methods, and applications of new technologies like deep learning. These modified algorithms effectively enhance estimation performance and robustness in complex scenarios while preserving the advantages of the original Capon approach.