Explore MATLAB source code curated for "波达方向估计" with clean implementations, documentation, and examples.
Source code implementation of the fourth-order cumulants-based MUSIC algorithm, an enhanced version of standard MUSIC algorithm for Direction of Arrival (DOA) estimation with improved noise robustness and accuracy
This MATLAB program implements Direction of Arrival (DOA) estimation using compressive sensing techniques
Direction of Arrival (DOA) estimation addresses the fundamental problem of determining spatial positions (azimuth angles relative to array reference elements) of multiple signals within a specified spatial region. The classical super-resolution DOA estimation method is the renowned MUSIC algorithm. This technical report presents implementation steps for an improved MUSIC approach, including signal covariance matrix computation, eigenvalue decomposition techniques, and spatial spectrum peak detection algorithms.
Implementation of direction of arrival estimation through compressive sensing, utilizing singular value decomposition for received signal dimensionality reduction and L1-norm minimization for sparse signal recovery
Implementation of Direction of Arrival estimation using MUSIC algorithm; The compressed package includes high-quality reference documents and MATLAB/Python code with detailed implementation examples.
Implementation of ESPRIT Algorithm for Direction of Arrival Estimation with Rotation Invariant Subspace Technique
Direction of Arrival Estimation for Multi-Element Circular Antenna Arrays in Smart Antenna Systems, including algorithmic implementation approaches and signal processing techniques
MUSIC algorithm implementation for Direction of Arrival (DOA) estimation demonstrating excellent performance, featuring comprehensive comparison with root-MUSIC algorithm and detailed code implementation insights including eigenvalue decomposition, spatial spectrum calculation, and peak detection techniques.
Capon algorithm implementation with code explanations, primarily used for Direction of Arrival (DOA) estimation and beamforming analysis simulations
This study analyzes the Incoherent Signal Subspace Method (ISM) for wideband source DOA estimation and applies a modified MUSIC algorithm with data matrix conjugate reconstruction to enhance resolution and enable coherent source detection. The Coherent Signal Subspace Method (CSM) is discussed with analysis of focusing matrices and frequency selection impacts, including criteria for optimal focusing matrix and frequency selection. For colored noise environments, a novel DOA estimation approach integrating propagator operator concepts with TCT focusing matrices is developed, enabling efficient noise covariance estimation directly from array signals without complex eigenvalue decomposition.