Explore MATLAB source code curated for "music算法" with clean implementations, documentation, and examples.
Adaptive array signal processing code implementations by Zhang Xiaofei (Nanjing University of Aeronautics and Astronautics), including MUSIC algorithm, ESPRIT algorithm, ROOT-MUSIC algorithm, and other essential techniques for modern signal processing applications.
A 16-element uniform linear array with half-wavelength spacing employs uniformly weighted conventional beamforming. Five uncorrelated far-field target sources transmit signals from azimuth angles -40°, -42°, -5°, 30°, and 33° relative to the array, each with equal 10dB signal-to-noise ratio at reception. Comparative analysis is performed between beamspace and element-space MUSIC algorithms for direction of arrival estimation.
Implementation of frequency estimation for three sinusoidal signals with additive white Gaussian noise using Pisarenko harmonic estimation, MUSIC algorithm, and ESPRIT algorithm. The attached code provides MATLAB implementations with detailed explanations of key functions and algorithm parameters.
Source codes for MUSIC algorithms in array signal processing: classical MUSIC algorithm, Root-MUSIC algorithm, beamspace MUSIC algorithm, decorrelation-based MUSIC algorithm, and fourth-order cumulant-based MUSIC algorithm with implementation details.
MUSIC algorithm for spatial spectrum estimation and DOA (Direction of Arrival) analysis: A power spectrum estimation method based on matrix eigenvalue decomposition comprising two non-parametric estimation approaches - eigenvector estimation and MUSIC estimation. Eigenvector estimation is primarily suitable for power spectrum estimation of sinusoidal signals contaminated with white noise, while MUSIC estimation is more appropriate for general sinusoidal signal parameter estimation. The algorithm implementation involves covariance matrix computation, eigenvalue decomposition, and noise subspace identification for high-resolution spectral estimation.
Comprehensive MATLAB implementation of Direction of Arrival (DOA) estimation, including detailed explanations and code examples for MUSIC algorithm, RootMUSIC algorithm, ESPRIT algorithm, and MVDR algorithm with performance comparisons.
The root MUSIC method is implemented for angle of arrival prediction in indoor environments, utilizing signal harmonic analysis for enhanced spatial spectrum estimation.
Simulation of the classical radar angle-of-arrival estimation algorithm, MUSIC algorithm, which offers high-resolution target detection capabilities through eigen-decomposition of signal covariance matrices.
MATLAB implementation of the forward smoothing MUSIC algorithm demonstrates robust resolution capability under low signal-to-noise ratio conditions through simulation results, utilizing key signal processing functions for covariance matrix estimation and spectral peak detection.
Traditional MUSIC algorithm implementation for narrowband incoherent signal direction of arrival estimation using a 6-element uniform linear array with additive white Gaussian noise