Single Electromagnetic Vector Sensor Noise Subspace Fitting Algorithm - Spatial Spectrum Diagram
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In this document, we conduct computer simulations of the noise subspace algorithm based on electromagnetic vector sensor arrays and compare the results with the classical reduced-rank MUSIC algorithm. To better demonstrate the differences between these two algorithms, we plot their spatial spectrum diagrams and contrast their performance across various environments. The implementation involves array signal processing techniques where we construct covariance matrices from simulated electromagnetic vector sensor data, perform eigenvalue decomposition to identify noise subspaces, and apply spectral estimation functions. This comparative analysis helps develop a comprehensive understanding of the advantages and limitations of both algorithms, along with their practical applicability in real-world scenarios.
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