Two-Dimensional Signal Angle of Arrival and Parameter Estimation Using Matrix Pencil Method

In the process of estimating two-dimensional signal angle of arrival and system parameters, we can employ the Matrix Pencil Method to enhance precision and accuracy. The Matrix Pencil Method serves as an efficient algorithm that improves estimation results through multiple signal measurements and computational operations. This approach typically involves constructing a Hankel matrix from sampled data and performing singular value decomposition (SVD) to extract signal subspaces. Key implementation steps include: forming data matrices from sensor array outputs, applying eigenvalue decomposition to matrix pencils for parameter extraction, and utilizing total least squares optimization for noise robustness. Through the Matrix Pencil Method implementation, we gain better understanding of signal arrival angles and system parameters, providing valuable data insights and practical advantages for research applications. The algorithm's core functionality can be implemented using mathematical libraries like NumPy or MATLAB with functions such as svd() for matrix decomposition and eig() for eigenvalue computation.