High-Precision Time Delay Estimation Between Two Signals Using MUSIC Algorithm

Conventional time delay estimation methods generally utilize signal correlation analysis to determine delays. However, to achieve superior accuracy, the MUSIC (Multiple Signal Classification) algorithm can be employed for estimating time delays between two signals. This method significantly improves measurement precision through sophisticated spectral estimation techniques and has found widespread application in practical scenarios. The implementation typically involves constructing a signal covariance matrix, performing eigenvalue decomposition to separate signal and noise subspaces, and identifying time delays by locating peaks in the MUSIC pseudospectrum. Furthermore, measurement accuracy can be further enhanced by integrating this algorithm with complementary technologies, such as applying machine learning algorithms to analyze and identify distinctive signal characteristics. Consequently, the MUSIC algorithm represents a highly promising research direction that warrants further exploration and investigation, particularly through Python implementations using libraries like NumPy for matrix operations or MATLAB with its built-in signal processing toolkit.