Rank Revealing QR Factorization for Jointly Time Delay and Frequency Estimation

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Executive Summary

The Rank-Revealing QR factorization (RRQR) is a valuable tool in numerical linear algebra because it provides accurate information about rank and numerical null-space. In this paper, the authors addressed the problem of estimating the time delay and the frequencies of noisy sinusoidal signals received at two spatially separated sensors using the well known RRQR, subspace decomposition technique. Although EigenValue Decomposition (EVD) of cross spectral matrix or Singular value decomposition SVD for the data matrix based techniques provide accurate estimation, they are hard to meet real time constraints due to computational load and cost.

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