An efficient approach for the harmonic retrieval problem via Haar wavelet transform

Modern subspace-based algorithms can offer high-resolution spectral estimates but with a cost of high computational complexity for the eigenvalue decomposition (EVD) involved. We propose a novel preprocessing scheme that can be used in conjunction with the subspace-based algorithms to alleviate the high amount of computations previously required. The main crux of the new scheme lies in a subband decomposition of the input data via the computationally efficient discrete-time Haar wavelet transform (HWT). Some simulation results are provided to justify the proposed approach.