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A novel time delay estimation using chirp signals robust to sampling frequency offset for a ranging system

We propose a novel time delay estimation algorithm using a training and data sequence composed of chirp signals for a ranging system with frequency offset. This training and data sequence can be used for SNR enhancement using the proposed denoising method. Then, a subspace-based algorithm, ESPRIT, is applied to estimate the time delay of the first arrival path. We analyze the estimation performance of ESPRIT based on the proposed denoising method and verify it through Monte-carlo simulations in AWGN and a multi-path channel.