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Superresolution Wireless Multipath Channel Path Delay Estimation for CIR-Based Localization

The channel impulse response (CIR)-based localization requires estimating the channel path delays at a certain position. Several state-of-the-art (SoA) approaches have been proposed to estimate the delays based on eigendecomposition. However, they are limited by the assumption of uncorrelated paths, which is not accurate in the context of localization. The attempt to mitigate the rank deficits problem by means of frequency smoothing (FS) requires a considerable amount of measurements on different center frequencies. Another solution with single snapshot multiple signal classification (MUSIC) lacks the accuracy in resolving fractional path delays and requires high computational complexity. In this paper, we propose a new approach to construct the eigendecomposition model by means of a simple arrangement of the frequency-domain estimated channel gains. Our method has lower computational complexity and is able to outperform the SoA techniques in terms of estimation accuracy and resolution. The performance is evaluated with numerical simulations and supported by measurements using realistic radio frequency (RF) hardware.