Multiresolution Time-of-arrival Estimation from Multiband Radio Channel Measurements
Tarik Kazaz (TU Delft - Signal Processing Systems)
Raj Thilak Rajan (TU Delft - Signal Processing Systems)
Gerard J.M. Janssen (TU Delft - Signal Processing Systems)
Alle Jan Van Der Veen (TU Delft - Signal Processing Systems)
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Abstract
Achieving high resolution time-of-arrival (TOA) estimation in multipath propagation scenarios from bandlimited observations of communication signals is challenging because the multipath channel impulse response (CIR) is not bandlimited. Modeling the CIR as a sparse sequence of Diracs, TOA estimation becomes a problem of parametric spectral inference from observed bandlimited signals. To increase resolution without arriving at unrealistic sampling rates, we consider multiband sampling approach, and propose a practical multibranch receiver for the acquisition. The resulting data model exhibits multiple shift invariance structures, and we propose a corresponding multiresolution TOA estimation algorithm based on the ESPRIT algorithm. The performance of the algorithm is compared against the derived Cramér Rao Lower Bound, using simulations with standardized ultra-wideband (UWB) channel models. We show that the proposed approach provides high resolution estimates while reducing spectral occupancy and sampling costs compared to traditional UWB approaches.