TOA Estimation Based on Multi-Band CSI Exploiting the Structure of the Correlation Matrix

In the future generation of mobile communication systems, many scenarios will require high-resolution range-based positioning. However, the accuracy of time-of-arrival (TOA) estimation algorithms for single wideband systems is generally limited due to the constraints of available bandwidth. Currently, leveraging multiple available frequency bands and carrier frequency switching to obtain multi-band channel state information (CSI) for TOA estimation is gaining popularity, as it effectively constructs an equivalent wideband signal. In this paper, we proposed a subspace-based TOA estimation algorithm using multi-band CSI by constructing a correlation matrix and then exploiting its mathematical properties. The proposed algorithm eliminates the need for grid search and thus has lower computational complexity. We analyze the Cramér-Rao Bound (CRB) for the multi-band data model and derive a tighter lower bound for our algorithm. Simulation results show that our algorithm converges to the CRB at high SNR and closely follows the proposed lower bound across all SNR levels. Additionally, our algorithm demonstrates superior performance compared to single-band algorithms and offers advantages in either accuracy or complexity when compared to other multi-band algorithms.