  We study the problem of indoor localization using commodity WiFi channel
state information (CSI) measurements. The accuracy of methods developed to
address this problem is limited by the overall bandwidth used by the WiFi
device as well as various types of signal distortions imposed by the underlying
hardware. In this paper, we propose a localization method that performs channel
impulse response (CIR) estimation by splicing measured CSI over multiple WiFi
bands. In order to overcome hardware-induced phase distortions, we propose a
phase retrieval (PR) scheme that only uses CSI magnitude values to estimate the
CIR. To achieve high localization accuracy, the PR scheme involves a sparse
recovery step, which exploits the fact that the CIR is sparse over the delay
domain, due to the small number of contributing signal paths in an indoor
environment. Simulation results indicate that our approach outperforms the
state of the art by an order of magnitude (cm-level localization accuracy) for
more than 90% of the trials and for various SNR regimes.
