WiFi-Based Indoor Localization via Multi-Band Splicing and Phase\n Retrieval

Abstract

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