CRISLoc is the first CSI fingerprinting based localization prototype system using ubiquitous smartphones.
To the best of our knowledge, CRISLoc is the first CSI fingerprinting localization system using off-the-shelf smartphones.
Extensive experiments show that CRISLoc achieves a mean error of 0.29m in a research laboratory (6m×8m), and a median error of 0.78m in a complex academic building (8m×28m) consisting of a research room, a long orridor and a small square.
CSI is extracted from Nexus 5 by Nexmon, whose amplitudes are more stable over time.
We design a suit of methods to sanitize CSI data, encompassing the cancellation of automatic gain control and the filtering of unstable subcarriers and frames.
We design a joint clustering and outlier detection approach to find the altered APs. The core idea of this approach is to perform localization by different subsets of APs.
We develop a novel transfer learning approach to reconstruct their CSI & RSSI fingerprints.
Our data is now available on Google Drive, please refer to the link below:
https://drive.google.com/file/d/1FHW14t2U2CK9j2P9AwsrD2Q5U4mgv2SC/view?usp=sharing
To reference CRISLoc:
Zhihui Gao*, Yunfan Gao*, Sulei Wang, Dan Li, Yuedong Xu, “CRISLoc: Reconstructable CSI Fingerprinting for Indoor Smartphone Localization”, submitted to IEEE Internet of Things Journal.