LocAP: Autonomous Millimeter Accurate Mapping of WiFi Infrastructure


Roshan Ayyalasomayajula, Aditya Arun, Chenfeng Wu, Shrivatsan Rajagopalan, Shreya Ganesaraman, Aravind Seetharaman, Ish Kumar Jain, and Dinesh Bharadia, University of California, San Diego


Indoor localization has been studied for nearly two decades fueled by wide interest in indoor navigation, achieving the necessary decimeter-level accuracy. However, there are no real-world deployments of WiFi-based user localization algorithms, primarily because these algorithms are infrastructure dependent and therefore assume the location of the Access Points, their antenna geometries, and deployment orientations in the physical map. In the real world, such detailed knowledge of the location attributes of the access point is seldom available, thereby making WiFi localization hard to deploy. In this paper, for the first time, we establish the accuracy requirements for the location attributes of access points to achieve decimeter level user localization accuracy. Surprisingly, these requirements for antenna geometries and deployment orientation are very stringent, requiring millimeter level and sub-10 of accuracy respectively, which is hard to achieve with manual effort. To ease the deployment of real-world WiFi localization, we present LocAP, which is an autonomous system to physically map the environment and accurately locate the attributes of existing wireless infrastructure in the physical space down to the required stringent accuracy of 3 mm antenna separation and 3o deployment orientation median errors, whereas state-of-the-art algorithm reports 150 mm and 25o respectively.

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@inproceedings {246340,
author = {Roshan Ayyalasomayajula and Aditya Arun and Chenfeng Wu and Shrivatsan Rajagopalan and Shreya Ganesaraman and Aravind Seetharaman and Ish Kumar Jain and Dinesh Bharadia},
title = {{LocAP}: Autonomous Millimeter Accurate Mapping of {WiFi} Infrastructure },
booktitle = {17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20)},
year = {2020},
isbn = {978-1-939133-13-7},
address = {Santa Clara, CA},
pages = {1115--1129},
url = {https://www.usenix.org/conference/nsdi20/presentation/ayyalasomayajula},
publisher = {USENIX Association},
month = feb,

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