Abstract
WiFi Round Trip Time (RTT) unlocks meter level accuracies in user terminal positions where no other navigation systems, such as Global Navigation Satellite Systems (GNSS), are able to (e.g., indoors). However, little has been done so far to obtain a scalable and automated system that computes the position of the WiFi Access Points (WAP) using RTT and that is able to estimate, in addition to the position, the hardware biases that offset the WiFi ranging measurements. These biases have a direct impact on the ultimate position accuracy of the terminals. This work proposes a method in which the computation of the WiFi Access Points positions and hardware biases (i.e., products) can be estimated based on the ranges and position fixes provided by user terminals (i.e., inverse positioning) and details how this can be improved if raw GNSS measurements (pseudoranges and carrier phase) are also available in the terminal. The data setup used to obtain a performance assessment was configured in a benign scenario (open sky with no obstructions) in order to obtain an upper boundary on the positioning error that can be achieved with the proposed method. Under these conditions, accuracies better than 1.5 m were achieved for the WAP position and hardware bias. The proposed method is suitable to be implemented in an automated manner, without having to rely on dedicated campaigns to survey 802.11mc-compliant WAPs. This paper offers a technique to automatically estimate both mild-indoor WAP products (where terminals have both Wi-Fi RTT and GNSS coverage) and deep-indoor WAP (with no GNSS coverage where the terminals obtain their position exclusively from previously estimated mild-indoor WAPs).
Highlights
The WIFI 802.11mc protocol ([1]) allows a device to measure the distance to a WiFiAccess Point (WAP) in a bi-directional communication process
This is slightly different than other navigation systems, such as Global Navigation Satellite Systems (GNSS), where the receiver clock biases depend over time, and measurements over different epochs have to be processed in different batches
The environment was open sky without obstructions. This can be considered as a benign scenario and a measure of the best possible accuracy that can be obtained using WiFi Round Trip Time (RTT) measurements collected with a smartphone
Summary
The WIFI 802.11mc protocol ([1]) allows a device to measure the distance to a WiFi. Access Point (WAP) in a bi-directional communication process. Besides environmental error sources, such as multipath, RTT ranges are usually offset due to biases introduced by the WAP hardware ([13]) Despite this potential breakthrough, there is a clear limitation of the 802.11mc protocol due to its bi-directional nature, as opposed to other navigation systems, such as Global. WAP positions were usually obtained by survey campaigns using geodetic grade GNSS receivers (see, for instance, [16]) This solution is not practical for operational systems, and an automated methodology should be developed. Geotagging the RTT measurements with a more accurate user terminal position has, in turn, the potential to better locate the position of WAPs. In the following paper, we intend to provide a methodology to estimate the WAP position and hardware bias as well as to improve these estimates by means of exploiting the better accuracy offered by processing the raw GNSS measurements. The paper is concluded with the Discussion section, which contains our conclusions of the work
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
