# Round-Trip Time Ranging to Wi-Fi Access Points Beats GNSS Localization
## 11 Sample Outdoor Localization Results  
We experimented with the method in three locations (see Figure 3):  
* A small hotel with three main buildings (133 \(\times\) 72 m) and 17 APs supporting only one-sided RTT (video at [55]). * A condominium development (182 \(\times\) 108 m) with 29 active APs, supporting only one-sided RTT. * A hotel/condominium complex (210 \(\times\) 120 m) with 113 APs supporting two-sided RTT (videos at [56; 57]). Figure 3: Sample FTMRTT screen shots at the three locations: (i) with 17 APs; (ii) with 29 APs; (iii) with 113 APs. The red blob is the probability distribution of the UE position. The GNSS position is shown as a small dark blue dot. APs currently responding are shown in green (or cyan); APs not currently responding to range requests are shown in magenta (or red). In each of the above referenced screen recordings, the red blob is the probability distribution of where the app thinks the UE may be. APs currently responding are shown in green (or cyan), while APs not responding are shown in magenta (or red). APs not in the current selection, but whose frequency is known, are shown in a brownish yellow. When available, the GNSS location is shown as a dark blue dot. We focus here on the third, the most challenging case. The locations of the 113 APs were determined using the inverse BGU method described above in Section 6. In this particular location, additional prior information was available to constrain the results for the 108 (=\(36\times 3\)) APs in the three main buildings: the layout of rooms and the position of APs within the rooms was the same in each of the buildings. This made it possible to use a least-squares method to find that regular pattern using data from all three buildings. The positions of the APs could then be fine-tuned to fit this common pattern. The results could not be checked directly since the APs were not visible from outside, but comparing AP positions obtained using data on three different days indicated that the AP positions were accurate to within 1-2 m.  
For comparison, the Google geolocation API applied to the \"universally administered\" MAC addresses of these APs yielded results mostly within 3-5 m of the AP positions determined as above (albeit with a few large outliers). So, actually, one could just use the locations supplied by the geolocation API if a slightly larger error in the estimated location of the UE was acceptable. The known positions of the APs were then used in the FTMRTT app [34] to determine the position of the UE as it was carried around the property. In this installation APs use channels in both the 2.4 GHz and 5 GHz bands. The 5 GHz band potentially provides for higher ranging accuracy because it can support wider bandwidths (up to 80 MHz), but in this installation, channels in _both_ bands were restricted to 20 MHz bandwidth. BSSIDs operating in the 2.4 GHz band were chosen for ranging because, for the same transmitted power, lower frequencies provide a stronger signal [58], and so allow for ranging at larger distances (on the other hand, using both 2.4 GHz and 5 GHz channels on an AP can provide improved accuracy because of frequency diversity [19]). GNSS coordinates were recorded, as well as the times at which easy-to-identify landmarks on the path were passed (using the repurposed \"volume down\" key). The geographical coordinates of these were determined using Google Maps. In Figure 4, the ground truth is indicated in blue, the GNSS coordinates in red, and the results of the BGU method in green. Note that some parts of the path are traversed twice, and that there are two gaps in the recording apparently resulting from firmware freezes leading to 5 s watch-dog timer events. The locations of the five APs (top left) not in the three main buildings are not as well known because they are not part of a repeating pattern that could be used for fine-tuning. Figure 5 compares the errors in the estimated position of the UE based on RTT measurements and the smartphone's GNSS.