Crowd sourced RTT-based positioning
In various embodiments, crowd sourcing techniques are provided to enable RTT-based positioning of UE. To address issues of discovering which beacons (e.g., Wi-Fi APs, cellular base stations, BLE transmitters, etc.) support measurement of RTT (e.g., according to IEEE 802.11mc, 3GPP Release 16, etc.), beacon RTT capabilities may be crowd-sourced from UE and maintained by a cloud-based location platform in a beacon database (or more specifically, a RTT database portion thereof). To address the issue of determining physical antenna positions, RTT measurements may be crowd-sourced from UE for those beacons that are RTT capable, and used by a trilateration algorithm (e.g., a WLS multilateration algorithm) to determine physical antenna positions, which also may be maintained in the beacon database. Accuracy of the trilateration may be enhanced by obtaining raw GNSS measurements (e.g., psuedoranges) from the UE, and performing a cloud-based RTK GNSS position fix for the UE.
1. A method to enable round-trip time (RTT)-based positioning, comprising:
receiving, by a cloud-based location platform that maintains a beacon database, observations from a plurality of user equipment (UE) that have observed a beacon, the observations including at least a determined position of each of the plurality of UE, a RTT measurement for each of the plurality of UE by the beacon, a RTT measurement uncertainty, a signal strength associated with the RTT measurement, and a bandwidth associated with the RTT measurement;
using, by the cloud-based location platform, a trilateration algorithm to determine a physical antenna position of the beacon based on at least the determined position of each of the plurality of UE and the RTT measurement of each of the plurality of UE, wherein the determination by the trilateration algorithm is further based on the RTT measurement uncertainty, the signal strength, and the bandwidth for each of the plurality of UE;
updating the beacon database to include the determined physical antenna position of the beacon; and
providing, by the cloud-based location platform, the physical antenna position of the beacon to one or more UE of the plurality of UE,
such that the one or more UE contribute information used to determine the physical antenna position of the beacon to build the beacon database and consume the physical antenna position of the beacon from the beacon database.
2. The method of claim 1 , wherein the beacon is a Wi-Fi access point (AP) and each of the plurality of UE support fine timing measurement (FTM) protocol according to an Institute of Electrical and Electronics Engineers (IEEE) 802.11mc standard.
3. The method of claim 1 , wherein the beacon is a cellular base station, each of the plurality of UE support 3rd Generation Partnership Project (3GPP) Release 16, and the RTT-based positioning is multi-RTT-based positioning.
4. The method of claim 1 , wherein the determined position of each of the plurality of UE includes a position confidence of the determined position, and the method further comprises:
filtering out observations based on a comparison of the position confidence of the determined position of each of the plurality of UE with a threshold.
5. The method of claim 4 , wherein the determination by the trilateration algorithm is further based on the position confidence of a determined position.
6. The method of claim 1 , wherein the trilateration algorithm is a weighted least square (WLS) multilateration algorithm.
7. The method of claim 1 , wherein information describing the determined position of each of the plurality of UE includes raw global navigation satellite system (GNSS) measurements for the UE and the method further comprises:
obtaining, by the cloud-based location platform from a Real Time Kinematic (RTK) correction service RTK correction information for the raw GNSS measurements of each of the plurality of UE; and
determining, by the cloud-based location platform, a corrected GNSS position fix for each of the plurality of UE using the raw GNSS measurements and the RTK correction information,
wherein the information describing the determined position and the RTT measurement used by the trilateration algorithm includes the corrected GNSS position fix for each of the plurality of UE.
8. The method of claim 7 , further comprising:
determining a horizontal positioning error (HPE) of the corrected GNSS position fix for the plurality of UE, and
wherein the determination by the trilateration algorithm is further based on HPE of the corrected GNSS position fix for the plurality of UE.
9. A cloud-based location platform, comprising:
at least one memory;
at least one transceiver; and
at least one processor communicatively coupled to the at least one memory and the at least one transceiver, the at least one processor configured to:
receive, via the at least one transceiver, observations from a plurality of user equipment (UE) that have observed a beacon, the observations including at least a determined position of each of the plurality of UE, a RTT measurement for each of the plurality of UE by the beacon, a RTT measurement uncertainty, a signal strength associated with the RTT measurement, and a bandwidth associated with the RTT measurement;
use a trilateration algorithm to determine a physical antenna position of the beacon based on at least the determined position of each of the plurality of UE and the RTT measurement of each of the plurality of UE, wherein the determination by the trilateration algorithm is further based on the RTT measurement uncertainty, the signal strength, and the bandwidth for each of the plurality of UE;
update a beacon database maintained by the cloud-based location platform to include the determined physical antenna position of the beacon; and
provide the physical antenna position of the beacon to one or more UE of the plurality of UE,
such that the one or more UE contribute information used to determine the physical antenna position of the beacon to build the beacon database and consume the physical antenna position of the beacon from the beacon database.
10. The cloud-based location platform of claim 9 , wherein the beacon is a Wi-Fi access point (AP) and each of the plurality of UE support fine timing measurement (FTM) protocol according to an Institute of Electrical and Electronics Engineers (IEEE) 802.11mc standard.
11. The cloud-based location platform of claim 9 , wherein the beacon is a cellular base station, each of the plurality of UE support 3rd Generation Partnership Project (3GPP) Release 16, and the RTT-based positioning is multi-RTT-based positioning.
12. The cloud-based location platform of claim 9 , wherein the determined position of each of the plurality of UE includes a position confidence of the determined position, and the at least one processor is further configured to:
filter out observations based on a comparison of the position confidence of the determined position of each of the plurality of UE with a threshold.
13. The cloud-based location platform of claim 12 , wherein the determination by the trilateration algorithm is further based on the position confidence of a determined position.
14. The cloud-based location platform of claim 9 , wherein the trilateration algorithm is a weighted least square (WLS) multilateration algorithm.
15. The cloud-based location platform from a Real Time Kinematic (RTK) correction service RTK correction information for the raw GNSS measurements of each of the plurality of UE; of claim 9 , wherein information describing the determined position of each of the plurality of UE includes raw global navigation satellite system (GNSS) measurements for the UE and the at least one processor is further configured to:
obtain, from a Real Time Kinematic (RTK) correction service RTK correction information for the raw GNSS measurements of each of the plurality of UE; and
determine a corrected GNSS position fix for each of the plurality of UE using the raw GNSS measurements and the RTK correction information,
wherein the information describing the determined position and the RTT measurement used by the trilateration algorithm includes the corrected GNSS position fix for each of the plurality of UE.
16. The cloud-based location platform from a Real Time Kinematic (RTK) correction service RTK correction information for the raw GNSS measurements of each of the plurality of UE; of claim 15 , wherein the at least one processor is further configured to:
determine a horizontal positioning error (HPE) of the corrected GNSS position fix for the plurality of UE, and
wherein the determination by the trilateration algorithm is further based on the HPE of the corrected GNSS position fix for the plurality of UE.