Position estimation based on environmental, non-uniform priors

1 . A method of positioning performed by a positioning entity, comprising:

obtaining a set of error distributions associated with a set of locations associated with an environment, wherein each error distribution of the set of error distributions indicates an expected error distribution of positioning measurements associated with a corresponding location of the set of locations;

obtaining one or more positioning measurements obtained by a user equipment (UE) located within the environment; and

determining a location estimate of the UE within the environment based on a comparison of uncertainty values associated with the one or more positioning measurements to the set of error distributions.

2 . The method of claim 1 , further comprising:

discarding positioning measurements of the one or more positioning measurements that are inconsistent with an error distribution of the set of error distributions associated with the location estimate of the UE.

3 . The method of claim 2 , wherein the positioning measurements of the one or more positioning measurements being inconsistent with the error distribution of the set of error distributions comprises the positioning measurements of the one or more positioning measurements being less likely than a threshold to have been obtained at the location estimate of the UE based on a comparison of uncertainty values associated with the positioning measurements to the error distribution.

4 . The method of claim 1 , wherein determining the location estimate of the UE comprises:

weighting the one or more positioning measurements based on a comparison of the one or more positioning measurements to an error distribution of the set of error distributions.

5 . The method of claim 4 , wherein the error distribution of the set of error distributions is selected based on:

a coarse location estimate of the UE,

a previous location estimate of the UE,

a trajectory of the UE, or

any combination thereof.

6 . The method of claim 4 , wherein:

higher weights are assigned to positioning measurements of the one or more positioning measurements that are more consistent with the error distribution, and

lower weights are assigned to positioning measurements of the one or more positioning measurements that are less consistent with the error distribution.

7 . The method of claim 4 , wherein the location estimate of the UE is determined based on positioning measurements of the one or more positioning measurements having a weight above a threshold.

8 . The method of claim 1 , wherein the location estimate of the UE within the environment is based on a two-dimensional or three-dimensional point cloud representing a plurality of estimated positions of the UE within the environment.

9 . The method of claim 8 , further comprising:

pruning points from the point cloud that are based on positioning measurements of the one or more positioning measurements that are inconsistent with error distributions of the set of error distributions associated with the points.

10 . The method of claim 1 , wherein the set of error distributions is obtained based on:

a survey of the environment,

a map of the environment,

crowdsourced positioning measurements of the environment, or

any combination thereof.

11 . The method of claim 1 , wherein the one or more positioning measurements comprise:

one or more timing measurements,

one or more angle-based measurements,

one or more signal strength measurements, or

any combination thereof.

12 . The method of claim 1 , wherein the one or more positioning measurements comprise measurements of one or more reference signals transmitted by one or more access points within the environment.

13 . The method of claim 1 , wherein the positioning entity comprises:

a location server,

an over-the-top (OTT) server, or

a positioning engine executing on the UE.

14 . The method of claim 1 , wherein the environment is an indoor environment.

15 . A positioning entity, comprising:

one or more memories;

one or more transceivers; and

one or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to:

obtain a set of error distributions associated with a set of locations associated with an environment, wherein each error distribution of the set of error distributions indicates an expected error distribution of positioning measurements associated with a corresponding location of the set of locations;

obtain one or more positioning measurements obtained by a user equipment (UE) located within the environment; and

determine a location estimate of the UE within the environment based on a comparison of uncertainty values associated with the one or more positioning measurements to the set of error distributions.

16 . The positioning entity of claim 15 , wherein the one or more processors are further configured to:

discard positioning measurements of the one or more positioning measurements that are inconsistent with an error distribution of the set of error distributions associated with the location estimate of the UE.

17 . The positioning entity of claim 16 , wherein the positioning measurements of the one or more positioning measurements being inconsistent with the error distribution of the set of error distributions comprises the positioning measurements of the one or more positioning measurements being less likely than a threshold to have been obtained at the location estimate of the UE based on a comparison of uncertainty values associated with the positioning measurements to the error distribution.

18 . The positioning entity of claim 15 , wherein the one or more processors configured to determine the location estimate of the UE comprises the one or more processors, either alone or in combination, configured to:

weight the one or more positioning measurements based on a comparison of the one or more positioning measurements to an error distribution of the set of error distributions.

19 . The positioning entity of claim 18 , wherein the error distribution of the set of error distributions is selected based on:

a coarse location estimate of the UE,

a previous location estimate of the UE,

a trajectory of the UE, or

any combination thereof.

20 . The positioning entity of claim 18 , wherein:

higher weights are assigned to positioning measurements of the one or more positioning measurements that are more consistent with the error distribution, and

lower weights are assigned to positioning measurements of the one or more positioning measurements that are less consistent with the error distribution.

21 . The positioning entity of claim 18 , wherein the location estimate of the UE is determined based on positioning measurements of the one or more positioning measurements having a weight above a threshold.

22 . The positioning entity of claim 15 , wherein the location estimate of the UE within the environment is based on a two-dimensional or three-dimensional point cloud representing a plurality of estimated positions of the UE within the environment.

23 . The positioning entity of claim 22 , wherein the one or more processors are further configured to:

prune points from the point cloud that are based on positioning measurements of the one or more positioning measurements that are inconsistent with error distributions of the set of error distributions associated with the points.

24 . The positioning entity of claim 15 , wherein the set of error distributions is obtained based on:

a survey of the environment,

a map of the environment,

crowdsourced positioning measurements of the environment, or

any combination thereof.

25 . The positioning entity of claim 15 , wherein the one or more positioning measurements comprise:

one or more timing measurements,

one or more angle-based measurements,

one or more signal strength measurements, or

any combination thereof.

26 . The positioning entity of claim 15 , wherein the one or more positioning measurements comprise measurements of one or more reference signals transmitted by one or more access points within the environment.

27 . The positioning entity of claim 15 , wherein the positioning entity comprises:

a location server,

an over-the-top (OTT) server, or

a positioning engine executing on the UE.

28 . The positioning entity of claim 15 , wherein the environment is an indoor environment.

29 . A positioning entity, comprising:

means for obtaining a set of error distributions associated with a set of locations associated with an environment, wherein each error distribution of the set of error distributions indicates an expected error distribution of positioning measurements associated with a corresponding location of the set of locations;

means for obtaining one or more positioning measurements obtained by a user equipment (UE) located within the environment; and

means for determining a location estimate of the UE within the environment based on a comparison of uncertainty values associated with the one or more positioning measurements to the set of error distributions.

30 . A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a positioning entity, cause the positioning entity to:

obtain a set of error distributions associated with a set of locations associated with an environment, wherein each error distribution of the set of error distributions indicates an expected error distribution of positioning measurements associated with a corresponding location of the set of locations;

obtain one or more positioning measurements obtained by a user equipment (UE) located within the environment; and

determine a location estimate of the UE within the environment based on a comparison of uncertainty values associated with the one or more positioning measurements to the set of error distributions.