SYSTEMS AND METHODS FOR CALIBRATION OF INDOOR GEOLOCATION

• US 20130162481A1
• Filed: 12/05/2012
• Published: 06/27/2013
• Est. Priority Date: 10/01/2009
• Status: Abandoned Application

• Current Assignee: Lighthouse Signal Systems, LLC
• Original Assignee: Mohammad Heidari
• Inventors: Parvizi, Parviz, Heidari, Mohammad
• Application Number:
  US13/705,914
• Publication Number:
  US 20130162481A1
• Time in Patent Office: Days
• US Class Current: 342/452
• CPC Class Codes: G01S 5/0244 Accuracy or reliability of position solution or of measurements contributing thereto
• CPC Class Codes: G01S 5/02524 Creating or updating the radio-map

Abstract

In a system facilitating the calibration of a map-point grid for an indoor location, the grid includes several map points, each having a radio frequency (RF) data fingerprint associated therewith. RF data are received from a device associated with a user, and a map point is identified or determined based on, at least in part, the received RF data. A reliability of a fingerprint to be associated with the map point is computed based on, at least in part, a comparison of a parameter associated with the map point with reference data associated with the indoor location such as topology of the location, and speed and orientation of the user. A fingerprint is associated with the first map point based on, at least in part, the first RF data and the computed reliability. The computation of the reliability may also be based on additional RF data and location determination based thereon and/or user feedback. An existing fingerprint may be adjusted based on the received RF data.

Claims

1. A method of calibrating a map-point grid for an indoor location, the grid comprising a plurality of map points, each having a radio frequency (RF) data fingerprint being associated therewith, the method comprising:

receiving first RF data from a device associated with a user;

identifying a first map point, or determining the first map point based on, at least in part, the first RF data;

computing a reliability of a fingerprint to be associated with the first map point based on, at least in part, a comparison of a parameter associated with the first map point with reference data associated with the indoor location; and

associating a fingerprint with the first map point based on, at least in part, the first RF data and the computed reliability.

2. The method of claim 1, wherein the parameter associated with the first map point comprises a user identified orientation and the reference data comprises sensor-based orientation.

3. The method of claim 1 further comprising:

receiving second RF data from the device associated with the user; and

identifying a second map point, or determining the second map point based on, at least in part, the second RF data.

4. The method of claim 3, wherein the parameter associated with the first map point comprises an estimated speed of user movement from the first map point to the second map point based on a time elapsed between receiving the identifications of the first and second map points and a distance between the first and second map points, and the reference data comprises a nominal movement speed.

5. The method of claim 3, wherein the parameter associated with the first map point comprises an estimated path from the first map point to the second map point, the estimated path comprising a set of estimated segments, each estimated segment having a distance and an orientation, at least one of the distance and the orientation being determined according to tracking data obtained from an inertial navigation system.

6. The method of claim 5, wherein the reference data comprises an actual path from the first map point to the second map point, the actual path comprising actual segments, each actual segment having a distance and an orientation;

and

the computed reliability is set to a preset low value if the distance or orientation of at least one estimated segment is substantially different than the distance or orientation of the corresponding actual segment.

7. The method of claim 5, wherein the reference data comprises a topology of an indoor location;

and

the computed reliability is set to a preset low value if movement along the estimated path is determined to violate a characteristic of the indoor location topology.

8. The method of claim 7, wherein the characteristic of the indoor location topology comprises one of a location of an obstacle, a lack of a floor, an exit, or an unauthorized location within the topology.

9. A method of calibrating a map-point grid for an indoor location, the grid comprising a plurality of map points, each having a radio frequency (RF) data fingerprint being associated therewith, the method comprising:

receiving from a device associated with a user RF data corresponding to a plurality of map points;

identifying the plurality of map points based on, at least in part, the RF data;

computing a statistical property of a parameter associated with each of at least a subset of the map points;

computing a reliability of a fingerprint to be associated with a candidate map point based, at least in part, on a comparison of the parameter associated with the candidate map point to the statistical property; and

associating a fingerprint with the candidate map point based on, in part, the RF data associated with the candidate map point and the computed reliability.

10. The method of claim 9, wherein the parameter associated with a map point comprises estimated speed of moving to the map point from another map point.

11. The method of claim 9, wherein the parameter associated with a map point comprises a difference between a user identified orientation and a sensor-based orientation, both corresponding to the map point.

12. The method of claim 9, wherein the parameter associated with a map point comprises a difference between an estimated path to the map point from another map point and an actual path to the map point from the other map point.

13. The method of claim 12, wherein the estimated path is determined based on sensor data.

14. A method of calibrating a map-point grid for an indoor location, the grid comprising a plurality of map points, each having a radio frequency (RF) data fingerprint being associated therewith, the method comprising:

receiving first and second RF data from a device associated with a user;

identifying a map point or determining the map point based on, at least in part, the first RF data;

obtaining a location based on the second RF data;

computing a reliability of a fingerprint to be associated with the map point based on, in part, a comparison of a location associated with the map point with the obtained location; and

associating a fingerprint with the map point based on, in part, the first RF data and the computed reliability.

15. The method of claim 14, wherein the second RF data comprises at least one of global positioning system (GPS) data and cellular phone signals.

16. A method of calibrating a map-point grid for an indoor location, the grid comprising a plurality of map points, each having a radio frequency (RF) data fingerprint being associated therewith, the method comprising:

receiving RF data from a device associated with a user;

selecting a map point based on, at least in part, the received RF data;

determining a location of the user based on, at least in part, the selected map point and the received RF data; and

receiving an accuracy indication about the determined location.

17. The method of claim 16 further comprising selectively adjusting a fingerprint associated with the selected map point based on, at least in part, the received RF data and the accuracy indication.

18. The method of claim 17, wherein:

the accuracy indication comprises a correction to the determined location; and

the selective adjustment is triggered upon receiving the correction.

19. The method of claim 17, wherein the adjustment to the fingerprint comprises changing a weight associated with the fingerprint based on, at least in part, the accuracy indication.

20. The method of claim 17, wherein:

the fingerprint comprises RF data associated with a set of RF transmitters; and

the adjustment to the fingerprint comprises removing RF data associated with an RF transmitter in the set, the removed RF data being identified from the received RF data.

21. The method of claim 17, wherein:

the fingerprint comprises RF data associated with at least one RF transmitter; and

the adjustment to the fingerprint comprises adding RF data associated with a new RF transmitter, the added RF data being obtained from the received RF data.

22. The method of claim 16 further comprising:

adding a new map point associated with the selected map point; and

assigning a new fingerprint to the new map point, the new fingerprint being based on, at least in part, the received RF data and the accuracy indication.

23. The method of claim 21 further comprising identifying a lack of substantial movement by a user for a preset duration, wherein the new map point is added if the lack of substantial movement is identified for the preset duration.

24. A system for calibrating a map-point grid for an indoor location, the grid comprising a plurality of map points, each having a radio frequency (RF) data fingerprint being associated therewith, the system comprising:

a memory for storing the grid;

a receiver for receiving first RF data from a device associated with a user; and

a processor for;

(i) identifying a first map point or determining the first map point based on, at least in part, the first RF data, (ii) computing a reliability of a fingerprint to be associated with the first map point based on, in part, a comparison of a parameter associated with the first map point with reference data, and (iii) associating a fingerprint with the first map point based on, in part, the first RF data and the computed reliability.

25. A system for calibrating a map-point grid for an indoor location, the grid comprising a plurality of map points, each having a radio frequency (RF) data fingerprint being associated therewith, the system comprising:

a memory for storing the grid;

a receiver for receiving first and second RF data from a device associated with a user;

a processor for;

(i) identifying a map point or determining the map point based on, at least in part, the first RF data, (ii) computing a location based on the second RF data, (iii) computing a reliability of a fingerprint to be associated with the map point based on, in part, a comparison of a location associated with the map point with the computed location, and (iv) updating in the memory a fingerprint associated with the map point based on, in part, the first RF data and the computed reliability.

26. A system for calibrating a map-point grid for an indoor location, the grid comprising a plurality of map points, each having a radio frequency (RF) data fingerprint being associated therewith, the system comprising:

a memory for storing the grid;

a receiver for receiving;

(i) RF data from a device associated with a user, and (ii) an accuracy indication;

a processor for;

(i) selecting a map point based on, at least in part, the received RF data, and (ii) determining a location of the user based on, at least in part, the selected map point and the received RF data.

27. The system of claim 26, wherein the processor is further adapted to adjust a fingerprint associated with the selected map point based on, at least in part, the received RF data and the accuracy indication.

28. A device comprising:

a transceiver for receiving RF signals and transmitting RF data based on the received RF signals; and

a user interface for;

(i) receiving location information, and (ii) providing feedback about the received location information.

29. The device of claim 28 further comprising a sensor for sensing a parameter associated with the received RF signal, wherein the transmitted RF data comprises the sensed parameter.

30. A method for determining a user'"'"'s location within an indoor environment, the method comprising:

receiving a location request and a set of radio frequency (RF) signals;

selecting a subset of the RF signals based on yield information associated with at least some of the received RF signals; and

identifying the location of the user based on, at least in part, data associated with the selected subset of the RF signals.