Systems and methods for indoor geolocation based on yield of RF signals

• US 8,350,758 B1
• Filed: 10/01/2010
• Issued: 01/08/2013
• Est. Priority Date: 10/01/2009
• Status: Active Grant

• Current Assignee: Lighthouse Signal Systems, LLC
• Original Assignee: Lighthouse Signal Systems, LLC
• Inventors: Parvizi, Parviz, Heidari, Mohammad
• Primary Examiner(s): Keith, Jack W
• Assistant Examiner(s): Mull, Fred H
• Application Number:
  US12/896,417
• Time in Patent Office: 830 Days
• Field of Search: 342451-453, 342/463
• US Class Current: 342/452
• CPC Class Codes: G01S 5/02526 using non-dedicated equipment, e.g. user equipment or crowd-sourcing

Abstract

Systems and methods are disclosed herein for determining a user'"'"'s location within an indoor environment. In particular, the system receives a location request including a set of radio frequency signal data collected by a mobile device inside of an indoor environment. Using this data set, the system first selects a map from a plurality of maps stored in a map database. The system then processes the data to identify the user'"'"'s location on the selected map. The system uses yield information associated with the received signals in determining the map that the user is on, the user'"'"'s location on the map, or both the map and the user'"'"'s location to filter out transient signals and identify those signals that are reliably indicative of the user'"'"'s location.

Claims

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

receiving a location request including data related to a set of radio frequency (RF) signals;

selecting a map from a plurality of maps based on the received data; and

processing the received data to identify the location of the user on the map,

wherein at least one of the map selection and the location identification comprises processing the received data based on yield information associated with at least a subset of the set of received signals identified in the requests.

2. The method of claim 1, wherein the yield comprises for a given signal a measure of how often the signal is detected over a period of time.

3. The method of claim 1, wherein the yield comprises for a given signal a measure of how many times the signal is detected over a number of observations.

4. The method of claim 1, wherein selecting a map further comprises:

filtering the received data to obtain a subset of the data with preferred signal characteristics; and

comparing the filtered received data to the sets of signal sources associated with the maps.

5. The method of claim 1, wherein filtering the received data and map data sets is based on the average signal strength of the received signals.

6. The method of claim 1, wherein comparing the filtered received data to the filtered map data further comprises calculating a score for each map based on the number of filtered detected wireless signals that are in the filtered set of wireless signals of the map.

7. The method of claim 1, wherein selecting a map further comprises use of the mobile device'"'"'s approximate location to narrow a set of maps for potential selection to those in the mobile device'"'"'s region.

8. The method of claim 1, wherein processing the received data to identify the location on the map further comprises the steps of:

filtering the received data;

comparing the received data to a map data set including data for a plurality of RF signals at a plurality of locations within the selected map;

determining a variable number of most probable map points at which the user may be located; and

finding the location through interpolation of the most probable map points.

9. The method of claim 8, wherein comparing the received data to a map data set further comprises the calculation of at least one cost function for each location within the map.

10. The method of claim 9, wherein the cost functions produced are used to determine a set of most probable map points.

11. The method of claim 8, wherein the most probable map points are assigned weights which are used in the interpolation.

12. The method of claim 1, wherein processing the received data to identify the location on the map comprises processing the received data by a neural network.

13. A non-transitory computer readable medium storing computer executable instructions, which, when executed by a processor, cause the processor to carry out a method for determining a user'"'"'s location within an indoor environment comprising:

receiving a location request including data related to a set of radio frequency (RF) signals;

selecting a map from a plurality of maps based on the received data; and

processing the received data to identify the location of the user on the map,

wherein at least one of the map selection and the location identification comprises processing the received data based on yield information associated with at least a subset of the set of received signals identified in the requests.

14. The non-transitory computer readable medium of claim 13, wherein the yield comprises for a given signal a measure of how often the signal is detected over a period of time.

15. The non-transitory computer readable medium of claim 13, wherein the yield comprises for a given signal a measure of how many times the signal is detected over number of observations.

16. The non-transitory computer readable medium of claim 13, wherein selecting a map further comprises:

filtering the received data to obtain a subset of the data with preferred signal characteristics; and

comparing the filtered received data to the sets of signal sources associated with the maps.

17. The non-transitory computer readable medium of claim 13, wherein filtering the received data and map data sets is based on the average signal strength of the received signals.

18. The non-transitory computer readable medium of claim 13, wherein comparing the filtered received data to the filtered map data further comprises calculating a score for each map based on the number of filtered detected wireless signals that are in the filtered set of wireless signals of the map.

19. The non-transitory computer readable medium of claim 13, wherein selecting a map further comprises use of the mobile device'"'"'s approximate location to narrow a set of maps for potential selection to those in the mobile device'"'"'s region.

20. The non-transitory computer readable medium of claim 13, wherein processing the received data to identify the location on the map further comprises the steps of:

filtering the received data;

comparing the received data to a map data set including data for a plurality of RF signals at a plurality of locations within the selected map;

determining a variable number of most probable map points at which the user may be located; and

finding the location through interpolation of the most probable map points.

21. The non-transitory computer readable medium of claim 20, wherein comparing the received data to a map data set further comprises the calculation of at least one cost function for each location within the map.

22. The non-transitory computer readable medium of claim 21, wherein the cost functions produced are used to determine a set of most probable map points.

23. The non-transitory computer readable medium of claim 20, wherein the most probable map points are assigned weights which are used in the interpolation.

24. The non-transitory computer readable medium of claim 13, wherein processing the received data to identify the location on the map comprises processing the received data by a neural network.

25. A system for determining a user'"'"'s location within an indoor environment comprising:

a database for storing a plurality of maps in which each map contains a plurality of map points with RF fingerprint data; and

a processor configured for;

receiving a location request including data related to a set of radio frequency (RF) signals;

selecting a map from a plurality of maps based on the received data; and

processing the received data to identify the location of the user on the map,

wherein at least one of the map selection and the location identification comprises processing the received data based on yield information associated with at least a subset of the set of received signals identified in the requests.

26. The system of claim 25, further comprising at least of one receiver or transceiver configured to receive the set of radio frequency signals.

27. The system of claim 26, wherein the at least one receiver or transceiver are collocated with the processor and the database within a mobile device.

28. The system of claim 27, further comprising a memory for storing a graphical user interface for presenting the location to the user.

29. The system of claim 26, wherein the at least one receiver or transceiver is physically separated from the processor and the database, the system comprising a second processor co-located with the at least one receiver or transceiver for initiating a transmission of the location request to the processor via a wireless communication link.

30. The system of claim 28, wherein the graphical user interface is configured to accept a corrected location from the user.