Indoor Location-Finding using Magnetic Field Anomalies

• US 20150018018A1
• Filed: 07/12/2013
• Published: 01/15/2015
• Est. Priority Date: 07/12/2013
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Shen, Guobin (Jacky), Zhao, Chunshui, Zhao, Feng
• Granted Patent: US 9,326,103 B2
• Time in Patent Office: Days
• US Class Current: 455/457
• CPC Class Codes: G01C 21/005 with correlation of navigation data from several sources, e.g. map or contour matching G01C21/30 takes precedence
• CPC Class Codes: G01C 21/08 involving use of the magnetic field of the earth
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: H04W 4/025 using location based information parameters
• CPC Class Codes: H04W 4/33 for indoor environments, e.g. buildings

Abstract

Techniques for indoor location-finding are described herein. Inside buildings, anomalies in the Earth'"'"'s magnetic field may be caused by the buildings'"'"' structures. These anomalies tend to be location specific and temporally stable. Accordingly, a database or map may be constructed of field strength measurements, and made available to clients, either online (e.g., through cloud services) or offline. As a user carrying a portable device walks within a building, magnetic field measurements may be made. The measurements may be configured in as vectors and compared to the database. A specific location may be indicated by anomaly information seen in both the vector(s) and database. Optionally, techniques may be combined with a particle filter that may be operated step-by-step as the user moves within the building. In another option, fusion with Wi-Fi signals may be performed, such as with a two-pass bidirectional particle filtering.

Claims

1. One or more computer-readable storage media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising:

measuring magnetic field strength at a plurality of locations within a building using a mobile device;

comparing the measured magnetic field strength at the plurality of locations to previous measurements of magnetic field strength within the building; and

identifying a location of the mobile device based at least in part on the comparison.

2. One or more computer-readable storage media as recited in claim 1, wherein the comparing comprises:

comparing a vector created by the mobile device with the previous measurements, wherein the previous measurements comprise a pre-established magnetic signal map that describes an indoor geomagnetic field that is location specific and temporally stable.

3. One or more computer-readable storage media as recited in claim 1, wherein the plurality of locations and the previous measurements of magnetic field strength comprise an indoor geomagnetic field that is location specific and temporally stable.

4. One or more computer-readable storage media as recited in claim 1, additionally comprising instruction for:

comparing received Wi-Fi signals to known Wi-Fi signals;

wherein the identifying the location of the mobile device is also based in part on the comparison of the received Wi-Fi signals and the known Wi-Fi signals.

5. One or more computer-readable storage media as recited in claim 1, additionally comprising instruction for:

accessing online maps containing floor plan information and the previous measurements of magnetic field strength and Wi-Fi information; and

accessing offline maps containing the previous measurements of magnetic field strength and Wi-Fi information.

6. One or more computer-readable storage media as recited in claim 1, additionally comprising instruction for:

fusing Wi-Fi based and magnetic field based location-finding methods using a two-pass bidirectional particle filtering method.

7. One or more computer-readable storage media as recited in claim 1, wherein:

the measuring of the magnetic field strength at the plurality of locations comprises creating a vector indicating a plurality of magnetic field strength measurements; and

the comparing comprises comparing the vector to a map depicting at least part of the building.

8. One or more computer-readable storage media as recited in claim 1, wherein measuring magnetic field strength at the plurality of locations comprises:

measuring magnetic field strength at step-sized intervals of distance, assuming uniform step distance, and assuming uniform step direction; and

forming vectors, each vector including multiple measurements.

9. One or more computer-readable storage media as recited in claim 1, wherein identifying the location is additionally based in part on a map-constrained, position-aware and inertial-based particle-motion model that performs acts comprising:

using walls indicated by map information to remove wrongly positioned and moving particles; and

using pathway directions defined by the map information to initialize particles'"'"' direction of motion.

10. A mobile device, comprising:

a processor in communication with memory and a video display;

instructions defined in the memory and executable by the processor, to;

measure magnetic field strength at a plurality of locations to define magnetic information;

compare the magnetic information to previous measurements of magnetic field strength; and

identify a location of the mobile device on the video display, based at least in part on the comparison.

11. The mobile device as recited in claim 10, wherein the previous measurements of magnetic field strength are taken at a plurality of locations.

12. The mobile device as recited in claim 10, additionally comprising instruction to:

fuse Wi-Fi based and magnetic field based location-finding methods using a particle filtering method.

13. The mobile device as recited in claim 10, additionally comprising instruction to:

compare received Wi-Fi signals to signals of known Wi-Fi transmitters;

wherein comparing the measured magnetic field strength and comparing received Wi-Fi signals are combined in part by operation of a bidirectional particle filtering process.

14. The mobile device as recited in claim 10, additionally comprising instruction to:

compare received Wi-Fi signals to signals of known Wi-Fi transmitters;

wherein the identifying is also based at least in part on the comparison of the received Wi-Fi signals.

15. The mobile device as recited in claim 10, additionally comprising:

access to map of a magnetic field within a building, the map based on pre-planned survey paths followed by one or more devices receiving inertial sensor information and magnetic sensor information.

16. A system comprising the mobile device as recited in claim 10 and cloud services, wherein the mobile device has access to cloud services comprising:

a database constructor configured for;

survey plan creation;

user trace estimation; and

trace matching; and

online maps comprising the previous measurements of magnetic field strength.

17. A method, comprising:

under control of one or more processors configured with executable instructions;

defining survey paths within a building based in part on a venue map;

receiving data from an inertial measurement unit (IMU) as the defined survey paths are walked;

receiving magnetic field data from a magnetometer as the defined survey paths are walked; and

creating a map using the IMU data and the received magnetic field data, wherein the created map is based at least in part on a plurality of magnetic field anomalies.

18. The method of claim 17, additionally comprising:

matching an estimated user trace to a corresponding portion of one of the survey paths, wherein the matching comprises matching turns consistent with the one survey path to turns consistent with the received data from the IMU.

19. The method of claim 17, additionally comprising:

storing the map as a bitmap image, wherein a gradient in the bitmap image indicates magnetic field strength.

20. The method of claim 17, additionally comprising:

applying a detection window to walking traces to search for a candidate turn within the data received from the IMU; and

identifying a candidate turn if a sum of angle changes within the window exceeds a threshold value.