ESTIMATING AND PREDICTING STRUCTURES PROXIMATE TO A MOBILE DEVICE

• US 20140070991A1
• Filed: 09/07/2012
• Published: 03/13/2014
• Est. Priority Date: 09/07/2012
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Liu, Jie, Zhong, Lin, Chu, David, Sidhu, Gursharan, Priyantha, Nissanka Arachchige Bodhi, Agarwal, Sharad
• Granted Patent: US 9,817,125 B2
• Time in Patent Office: Days
• US Class Current: 342/357.63
• CPC Class Codes: G01S 19/22 Multipath-related issues
• CPC Class Codes: G01S 19/34 Power consumption
• CPC Class Codes: G01S 19/39 the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
• CPC Class Codes: G01S 19/428 using multipath or indirect path propagation signals in position determination

Abstract

The description relates to mobile device location. One example can identify global navigation satellite system (GNSS) satellites expected to be in line-of-sight of a mobile device. This example can detect differences between received GNSS data signals and expected GNSS data signals from the expected GNSS satellites. The example can also determine a direction from the mobile device of an obstruction that is causing at least some of the detected differences.

Claims

1. One or more computer-readable storage media having instructions stored thereon that when executed by a processor of a computing device cause the computing device to perform acts, comprising:

approximating a location of a mobile device based upon a last accurate global navigation satellite system (GNSS) reading;

identifying expected GNSS data from a set of GNSS satellites that should be in line of sight to the mobile device based upon the last accurate GNSS reading and ephemeris information;

detecting differences between received GNSS data and the expected GNSS data;

recognizing a geographic feature proximate to the mobile device that is causing the differences;

predicting effects of the geographic feature on the mobile device at a subsequent time; and

,

controlling a function of the mobile device based at least in part on the predicted effects.

2. The one or more computer-readable storage media of claim 1, wherein the identifying comprises obtaining the ephemeris information from the set of GNSS satellites.

3. The one or more computer-readable storage media of claim 1, wherein the detecting comprises determining that the mobile device is in a penumbral region created by the geographic feature.

4. The one or more computer-readable storage media of claim 1, wherein the detecting comprises comparing the received GNSS data to a predefined threshold or a dynamically set threshold.

5. The one or more computer-readable storage media of claim 4, further comprising treating the received GNSS data from individual GNSS satellites that fall below the predefined threshold or the dynamically set threshold as being blocked by the geographic feature.

6. The one or more computer-readable storage media of claim 1, wherein the predicting comprises predicting whether the mobile device will enter an umbral region created by the geographic feature.

7. The one or more computer-readable storage media of claim 1, wherein the predicting comprises determining whether the mobile device is moving toward the geographic feature, away from the geographic feature, or parallel to the geographic feature.

8. The computer-readable storage media of claim 7, wherein in an instance where the mobile device is moving toward the geographic feature, the controlling comprises causing the mobile device to attempt to sense additional GNSS signals at a time that is earlier than a predefined default setting of the mobile device.

9. The computer-readable storage media of claim 7, wherein in an instance where the mobile device is moving toward the geographic feature, the predicting comprises predicting a time when the mobile device will clear the geographic feature and be able to accurately determine a subsequent location of the mobile device.

10. The computer-readable storage media of claim 9, wherein the predicting a time comprises determining a size and relative location of the geographic feature and a direction and velocity of the mobile device.

11. The one or more computer-readable storage media of claim 1, wherein the controlling comprises attempting to determine a path of the mobile device from the location.

12. The one or more computer-readable storage media of claim 1, embodied on the mobile device.

13. A computer-implemented method, comprising:

identifying global navigation satellite system (GNSS) satellites expected to be in line-of-sight of a mobile device;

detecting differences between received GNSS data signals and expected GNSS data signals from the expected GNSS satellites; and

,

determining a direction from the mobile device of an obstruction that is causing at least some of the detected differences.

14. The computer-implemented method of claim 13, wherein the identifying comprises accessing a database of ephemeris information.

15. The computer-implemented method of claim 13, wherein the detecting differences is performed on a signal strength of the GNSS data signals received from an individual GNSS satellite and wherein in an instance where the signal strength of the GNSS data signals received from the individual GNSS satellite falls below a predefined or dynamically set threshold, the individual GNSS satellite is considered to be blocked by the obstruction.

16. The computer-implemented method of claim 13, further comprising predicting future effects of the obstruction on the mobile device or suggesting a direction of user movement to reduce the future effects.

17. A mobile device, comprising:

an obstruction-detection module configured to detect an obstruction relative to the mobile device; and

,

a prediction module configured to predict future effects of the obstruction on the mobile device based at least in part on a location of the obstruction and a direction of travel of the mobile device.

18. The mobile device of claim 17, wherein the obstruction-detection module is further configured to access a crowd-sourcing database to obtain additional information about the obstruction proximate to a location of the mobile device.

19. The mobile device of claim 18, wherein the prediction module is further configured to utilize information from the crowd-sourcing database to predict the future effects.

20. The mobile device of claim 18, wherein the obstruction-detection module is further configured to contribute penumbral and umbral zone information about the obstruction to the crowd-sourcing database.