Multimode Pedestrian Odometer

• US 20160349376A1
• Filed: 08/27/2015
• Published: 12/01/2016
• Est. Priority Date: 06/01/2015
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Kazemi, Pejman Lotfali, MacGougan, Glenn Donald
• Granted Patent: US 10,274,605 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01S 19/34 Power consumption
• CPC Class Codes: G01S 19/52 Determining velocity

Abstract

Systems, methods and non-transitory, computer-readable storage mediums are disclosed for a multimode GNSS odometer. In some implementations, a method comprises: obtaining, by a device, position and velocity data from a sensor embedded in, or coupled to the device; statistically combining, by the device, the position and velocity data to generate a first delta distance travelled by the device over a period of time, the statistical combining including weighting a contribution of an integrated speed to the first delta distance, the integrated speed derived from the obtained velocity data and period of time; filtering, by the device, the first delta distance to generate a filtered first delta distance; and generating, by the device, a first estimate of total distance travelled by the device based on the filtered first delta distance.

Claims

1. A method comprising:

obtaining, by a mobile device, position and velocity data from a sensor embedded in, or coupled to the mobile device;

statistically combining, by the mobile device, the position and velocity data to generate a first delta distance travelled by the mobile device over a period of time, the statistical combining including weighting a contribution of an integrated speed to the first delta distance, the integrated speed derived from the obtained velocity data and period of time;

filtering, by the mobile device, the first delta distance to generate a filtered first delta distance; and

generating, by the mobile device, a first estimate of total distance travelled by the mobile device based on the filtered first delta distance.

2. The method of claim 1, further comprising:

detecting, by the mobile device, a process mode change;

responsive to the process mode change;

generating, by the mobile device, a trajectory of the mobile device over the time period using a block of the obtained position data;

determining, by the mobile device, a second delta distance travelled by the mobile device based on the trajectory; and

generating, by the mobile device, a second estimate of total distance travelled by the mobile device based on the second delta distance.

3. The method of claim 1, further comprising:

detecting, by the mobile device, a process mode change;

responsive to the process mode change;

determining, by the mobile device, a second delta distance travelled by the mobile device;

filtering, by the mobile device, the second delta distance to generate a filtered second delta distance; and

generating, by the mobile device, a second estimate of total distance travelled by the mobile device based on the filtered second delta distance.

4. The method of claim 1, wherein the sensor is a Global Navigation Satellite System (GNSS) receiver.

5. The method of claim 1, wherein statistically combining the position and velocity data to generate a first delta distance travelled by the mobile device over a period of time includes applying a Weighted Least Squares (WLS) formulation to the position data integrated speed.

6. The method of claim 1, wherein filtering the first delta distance to generate a filtered first delta distance includes applying a Kalman filter to the first delta distance.

7. The method of claim 1, wherein an amount of weighting of a contribution of an integrated speed to the first delta distance is based on an update rate of the position and velocity data from the sensor.

8. The method of claim 2, wherein generating a trajectory of the mobile device over the time period using a block of the obtained position data includes applying a polynomial fitting to the block of obtained position data.

9. The method of claim 3, wherein filtering the second delta distance to generate a filtered second delta distance includes applying a Kalman filter to the second delta distance.

10. The method of claim 1, further comprising:

receiving, by the mobile device, an update of the position and velocity from the sensor;

determining, by the mobile device, that the update is delayed due to a process change; and

terminating, by the mobile device, the method.

11. A device comprising:

a sensor;

one or more processors;

one or more computer-readable mediums coupled to the one or more processors and configured to store instructions, which, when executed by the one or more processors, causes the one or more processors to perform operations comprising;

obtaining position and velocity data from the sensor;

statistically combining the position and velocity data to generate a first delta distance travelled by the device over a period of time, the statistical combining including weighting a contribution of an integrated speed to the first delta distance, the integrated speed derived from the obtained velocity data and period of time;

filtering the first delta distance to generate a filtered first delta distance; and

generating a first estimate of total distance travelled by the device based on the filtered first delta distance.

12. The device of claim 11, further comprising:

detecting a process mode change;

responsive to the process mode change;

generating a trajectory of the device over the time period using a block of the obtained position data;

determining a second delta distance travelled by the device based on the trajectory; and

generating a second estimate of total distance travelled by the device based on the second delta distance.

13. The device of claim 11, further comprising:

detecting a process mode change;

responsive to the process mode change;

determining a second delta distance travelled by the device;

filtering the second delta distance to generate a filtered second delta distance; and

generating a second estimate of total distance travelled by the device based on the filtered second delta distance.

14. The device of claim 11, wherein the sensor is a Global Navigation Satellite System (GNSS) receiver.

15. The device of claim 11, wherein statistically combining the position and velocity data to generate a first delta distance travelled by the device over a period of time includes applying a Weighted Least Squares (WLS) formulation to the position data and the integrated speed.

16. The device of claim 11, wherein filtering the first delta distance to generate a filtered first delta distance includes applying a Kalman filter to the first delta distance.

17. The device of claim 11, wherein an amount of weighting of a contribution of the integrated speed to the first delta distance is based on an update rate of the position and velocity data from the sensor.

18. The device of claim 12, wherein generating a trajectory of the device over the time period using a block of the obtained position data includes applying a polynomial fitting to the block of obtained position data.

19. The device of claim 13, wherein filtering the second delta distance to generate a filtered second delta distance includes applying a Kalman filter to the second delta distance.

20. The device of claim 11, further comprising:

receiving an update of the position and velocity from the sensor;

determining that the update is delayed due to a process change; and

terminating one or more operations.