Pedestrian velocity estimation

• US 10,024,876 B2
• Filed: 06/05/2015
• Issued: 07/17/2018
• Est. Priority Date: 06/05/2015
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Miller, Isaac Thomas, MacGougan, Glenn Donald, Mayor, Robert
• Primary Examiner(s): Bui, Tha-O H
• Application Number:
  US14/732,470
• Publication Number:
  US 20160356804A1
• Time in Patent Office: 1,138 Days
• Field of Search: 702151
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G01P 3/00 Measuring linear or angular speed; Measuring differences of linear or angular speeds G01P5/00 - G01P11/00 take precedence; direction and speed indication G01P13/045; counting mechanisms G06M
• CPC Class Codes: G01S 19/05 providing aiding data
• CPC Class Codes: G01S 19/19 Sporting applications
• CPC Class Codes: G01S 19/34 Power consumption
• CPC Class Codes: G01S 19/52 Determining velocity
• CPC Class Codes: H04M 1/72454 according to context-related or environment-related conditions
• CPC Class Codes: H04M 1/72457 according to geographic location
• CPC Class Codes: H04W 4/80 Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication

Abstract

Systems, methods and computer-readable mediums are disclosed for GNSS velocity estimation for pedestrians. In some implementations, a method includes receiving a periodic sensor signal; determining a fundamental motion frequency of the periodic sensor signal; extracting a periodicity feature from the periodic sensor signal based on the fundamental motion frequency; and responsive to the extracting, initiating pedestrian velocity estimation.

Claims

1. A method comprising:

generating, by one or more motion sensors of a mobile device, a periodic sensor signal in response to periodic motion of the mobile device caused by a user'"'"'s arm swing;

receiving, by a processor of the mobile device, the periodic sensor signal;

determining, by the processor, a fundamental motion frequency of the periodic sensor signal using a sliding window Discrete Fourier Transform (DFT), where length of the sliding window is approximately equal to a fundamental period of the user'"'"'s arm swing, and lowest non-zero frequency bin output by the DFT is selected as the fundamental motion frequency;

extracting, by the processor, a periodicity feature from the periodic sensor signal based on the fundamental motion frequency;

responsive to the extracting, configuring a global navigation satellite system (GNSS) receiver of the mobile device to estimate GNSS velocity of the GNSS receiver; and

displaying, by the mobile device, the user'"'"'s speed or distance traveled based on the estimated GNSS velocity.

2. The method of claim 1, wherein the periodic sensor signal is acceleration magnitude and the periodicity feature is minimum acceleration magnitude.

3. The method of claim 1, further comprising:

tracking a phase of the periodic sensor signal based on the fundamental motion frequency.

4. The method of claim 3, where the phase is tracked using a Kalman filter.

5. The method of claim 1, where the received periodic sensor signal is pre-processed by a moving average or moving median filter.

6. A mobile device comprising:

one or more motion sensors configured to generate a periodic sensor signal in response to periodic motion of the mobile device caused by a user'"'"'s arm swing;

a display;

a global navigation satellite system (GNSS) receiver;

one or more processors;

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

determining a fundamental motion frequency of the periodic sensor signal using a sliding window Discrete Fourier Transform (DFT), where length of the sliding window DFT is approximately equal to a fundamental period of the user'"'"'s arm swing, and lowest non-zero frequency bin output by the DFT is selected as the fundamental motion frequency;

extracting a periodicity feature from the periodic sensor signal based on the fundamental motion frequency;

responsive to the extracting, configuring the GNSS receiver to estimate GNSS velocity of the GNSS receiver; and

displaying, by the display, the user'"'"'s speed or distance traveled based on the estimated GNSS velocity.

7. The mobile device of claim 6, wherein the periodic sensor signal is acceleration magnitude and the periodicity feature is minimum acceleration magnitude.

8. The mobile device of claim 6, further comprising:

tracking a phase of the periodic sensor signal based on the fundamental motion frequency.

9. The mobile device of claim 8, where the phase is tracked using a Kalman filter.

10. The mobile device of claim 6, where the received periodic sensor signal is pre-processed by a moving average or moving median filter.

11. A non-transitory, computer-readable storage medium having instructions stored thereon, that when executed by one or more processors of a mobile device, cause the one or more processors to perform operations comprising:

receiving a periodic sensor signal generated by one or more motion sensors of the mobile device in response to periodic motion of the mobile device caused by a user'"'"'s arm swing;

determining, by the one or more processor of the mobile device, a fundamental motion frequency of the periodic sensor signal using a sliding window Discrete Fourier Transform (DFT), where length of the sliding window is approximately equal to a fundamental period of the user'"'"'s arm swing, and lowest non-zero frequency bin output by the DFT is selected as the fundamental motion frequency;

extracting, by the one or more processor, a periodicity feature from the periodic sensor signal based on the fundamental motion frequency;

responsive to the extracting, configuring a GNSS receiver of the mobile device to estimate initiating pedestrian velocity estimation GNSS velocity of the GNSS receiver; and

displaying, by a display of the mobile device, the user'"'"'s speed or distance traveled based on the estimated GNSS velocity.

12. The non-transitory, computer-readable storage medium of claim 11, wherein the periodic sensor signal is acceleration magnitude and the periodicity feature is minimum acceleration magnitude.

13. The non-transitory, computer-readable storage medium of claim 11, further comprising:

tracking a phase of the periodic sensor signal based on the fundamental motion frequency.

14. The non-transitory, computer-readable storage medium of claim 13, where the phase is tracked using a Kalman filter.

15. The non-transitory, computer-readable storage medium of claim 11, where the received periodic sensor signal is pre-processed by a moving average or moving median filter.