CONTROLLING A GPS RECEIVER BY DETECTING MOTION BASED ON RADIOFREQUENCY SIGNAL TRACES

• US 20120223861A1
• Filed: 05/16/2012
• Published: 09/06/2012
• Est. Priority Date: 06/29/2009
• Status: Active Grant

• Current Assignee: Malikie Innovations Limited (Key Patent Innovations Limited)
• Original Assignee: Blackberry Limited
• Inventors: KÜPFER, Sandra Marcela, BROWN, Michael Stephen
• Granted Patent: US 8,482,461 B2
• Time in Patent Office: Days
• US Class Current: 342/357.74
• CPC Class Codes: G01S 19/34 Power consumption
• CPC Class Codes: G01S 19/48 by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system

Abstract

Operation of a satellite-based navigation-signal broadcast system receiver, such as a GPS receiver, on a wireless communications device is controlled by determining whether the device is stationary or in motion. Motion determination is accomplished by analyzing radiofrequency signal traces, e.g. GSM signal traces, received from one or more nearby base stations. A three-tiered analysis provides a progressively more accurate determination as to whether the device is moving or stationary while providing, in certain instances, a more rapid determination than prior-art techniques. When the device is determined to be stationary, the GPS receiver can be deactivated. When the device is determined to be moving, the receiver can be reactivated.

Claims

1. A method, performed by a wireless communications device, of controlling operation of a receiver configured to receive signals from a satellite-based navigation-signal broadcast system, the method comprising:

receiving radiofrequency signal traces from one or more base station towers;

applying first and second classifiers to determine from the signal traces whether the wireless communications device is moving or stationary, wherein the second classifier comprises a greater number of signal features than the first classifier;

deactivating the receiver when the wireless communications device is determined to be stationary; and

reactivating the receiver when the wireless communications device is determined to be moving.

2. The method as claimed in claim 1 further comprising applying a third classifier, wherein the third classifier comprises a greater number of signal features than the second classifier.

3. The method as claimed in claim 1 wherein:

applying the first classifier comprises computing three signal features; and

applying the second classifier comprises computing seven signal features.

4. The method as claimed in claim 2 wherein:

applying the first classifier comprises computing three signal features;

applying the second classifier comprises computing seven signal features; and

applying the third classifier comprises computing eleven signal features.

5. The method as claimed in claim 4 wherein applying the first classifier comprises computing three signal features over two consecutive data points for a first minute, wherein applying the second classifier comprises computing seven signal features over a short moving window of seven data points after one minute has elapsed for a subsequent four minutes, and wherein applying the third classifier comprises computing eleven signal features over a long moving window of thirty-one data points after five minutes have elapsed.

6. The method as claimed in claim 4 wherein the three signal features used for the first classifier are:

(i) common base station towers;

(ii) Spearman rank correlation coefficient; and

(iii) Euclidean distance;

and wherein the seven signal features used for the second classifier are;

(i) common base station towers;

(ii) Spearman rank correlation coefficient;

(iii) Euclidean distance;

(iv) mean of Euclidean distance over 7 data points;

(v) variance of Euclidean distance over 7 data points;

(vi) Euclidean distance between endpoints over 7 data points; and

(vii) signal strength variance for all base stations in window over 7 data points; and

wherein the eleven signal features used for the third classifier are;

(i) common base station towers;

(ii) Spearman rank correlation coefficient;

(iii) Euclidean distance;

(iv) mean of Euclidean distance over 7 data points;

(v) variance of Euclidean distance over 7 data points;

(vi) Euclidean distance between endpoints over 7 data points;

(vii) signal strength variance for all base stations in window over 7 data points;

(viii) mean of Euclidean distance over 31 data points;

(ix) variance of Euclidean distance over 31 data points;

(x) Euclidean distance between endpoints over 31 data points; and

(xi) signal strength variance for all base stations in window over 31 data points.

7. The method as claimed in claim 1 further comprising deferring reactivation of the receiver until the device has determined for a predetermined minimum consecutive number of times that the device is moving.

8. The method as claimed in claim 1 further comprising deferring deactivation of the receiver until the device has determined that the device has remained stationary for a period of exceeding a predetermined time threshold.

9. A machine-readable storage medium comprising instructions in code which, when loaded into memory and executed on a processor of a wireless communications device, controls operation of a receiver configured to receive signals from a satellite-based navigation-signal broadcast system by:

receiving radiofrequency signal traces from one or more base station towers;

applying first and second classifiers to determine from the signal traces whether the wireless communications device is moving or stationary, wherein the second classifier comprises a greater number of signal features than the first classifier;

deactivating the receiver when the wireless communications device is determined to be stationary; and

reactivating the receiver when the wireless communications device is determined to be moving.

10. The machine-readable storage medium as claimed in claim further comprising code for applying a third classifier, wherein the third classifier comprises a greater number of signal features than the second classifier.

11. The machine-readable storage medium as claimed in claim 10 further comprising code for applying the first classifier by computing three signal features over two consecutive data points for a first minute, code for applying the second classifier by computing seven signal features over a short moving window of seven data points after one minute has elapsed for a subsequent four minutes, and code for applying the third classifier by computing eleven signal features over a long moving window of thirty-one data points after five minutes have elapsed.

12. A wireless communications device comprising:

a receiver for determining a current location of the device from a satellite-based navigation-signal broadcast system;

a radiofrequency transceiver for receiving signal traces from one or more nearby base stations; and

a processor operatively coupled to memory for applying first and second classifiers to determine from the signal traces whether the wireless communications device is moving or stationary, wherein the second classifier comprises a greater number of signal features than the first classifier, the processor deactivating the receiver when the device is determined to be stationary and reactivating the receiver when the device is determined to be moving.

13. The device as claimed in claim 12 wherein the processor applies a third classifier, wherein the third classifier comprises a greater number of signal features than the second classifier.

14. The device as claimed in claim 13 wherein the processor applies the first classifier by computing three signal features, the second classifier by computing seven signal features, and the third classifier by computing eleven signal features, wherein the first classifier computes three signal features over two consecutive data points for a first minute, wherein the second classifier computes seven signal features over a short moving window of seven data points after one minute has elapsed for a subsequent four minutes, and wherein the third classifier computes eleven signal features over a long moving window of thirty-one data points after five minutes have elapsed.

15. The device as claimed in claim 13 wherein the three signal features used for the first classifier are:

(i) common base station towers;

(ii) Spearman rank correlation coefficient; and

(iii) Euclidean distance.

16. The device as claimed in claim 13 wherein the seven signal features used for the second classifier are:

(i) common base station towers;

(ii) Spearman rank correlation coefficient;

(iii) Euclidean distance;

(iv) mean of Euclidean distance over 7 data points;

(v) variance of Euclidean distance over 7 data points;

(vi) Euclidean distance between endpoints over 7 data points; and

(vii) signal strength variance for all base stations in window over 7 data points.

17. The device as claimed in claim 13 wherein the eleven signal features used for the third classifier are:

(i) common base station towers;

(ii) Spearman rank correlation coefficient;

(iii) Euclidean distance;

(iv) mean of Euclidean distance over 7 data points;

(v) variance of Euclidean distance over 7 data points;

(vi) Euclidean distance between endpoints over 7 data points;

(vii) signal strength variance for all base stations in window over 7 data points;

(viii) mean of Euclidean distance over 31 data points;

(ix) variance of Euclidean distance over 31 data points;

(x) Euclidean distance between endpoints over 31 data points; and

(xi) signal strength variance for all base stations in window over 31 data points.

18. A method of training classifiers for determining whether a wireless communications device is moving or stationary based on radiofrequency signal traces received from nearby base stations, the method comprising:

identifying a plurality of signal features for analyzing signal traces;

receiving radiofrequency signal traces from one or more base station towers;

receiving accelerometer readings indicating whether the device is moving or stationary; and

training first and second classifiers by determining coefficients of logistic functions, the first and second classifiers providing a progressively more accurate determination as to whether the wireless communications device is moving or stationary.

19. The method as claimed in claim 18 further comprising training a third classifier.