Geofence with Kalman Filter
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0 Petitions
Accused Products
Abstract
A least squares geofence method that minimizes trigger misfires caused by data variability and location blunders and minimizes delayed/missed entry triggers generated under urban or indoor conditions. The least squares geofence method uses a weighted least squares (LS) model to compute a location estimate for a target device. A LS location estimate is used to determine if a target device is located inside or outside a predefined geofence. The present invention additionally comprises a Kalman filter geofence method that further improves the accuracy of entry/exit geofence triggers. A Kalman filter geofence method uses a Kalman filter to filter location data retrieved for a target device. Filtered location data is used to determine if a target device is located inside or outside a predefined geofence. A Kalman filter geofence method estimates velocity and heading information for a target device to generate accurate entry/exit geofence triggers for devices in fast moving mode.
9 Citations
18 Claims
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1-5. -5. (canceled)
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6. A method of detecting a geofence crossing, comprising:
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a Kalman filter module to filter a plurality of past individual location fixes retrieved for a wireless device and produce a latest Kalman-filtered location of said wireless device; triggering a geofence boundary crossing by said wireless device based on said latest Kalman-filtered location of said wireless device, on a predictive heading and velocity, and on a given geofence having said boundary; and dynamically determining a time interval before a subsequent Kalman-filtered location of said wireless device, said time interval being determined based on a velocity of said wireless device. - View Dependent Claims (7, 8, 9, 10, 11, 12)
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13. A method of detecting a geofence crossing, comprising:
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a Kalman filter module to filter a plurality of past individual location fixes retrieved for a wireless device and produce a latest Kalman-filtered location of said wireless device; triggering a geofence boundary crossing by said wireless device based on said latest Kalman-filtered location of said wireless device, on a predictive heading and velocity, and on a given geofence having said boundary; and dynamically determining an appropriate number of individual location fixes retrieved for said wireless device to produce a subsequent Kalman-filtered location of said wireless device, based on a velocity of said wireless device. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification