Location determination using fingerprint data
First Claim
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1. A method comprising:
- receiving, by a mobile device and from a server, location fingerprint data, the location fingerprint data comprising a plurality of locations at a venue and a fingerprint of each location, the venue comprising a space accessible by a pedestrian and one or more constraints of movement of the pedestrian, each fingerprint comprising one or more expected measurements of an environment variable at the corresponding location;
receiving a measurement from one or more sensors of the mobile device, the measurement comprising one or more readings of the one or more sensors on the environment variable; and
determining a location of the mobile device at the venue using the measurement and the location fingerprint data, including performing a statistical classification categorizing the measurement using a particle filter, wherein performing the statistical classification comprises;
determining, from the location fingerprint data, a plurality of vectors, each vector corresponding to a possible location and including expected measurements of the environment variable at the corresponding possible location, each possible location corresponding to a category, each possible location being designated as a particle in the particle filter;
determining a probability density that includes a respective probability that the mobile device is located at each of the possible locations by applying a function to a difference between the measurement and each of the vectors;
classifying the measurement into a category according to the probability density; and
designating a possible location corresponding to the category as the location of the mobile device.
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Abstract
Methods, program products, and systems for using a location fingerprint database to determine a location of a mobile device are described. A mobile device can use location fingerprint data received from a server to determine a location of the mobile device at the venue. The mobile device can obtain, from a sensor of the mobile device, a vector of sensor readings, each sensor reading can measure an environment variable, e.g., a signal received by the sensor from a signal source. The mobile device can perform a statistical match between the vector and the location fingerprint data. The mobile device can then estimate a current location of the mobile device based on the statistical match.
76 Citations
24 Claims
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1. A method comprising:
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receiving, by a mobile device and from a server, location fingerprint data, the location fingerprint data comprising a plurality of locations at a venue and a fingerprint of each location, the venue comprising a space accessible by a pedestrian and one or more constraints of movement of the pedestrian, each fingerprint comprising one or more expected measurements of an environment variable at the corresponding location; receiving a measurement from one or more sensors of the mobile device, the measurement comprising one or more readings of the one or more sensors on the environment variable; and determining a location of the mobile device at the venue using the measurement and the location fingerprint data, including performing a statistical classification categorizing the measurement using a particle filter, wherein performing the statistical classification comprises; determining, from the location fingerprint data, a plurality of vectors, each vector corresponding to a possible location and including expected measurements of the environment variable at the corresponding possible location, each possible location corresponding to a category, each possible location being designated as a particle in the particle filter; determining a probability density that includes a respective probability that the mobile device is located at each of the possible locations by applying a function to a difference between the measurement and each of the vectors; classifying the measurement into a category according to the probability density; and designating a possible location corresponding to the category as the location of the mobile device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system comprising:
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a mobile device; a non-transitory computer-readable medium storing instructions operable to cause the mobile device to perform operations comprising; receiving, by a mobile device and from a server, location fingerprint data, the location fingerprint data comprising a plurality of locations at a venue and a fingerprint of each location, the venue comprising a space accessible by a pedestrian and one or more constraints of movement of the pedestrian, each fingerprint comprising one or more expected measurements of an environment variable at the corresponding location; receiving a measurement from one or more sensors of the mobile device, the measurement comprising one or more readings of the one or more sensors on the environment variable; and determining a location of the mobile device at the venue using the measurement and the location fingerprint data, including performing a statistical classification categorizing the measurement using a particle filter, wherein performing the statistical classification comprises; determining, from the location fingerprint data, a plurality of vectors, each vector corresponding to a possible location and including expected measurements of the environment variable at the corresponding possible location, each possible location corresponding to a category, each possible location being designated as a particle in the particle filter; determining a probability density that includes a respective probability that the mobile device is located at each of the possible locations by applying a function to a difference between the measurement and each of the vectors; classifying the measurement into a category according to the probability density; and designating a possible location corresponding to the category as the location of the mobile device. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A non-transitory computer-readable medium storing instructions operable to cause one or more processors to perform operations comprising:
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receiving, by a mobile device and from a server, location fingerprint data, the location fingerprint data comprising a plurality of locations at a venue and a fingerprint of each location, the venue comprising a space accessible by a pedestrian and one or more constraints of movement of the pedestrian, each fingerprint comprising one or more expected measurements of an environment variable at the corresponding location; receiving a measurement from one or more sensors of the mobile device, the measurement comprising one or more readings of the one or more sensors on the environment variable; and determining a location of the mobile device at the venue using the measurement and the location fingerprint data, including performing a statistical classification categorizing the measurement using a particle filter, wherein performing the statistical classification comprises; determining, from the location fingerprint data, a plurality of vectors, each vector corresponding to a possible location and including expected measurements of the environment variable at the corresponding possible location, each possible location corresponding to a category, each possible location being designated as a particle in the particle filter; determining a probability density that includes a respective probability that the mobile device is located at each of the possible locations by applying a function to a difference between the measurement and each of the vectors; classifying the measurement into a category according to the probability density; and designating a possible location corresponding to the category as the location of the mobile device. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24)
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Specification