Location determination using RF fingerprinting
First Claim
1. A method for locating the position of a mobile unit in a wireless communication network, the method comprising:
- providing a fingerprint database having a multiplicity of RF fingerprints, each fingerprint in the fingerprint database having an associated unique location;
generating a location probability distribution by assigning respective probabilities to locations associated with fingerprints in the fingerprint database;
capturing an RF fingerprint in the mobile unit;
updating the location probability distribution using the fingerprint, so captured, and the fingerprint database by generating an additional probability distribution based on the fingerprint database and the fingerprint, so captured, and combining the additional probability distribution with the location probability distribution to generate an updated location probability distribution; and
using the updated location probability distribution to generate an estimate of the position of the mobile unit.
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Abstract
A method for determining the location of a mobile unit (MU) in a wireless communication system and presenting it to a remote party. The location of a remote MU is determined by comparing a snapshot of a predefined portion of the radio-frequency (RF) spectrum taken by the MU to a reference database containing multiple snapshots taken at various locations. The result of the comparison is used to determine if the MU is at a specific location. The comparison may be made in the MU, or at some other location situated remotely from the MU. In the latter case, sufficient information regarding the captured fingerprint is transmitted from the MU to the remote location. The database may be pre-compiled or generated on-line.
444 Citations
36 Claims
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1. A method for locating the position of a mobile unit in a wireless communication network, the method comprising:
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providing a fingerprint database having a multiplicity of RF fingerprints, each fingerprint in the fingerprint database having an associated unique location;
generating a location probability distribution by assigning respective probabilities to locations associated with fingerprints in the fingerprint database;
capturing an RF fingerprint in the mobile unit;
updating the location probability distribution using the fingerprint, so captured, and the fingerprint database by generating an additional probability distribution based on the fingerprint database and the fingerprint, so captured, and combining the additional probability distribution with the location probability distribution to generate an updated location probability distribution; and
using the updated location probability distribution to generate an estimate of the position of the mobile unit. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
capturing an additional fingerprint of the RF spectrum in the mobile unit; and
using the additional fingerprint, so captured, and the fingerprint database to update the updated location probability distribution and so generate a further updated location probability distribution.
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10. The method of claim 1 wherein the fingerprint database is generated from field measurements at predetermined locations and from interpolation of fingerprints at locations in between the predetermined locations.
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11. The method of claim 1 wherein the fingerprint database is generated by calculations with RF prediction models.
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12. The method of claim 1 wherein the fingerprint database is generated by calculations with RF prediction models and calibrated using field measurements.
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13. The method of claim 1 wherein:
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the fingerprint database is stored in an Other Party that is linked to the mobile unit via the wireless communication network; and
the fingerprint, so captured, is transmitted over the wireless network to the Other Party; and
the Other Party generates the location probability distribution, updates the probability distribution, and generates the estimate of the position of the mobile unit.
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14. The method of claim 1 wherein the mobile unit generates the estimate of the position of the mobile unit.
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15. A method for locating the position of a mobile unit in a wireless communication network, the method comprising:
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providing a fingerprint database having a multiplicity of RF fingerprints, each fingerprint in the fingerprint database having an associated unique location;
capturing a measured RF fingerprint from the mobile unit;
generating a location probability distribution by assigning respective probabilities to locations associated with fingerprints in the fingerprint database by comparing the measured RF fingerprint to each of the multiplicity of RE fingerprints; and
using the location probability distribution to generate an estimate of the position of the mobile unit. - View Dependent Claims (16, 17, 18, 19, 20, 21)
capturing an additional fingerprint of the RF spectrum in the mobile unit and using the additional fingerprint, so captured, and the fingerprint database to update the updated location probability distribution and so generate a further updated location probability distribution.
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22. A method for locating the position of a mobile unit in a wireless communication network, the method comprising:
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providing a fingerprint database having a multiplicity of RF fingerprints, each fingerprint in the fingerprint database having an associated unique location;
generating a location probability distribution by assigning respective probabilities to locations associated with fingerprints in the fingerprint database;
capturing a series of fingerprints in the mobile unit at different times;
for each successively captured fingerprint, recursively updating the location probability distribution, each updating using a previous version of the location probability distribution, the fingerprint database, and the successively captured fingerprint; and
using the updated location probability distribution to generate an estimate of the position of the mobile unit. - View Dependent Claims (23, 24, 25, 26, 27)
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28. A method for tracking the position of a mobile unit in a wireless communication network, the method comprising:
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providing a fingerprint database having a multiplicity of RF fingerprints, each fingerprint in the predicted fingerprint database having an associated unique location;
capturing a series of measured RF fingerprints from the mobile unit at different times;
starting from an initial state in which each location is assigned the same probability;
for each successively captured RF fingerprint, recursively updating the location probability distribution, each updating using the previous version of the location probability distribution and a location probability distribution calculated from the captured fingerprint; and
using the series of location probability distributions so calculated to generate an updated series of estimates of the position of the mobile unit. - View Dependent Claims (29, 30, 31)
using the Markov model to predict the location probability distribution to some future time where a measured fingerprint may not be available; and
using the predicted location probability distribution to generate an estimate of the position of the mobile unit at that future time.
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32. A method for locating the position of a mobile unit in a wireless communication network, the method comprising:
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providing a fingerprint database having a multiplicity of RF fingerprints, each fingerprint in the fingerprint database having an associated unique location;
providing a Markov model that provides, for at least one location, transition probabilities that the mobile unit at that location will transition to other locations within a time interval between successive fingerprint captures;
generating a location probability distribution by assigning respective probabilities to locations associated with fingerprints in the fingerprint database;
capturing a series of fingerprints in the mobile unit at different times;
for each newly captured fingerprint, recursively updating the location probability distribution, each updating being performed by;
subjecting the previous version of the location probability distribution to the Markov model to provide a predicted probability distribution reflecting the transition probabilities in the Markov model, comparing the newly captured fingerprint with the fingerprint database to generate an additional probability distribution based on the fingerprint database and the newly captured fingerprint, and combining the additional probability distribution with the predicted probability distribution to provide the newly updated location probability distribution; and
using an updated version of the location probability distribution to generate an estimate of the position of the mobile unit. - View Dependent Claims (33, 34, 35, 36)
using the Markov model to predict the location probability distribution to some future time where a measured fingerprint may not be available; and
using the predicted location probability distribution to generate an estimate of the position of the mobile unit at that future time.
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35. The method of claim 32 wherein the fingerprint database is generated from field measurements at predetermined locations and from interpolation of fingerprints at locations in between the predetermined locations.
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36. The method of claim 32 wherein the fingerprint database is generated by calculations with RF prediction models.
Specification