METHOD AND SYSTEM FOR LOCATION ESTIMATION

• US 20150249907A1
• Filed: 02/28/2014
• Published: 09/03/2015
• Est. Priority Date: 02/28/2014
• Status: Active Grant

• Current Assignee: Texas Instruments, Inc.
• Original Assignee: Texas Instruments, Inc.
• Inventors: Ramakrishnan, Sthanunathan, Balakrishnan, Jaiganesh, Bhardwaj, Sachin, Gupta, Pankaj
• Granted Patent: US 9,374,678 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/024 Guidance services
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/043 using ambient awareness, e.g. involving buildings using floor or room numbers
• CPC Class Codes: H04W 4/33 for indoor environments, e.g. buildings

Abstract

Several systems and methods for location estimation in a multi-floor environment are disclosed. In an embodiment, the method includes performing wireless scanning so as to receive wireless signals from one or more access points from among a plurality of access points positioned at plurality of locations, respectively at one or more floors from among a plurality of floors within the multi-floor environment. A first set of RSSI measurements is computed corresponding to the wireless signals. Absolute floor location information is determined based on the first set of RSSI measurements and a pre-defined objective function. The pre-defined objective function is configured to maximize a probability of a user being located at a floor so as to receive the wireless signals. A user floor location is determined based on the absolute floor location information. The user location is estimated at least in part based on the user floor location.

Claims

1. A location estimation method comprising:

performing a wireless scanning so as to receive wireless signals from one or more access points from among a plurality of access points positioned at plurality of locations, respectively, at one or more floors from among a plurality of floors within a multi-floor environment;

computing a first set of received signal strength indication (RSSI) measurements corresponding to the wireless signals;

determining absolute floor location information in the multi-floor environment based on the first set of RSSI measurements and a pre-defined objective function, the pre-defined objective function configured to maximize a probability of a user being located at a floor from among the plurality of floors so as to receive the wireless signals corresponding to the first set of RSSI measurements, wherein the probability is estimated based on a three-dimensional channel model comprising a plurality of channel model parameters;

determining a user floor location based on the absolute floor location information; and

estimating the user location in the multi-floor environment based at least in part on the user floor location.

2. The method of claim 1, wherein the plurality of channel model parameters comprises at least one of log-normal shadowing model parameters and parameters accounting for signal attenuation across floors in the multi-floor environment.

3. The method of claim 1, further comprising identifying, subsequent to performing the wireless scanning, a primary set of access points and a secondary set of access points from among the plurality of access points, wherein the primary set of access points correspond to those one or more access points from which wireless signals are received during the wireless scanning, and, the secondary set of access points correspond to those access points whose presence has been ascertained previous to the wireless scanning and from which wireless signals are not received during the wireless scanning.

4. The method of claim 3, further comprising:

computing a geometric measure based on locations associated with access points from among the identified primary set of access points and the secondary set of access points;

generating an imaginary three-dimensional grid based on the geometric measure, the three-dimensional grid extending across one or more floors in the multi-floor environment and comprising a plurality of grid points;

computing a likelihood value at each grid point of the plurality of grid points;

identifying a set of grid points with associated likelihood values which when averaged maximizes the pre-defined objective function, the set of grid points associated with a floor location from among the one or more floors; and

identifying floor location information associated with the set of grid points as the absolute floor location information, the absolute floor location information comprising an absolute floor location estimate and a first uncertainty estimate associated with the absolute floor location estimate.

5. The method of claim 4, further comprising determining relative floor location information based on pressure sensor measurements corresponding to user movements in the multi-floor environment, wherein the relative floor location information comprises a relative floor location estimate and a second uncertainty estimate associated with the relative floor location estimate, the relative user floor location estimate computed by comparing a change in altitude associated with the user movements to a relative floor height value.

6. The method of claim 5, wherein the user floor location is determined along with a third uncertainty estimate by optimally weighing the absolute floor location estimate and the relative floor location estimate based on the first uncertainty estimate and the second uncertainty estimate.

7. The method of claim 6, wherein the relative floor height value is dynamically adapted based on periodic estimates of the user floor location if associated values of third uncertainty estimates are below a pre-defined acceptable level of uncertainty estimate.

8. The method of claim 6, further comprising performing:

detecting a presence of step movements associated with the user movements based on accelerometer measurements received from an accelerometer;

determining a vertical motion indication and a vertical velocity information based on the pressure sensor measurements; and

computing a context of the user location based on the step movements detection and the determined vertical motion indication and the vertical velocity information, wherein the context of the user location is one of a staircase context, an elevator context, an escalator context and an on-floor context.

9. The method of claim 8, wherein estimating the user location comprises:

identifying access points from among the primary set of access points and the secondary set of access points associated with one or more floors in the vicinity of the user floor location;

generating an imaginary two-dimensional grid across the user floor location based on the identified access points; and

computing a two-dimensional location estimate within the user floor location along with associated fourth uncertainty measure based on a second set of RSSI measurements corresponding to wireless signals received from at least one of access points positioned in the user floor location and access points positioned in the vicinity of the user floor location, wherein the two-dimensional location estimate is computed based on minimum mean square error (MMSE) algorithm configured to compute weighted probabilities of a user being located at various positions in the imaginary two-dimensional grid.

10. The method of claim 9, further comprising fusing the two-dimensional location estimate and the fourth uncertainty estimate with at least one of the context of the user location, the user floor location and the associated third uncertainty estimate, and a map information associated with the multi-floor environment to determine a three-dimensional estimate of the user location.

11. The method of claim 10, wherein values of the plurality of channel model parameters are iteratively adapted based on the user floor location and the user location to assist in subsequent estimation of the user floor location and the user location.

12. A location estimation system comprising:

a transceiver module configured to perform a wireless scanning so as to receive wireless signals from one or more access points from among a plurality of access points positioned at plurality of locations, respectively, at one or more floors from among a plurality of floors within a multi-floor environment; and

a location estimation module communicatively associated with the transceiver module and configured to;

compute a first set of received signal strength indication (RSSI) measurements corresponding to the wireless signals;

determine absolute floor location information in the multi-floor environment based on the first set of RSSI measurements and a pre-defined objective function, the pre-defined objective function configured to maximize a probability of a user being located at a floor from among the plurality of floors so as to receive the wireless signals corresponding to the first set of RSSI measurements, wherein the probability is estimated based on a three-dimensional channel model comprising a plurality of channel model parameters;

determine a user floor location based on the absolute floor location information; and

estimate the user location in the multi-floor environment based at least in part on the user floor location.

13. The system of claim 12, wherein the location estimation module is further configured to identify, subsequent to performing the wireless scanning, a primary set of access points and a secondary set of access points from among the plurality of access points, wherein the primary set of access points correspond to those one or more access points from which wireless signals are received during the wireless scanning, and, the secondary set of access points correspond to those access points whose presence has been ascertained previous to the wireless scanning and from which wireless signals are not received during the wireless scanning.

14. The system of claim 13, wherein the location estimation module is further configured to:

compute a geometric measure based on locations associated with access points from among the identified primary set of access points and the secondary set of access points;

generate an imaginary three-dimensional grid based on the geometric measure, the three-dimensional grid extending across one or more floors in the multi-floor environment and comprising a plurality of grid points;

compute a likelihood value at each grid point of the plurality of grid points;

identify a set of grid points with associated likelihood values which when averaged maximizes the pre-defined objective function, the set of grid points associated with a floor location from among the one or more floors; and

identify floor location information associated with the set of grid points as the absolute floor location information, the absolute floor location information comprising an absolute floor location estimate and a first uncertainty estimate associated with the absolute floor location estimate.

15. The system of claim 14, wherein the location estimation module is further configured to:

determine relative floor location information based on pressure sensor measurements corresponding to user movements in the multi-floor environment, wherein the relative floor location information comprises a relative floor location estimate and a second uncertainty estimate associated with the relative floor location estimate, the relative user floor location estimate computed by comparing a change in altitude associated with the user movements to a relative floor height value.

16. The system of claim 15, wherein the user floor location is determined along with a third uncertainty estimate by optimally weighing the absolute floor location estimate and the relative floor location estimate based on the first uncertainty estimate and the second uncertainty estimate.

17. The system of claim 16, wherein the location estimation module is further configured to:

detect a presence of step movements associated with the user movements based on accelerometer measurements received from an accelerometer;

determine a vertical motion indication and a vertical velocity information based on the pressure sensor measurements; and

compute a context of the user location based on the step movements detection and the determined vertical motion indication and the vertical velocity information, wherein the context of the user location is one of a staircase context, an elevator context, an escalator context and an on-floor context.

18. The system of claim 17, wherein estimating the user location comprises:

identifying access points from among the primary set of access points and the secondary set of access points associated with one or more floors in the vicinity of the user floor location;

generating an imaginary two-dimensional grid across the user floor location based on the identified access points;

computing a two-dimensional location estimate within the user floor location along with associated fourth uncertainty measure based on a second set of RSSI measurements corresponding to wireless signals received from at least one of access points positioned in the user floor location and access points positioned in the vicinity of the user floor location, wherein the two-dimensional location estimate is computed based on minimum mean square error (MMSE) algorithm configured to computed weighted probabilities of a user being located at various positions in the imaginary two-dimensional grid; and

fusing the two-dimensional location estimate and the fourth uncertainty estimate with at least one of the context of the user location, the user floor location and the associated third uncertainty estimate, and a map information associated with the multi-floor environment to determine a three-dimensional estimate of the user location.

19. A location estimation system comprising:

a transceiver module configured to receive a user floor location and associated floor location uncertainty estimate within a multi-floor environment; and

a location estimation module communicatively associated with the transceiver module and configured to;

generate an imaginary two-dimensional grid across the user floor location; and

compute a two-dimensional location estimate within the user floor location along with associated uncertainty measure based on RSSI measurements corresponding to wireless signals received from at least one of access points positioned in the user floor location and access points positioned in the vicinity of the user floor location, wherein the two-dimensional location estimate is computed based on MMSE algorithm configured to compute weighted probabilities of a user being located at various positions in the imaginary two-dimensional grid.

20. The location estimation system of claim 19, wherein the location estimation module is further configured to estimate the user location in the multi-floor environment by fusing the two-dimensional location estimate and the associated uncertainty measure with at least one of a context of the user location, the user floor location and the floor location uncertainty estimate, and a map information associated with the multi-floor environment to determine a three-dimensional estimate of the user location, wherein the context of the user location is one of a staircase context, an elevator context, an escalator context and an on-floor context.