SCALABLE INDOOR NAVIGATION AND POSITIONING SYSTEMS AND METHODS

• US 20170332203A1
• Filed: 04/06/2017
• Published: 11/16/2017
• Est. Priority Date: 05/11/2016
• Status: Active Grant

• Current Assignee: Mapsted Corp.
• Original Assignee: Mapsted Corp.
• Inventors: Nagpal, Paramvir Singh, Huberman, Sean, Hamidifar, Saeedeh
• Granted Patent: US 9,906,914 B2
• Time in Patent Office: Days
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: H04W 4/024 Guidance services
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/30 Services specially adapted for particular environments, situations or purposes
• CPC Class Codes: H04W 4/33 for indoor environments, e.g. buildings
• CPC Class Codes: H04W 4/50 Service provisioning or reconfiguring
• CPC Class Codes: H04W 4/90 Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]

Abstract

Embodiments of the present disclosure related to methods and systems of determining the position of a device in indoor space. A map importing module takes a floor map of an indoor space and processes it for further use. A calibration module creates a fingerprint map of the indoor space described by the floor map. A positioning module uses the calibration data embodied in a fingerprint map as well as device signal and sensor readings in order to estimate a trajectory for the device, then position the device within the indoor space described by the floor map using a probability density function.

Claims

1. A method of determining a position of a device within an indoor location, comprising:

gathering device signal data;

gathering device sensor data;

estimating a plurality of potential trajectories of the device based on the device signal data, the device sensor data, and a fingerprint map; and

determining the position of the device based on a data fusion of the estimated plurality of potential trajectories.

2. The method of claim 1, wherein the fingerprint map comprises a plurality of fingerprint locations, each of the plurality of fingerprint locations having at least one associated device signal data value or device sensor data value.

3. The method of claim 1, wherein the estimating the plurality of potential trajectories comprises a lightweight local optimization.

4. The method of claim 1, wherein the fingerprint map is constructed by inferring the plurality of signal data values based on actual signal data values.

5. The method of claim 4, wherein the actual signal data values are recorded by a calibration module.

6. The method of claim 1, further comprising estimating a step length and a heading based on the device sensor data.

7. The method of claim 1, further comprising updating the fingerprint map with the position of the device.

8. The method of claim 1, further comprising orienting the device to the global coordinate system.

9. The method of claim 8, wherein the orienting the device to the global coordinate system is performed using a rotation matrix.

10. The method of claim 1, wherein the device signal data comprise Wi-Fi data, Bluetooth data, GPS data and cellular data.

11. The method of claim 1, wherein the device sensor data comprise accelerometer data, barometric pressure data, magnetometer data, and gyroscope data.

12. A system for determining a position of a device in an indoor location, the system comprising:

a memory;

a processor;

a module that is stored in the memory and, when executed by the processor, determines the position of a device in an indoor location by performing the steps of;

gathering device signal data;

gathering device sensor data;

estimating a plurality of potential trajectories of the device based on the device signal data, the device sensor data, and a fingerprint map; and

determining the position of the device based on a data fusion of the estimated plurality of potential trajectories.

13. The system of claim 12, wherein the fingerprint map comprises a plurality of fingerprint locations, each of the plurality of fingerprint locations having at least one associated device signal data value or device sensor data value.

14. The system of claim 13, wherein the estimating the plurality of potential trajectories comprises a lightweight local optimization.

15. The system of claim 16, wherein the fingerprint map is constructed by inferring the plurality of signal data values based on actual signal data values.

16. The system of claim 17, wherein the actual signal data values are recorded by a calibration module.

17. The system of claim 12, further comprising estimating a step length and a heading based on the device sensor data.

18. The system of claim 12, wherein the device signal data comprise Wi-Fi data, Bluetooth data, GPS data and cellular data.

19. The method of claim 12, wherein the device sensor data comprise accelerometer data, barometric pressure data, magnetometer data, and gyroscope data.

20. A non-transitory computer-readable medium disposed in an audio device, the non-transitory computer-readable medium containing a set of instructions that causes a processor to perform a process comprising:

gathering device signal data;

gathering device sensor data;

estimating a plurality of potential trajectories of the device based on the device signal data, the device sensor data, and a fingerprint map; and

determining the position of the device based on a data fusion of the estimated plurality of potential trajectories.