Methods resolving the elevation of a tracked personnel or assets

• US 10,401,168 B2
• Filed: 05/10/2017
• Issued: 09/03/2019
• Est. Priority Date: 06/12/2012
• Status: Active Grant

• Current Assignee: TRX Systems, Inc.
• Original Assignee: TRX Systems, Inc.
• Inventors: Karvounis, John, Napora, Jared, Funk, Benjamin E., Hakim, Dan, Giles, Christopher, Teolis, Carole
• Primary Examiner(s): Tran, Huan H
• Application Number:
  US15/591,946
• Publication Number:
  US 20170328718A1
• Time in Patent Office: 846 Days
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G01C 5/00 Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels G01C3/20, G01C3/30 take precedence
• CPC Class Codes: G01C 5/06 by using barometric means

Abstract

Methods and systems are described for determining the elevation of tracked personnel or assets (trackees) that can take input from mounted sensors on each trackee (including barometric, inertial, magnetometer, radio frequency ranging and signal strength, light and GPS sensors), external constraints (including ranging constraints, feature constraints, and user corrections), and terrain elevation data. An example implementation of this method for determining elevation of persons on foot is described. But this method is not limited to computing elevation of personnel or to on foot movements.

Claims

1. A method for updating a building elevation model, comprising:

obtaining sensor data, including location data and inertial sensor data, from a tracked computing device among a plurality of tracked computing devices;

using the sensor data to generate a path of the tracked device;

using the sensor data to estimate elevation of the tracked device;

segmenting the path;

generating a node at an endpoint of each path segment;

classifying each node based on the node'"'"'s location and the estimated elevation;

generating one or more elevation constraints for each node, wherein the elevation constraints are based on the node'"'"'s classification;

resolving the elevation constraints to refine each node'"'"'s location and estimated elevation; and

updating the building elevation model, including one or more floor heights, using each node'"'"'s refined location and estimated elevation.

2. The method of claim 1, wherein the sensor data further includes pressure data, and further comprising applying inertial aiding to remove pressure fluctuations from the pressure data.

3. The method of claim 2, wherein applying inertial aiding comprises:

transforming the inertial sensor data to compensate for tilt;

filtering the inertial sensor data;

integrating the tilt-compensated data and filtered data to calculate vertical velocity;

determining an elevation change using the vertical velocity; and

updating the pressure data based on the elevation change.

4. The method of claim 2, further comprising:

determining a stationary pressure reference to remove local pressure variation from the pressure data.

5. The method of claim 1, further comprising:

obtaining local terrain elevation data along the path to determine a local terrain elevation;

determining an elevation offset between the local terrain elevation and the estimated elevation; and

updating the estimated elevation with the elevation offset.

6. The method of claim 1, wherein segmenting the path further comprises:

parsing the path into points, based on ascending time;

determining whether a point on the path is stable relative to a consecutive point on the path using a function of the estimated elevation; and

grouping consecutive stable points into a path segment.

7. The method of claim 1, wherein classifying each node comprises:

determining whether each node is located indoors, outdoors, or underground.

8. The method of claim 7, further comprising:

associating indoor nodes with a floor in the building elevation model.

9. The method of claim 1, wherein an elevation constraint enforces a minimum and a maximum allowed adjustment to each node'"'"'s estimated elevation.

10. The method of claim 1, wherein resolving the elevation constraints further comprises:

iterating through each of the elevation constraints for each node along a path segment to determine node elevations and floor heights for each node that satisfy corresponding elevation constraint.

11. The method of claim 1, further comprising:

updating the building elevation model using the sensor data obtained from each tracked computing device among the plurality of tracked computing devices.

12. The method of claim 1, wherein the sensor data does not include pressure data.

13. The method of claim 1, wherein segmenting the path is based on one or more of time, the estimated elevation, and the location data.

14. A computing system for updating a building elevation model, the computing system comprising:

a processor;

a memory communicatively coupled to the processor, the memory bearing instructions that, when executed on the processor, cause the computing system to at least;

obtain sensor data, including location data and inertial sensor data, from a tracked computing device among a plurality of tracked computing devices;

use the sensor data to generate a path of the tracked device;

use the sensor data to estimate elevation of the tracked device;

segment the path;

generate a node at an endpoint of each path segment;

classify each node based on the node'"'"'s location and the estimated elevation;

generate one or more elevation constraints for each node, wherein the elevation constraints are based on the node'"'"'s classification;

resolve the elevation constraints to refine each node'"'"'s location and estimated elevation; and

update the building elevation model, including one or more floor heights, using each node'"'"'s refined location and estimated elevation.

15. The system of claim 14, wherein the sensor data includes pressure data, and wherein the instructions, when executed on the processor, further cause the computing system to apply inertial aiding to remove pressure fluctuations from the pressure data.

16. The system of claim 15, wherein the instructions that apply inertial aiding comprise instructions, when executed on the processor, that cause the computing system to:

transform the inertial sensor data to compensate for tilt;

filter the inertial sensor data;

integrate the tilt-compensated data and filtered data to calculate vertical velocity;

determine an elevation change using the vertical velocity; and

update the pressure data based on the elevation change.

17. The system of claim 15, wherein the instructions, when executed on the processor, further cause the computing system to at least:

determine a stationary pressure reference to remove local pressure variation from the pressure data.

18. The system of claim 14, wherein the instructions, when executed on the processor, further cause the computing system to at least:

obtain local terrain elevation data along the path to determine a local terrain elevation;

determine an elevation offset between the local terrain elevation and the estimated elevation; and

update the estimated elevation with the elevation offset.

19. The system of claim 14, wherein the instructions to segment the path, when executed on the processor, further cause the computing system to at least:

parse the path into points, based on ascending time;

determine whether a point on the path is stable relative to a consecutive point on the path using a function of the estimated elevation; and

group consecutive stable points into a path segment.

20. The system of claim 14, wherein the instructions to classify each node, when executed on the processor, further cause the computing system to at least:

determine whether each node is located indoors, outdoors, or underground.

21. The system of claim 20, wherein the instructions, when executed on the processor, further cause the computing system to:

associate indoor nodes with a floor in the building elevation model.

22. The system of claim 14, wherein an elevation constraint enforces a minimum and a maximum allowed adjustment to the node'"'"'s estimated elevation.

23. The system of claim 14, wherein the instructions to resolve the elevation constraints, when executed on the processor, further cause the computing system to at least:

iterate through the elevation constraints for each node along a path segment to determine node elevations and floor heights for each node that satisfy the corresponding elevation constraint; and

adjust node elevation and/or one or more floor heights in the building model.

24. The system of claim 14, wherein the instructions, when executed on the processor, further cause the computing system to at least:

update the building elevation model using the sensor data obtained from each tracked computing device among the plurality of tracked computing devices.

25. The system of claim 14, wherein the sensor data does not include pressure data.

26. The method of claim 14, wherein segmenting the path is based on one or more of time, the estimated elevation, and the location data.

27. A non-transitory computer readable storage medium comprising instructions that, when executed on a computing system configured to update a building elevation model, cause the computing system to at least:

obtain sensor data, including location data and inertial sensor data, from a tracked computing device among a plurality of tracked computing devices;

use the sensor data to generate a path of the tracked device;

use the sensor data to estimate elevation of the tracked device;

segment the path;

generate a node at an endpoint of each path segment;

classify each node based on the node'"'"'s location and the estimated elevation;

generate one or more elevation constraints for each node, wherein the elevation constraints are based on the node'"'"'s classification;

resolve the elevation constraints to refine each node'"'"'s location and estimated elevation; and

update the building elevation model, including one or more floor heights, using each node'"'"'s refined location and estimated elevation.

28. The non-transitory computer readable storage medium of claim 27, wherein the sensor data includes pressure data, and wherein the instructions, when executed on the computing system, cause the computing system to apply inertial aiding to remove pressure fluctuations from the pressure data.

29. The non-transitory computer readable storage medium of claim 28, wherein the instructions that apply inertial aiding comprise instructions, when executing on the computing system, cause the computing system to at least:

transform the inertial sensor data to compensate for tilt;

filter the inertial sensor data;

integrate the tilt-compensated data and filtered data to calculate vertical velocity;

determine an elevation change using the vertical velocity; and

update the pressure data.

30. The non-transitory computer readable storage medium of claim 28, wherein the instructions further cause the computing system to at least:

determine a stationary pressure reference to remove local pressure variation from the pressure data.

31. The non-transitory computer readable storage medium of claim 27, wherein the instructions further cause the computing system to at least:

obtain local terrain elevation data along the path to determine a local terrain elevation;

determine an elevation offset between the local terrain elevation and the estimated elevation; and

update the estimated elevation with the elevation offset.

32. The non-transitory computer readable storage medium of claim 27, wherein the instructions to segment the path further cause the computing system to at least:

parse the path into points, based on ascending time;

determine whether a point on the path is stable relative to a consecutive point on the path, using a function of the estimated elevation; and

group consecutive stable points into a path segment.

33. The non-transitory computer readable storage medium of claim 27, wherein the instructions to classify each node further cause the computing system to at least:

determine whether each node is located indoors, outdoors, or underground.

34. The non-transitory computer readable storage medium of claim 33, wherein the instructions, when executed on the computing system, further cause the computing system to:

associate indoor nodes with a floor in the building elevation model.

35. The non-transitory computer readable storage medium of claim 27, wherein an elevation constraint enforces a minimum and maximum allowed adjustment to the node'"'"'s estimated elevation.

36. The non-transitory computer readable storage medium of claim 27, wherein the instructions to resolve the elevation constraints further cause the computing system to at least:

iterate through the elevation constraints for each node along a path segment to determine node elevations and floor heights for each node that satisfy the corresponding elevation constraint; and

adjust node elevation and/or one or more floor heights in the building model.

37. The non-transitory computer readable storage medium of claim 27, wherein the instructions further cause the computing system to at least:

update the building elevation model using the sensor data obtained from each tracked computing device among the plurality of tracked computing devices.

38. The non-transitory computer readable storage medium of claim 27, wherein the sensor data does not include pressure data.

39. The non-transitory computer storage medium of claim 27, wherein segmenting the path is based on one or more of time, the estimated elevation, and the location data.