Doppler aided inertial navigation

• US 10,371,806 B2
• Filed: 12/11/2015
• Issued: 08/06/2019
• Est. Priority Date: 10/08/2010
• Status: Active Grant

• Current Assignee: MDSP Technologies LLC
• Original Assignee: TeleCommunication Systems Inc (Comtech Telecommunications Corporation)
• Inventors: Mathews, Michael B., MacDoran, Peter F.
• Primary Examiner(s): Gregory, Bernarr E
• Assistant Examiner(s): Mull, Fred H
• Application Number:
  US14/966,318
• Publication Number:
  US 20160131751A1
• Time in Patent Office: 1,334 Days
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01S 11/10 using Doppler effect
• CPC Class Codes: G01S 5/0263 by combining or switching between positions derived from two or more separate positioning systems

Abstract

Doppler Aided Inertial Navigation (DAIN) facilitates the determination of position, velocity and direction of mobile devices operating in highly obstructed GPS/GNSS environments. Delivering high precision, high resolution positioning information using signals of opportunity, the present invention measures the Doppler shift of a moving device using a variety of signals combined with inertial accelerometers and environmental sensors to deliver an autonomous positioning and navigation capability that does not require external infrastructure or a priori knowledge of signal sources.

Claims

1. A mobile computing device comprising:

a receiver that transforms two or fewer intercepted radio frequency emissions external to the mobile computing device into Doppler frequency observables;

a plurality of inertial sensors, each sensor having a linear accelerometer that produces acceleration observables;

a spectral compression positioning sensor that performs spectral compression utilizing a non-linear operation on the Doppler frequency observables to produce a set of Doppler frequency observables in a format for physical state estimation by the physical state estimator; and

a physical state estimator that;

processes the set of Doppler frequency observables and the acceleration observables to determine a member of a physical state of the mobile computing device;

converts Doppler frequency observables to speed; and

corrects inertial drift error of the plurality of inertial sensors based on the speed.

2. The mobile computing device of claim 1, wherein the set of observables includes a physical characteristic of the two or less intercepted radio frequency emissions including at least one of an amplitude, a phase and a temporal derivative.

3. The mobile computing device of claim 1, wherein the plurality of inertial sensors have a rotational accelerometer that produces angular acceleration observables.

4. The mobile computing device of claim 1, further comprising an environmental sensor that provides information related to the environment in which the mobile computing device is located, wherein the environmental sensor includes one of a magnetic compass or a barometric pressure sensor.

5. The mobile computing device of claim 1, further comprising a positioning sensor that provides information related to the location of the mobile computing device.

6. The mobile computing device of claim 1, further comprising:

a map cache that provides map information relative to a current physical location of the mobile computing device; and

a map matching component that compares the map information to the member of the physical state of the mobile computing device, wherein the physical state estimator updates the member of the physical state of the mobile computing device based on the comparison.

7. The mobile computing device of claim 1, wherein the mobile computing device is carried on a person and the physical state estimator estimates the step-size and step-rate of the person based on the Doppler frequency observables and acceleration observables.

8. The mobile computing device of claim 7, wherein the physical state estimator updates the member of the physical state of the mobile computing device based on the step-size and step-rate.

9. The mobile computing device of claim 1, wherein the two or fewer intercepted radio frequency emissions external to the mobile computing device are propagated from a terrestrial source.

10. The mobile computing device of claim 1, the plurality of inertial sensors further comprising a rotational accelerometer that provides rotational acceleration observables associated with the mobile computing device, wherein systematic biases within the rotational acceleration observables are removed using Doppler data over time intervals exceeding a few seconds.

11. A method comprising:

intercepting, at a RF Doppler Receiver, two or fewer radio frequency emissions external to a mobile computing device;

transforming, at a spectral compression positioning sensor, by spectral compression utilizing a non-linear operation, the Doppler frequency observables from the two or fewer intercepted radio frequency emissions into a set of Doppler frequency observables for physical state estimation;

receiving, at a physical state estimator, acceleration observables from a linear accelerometer from a plurality of inertial sensors associated with the mobile computing device;

processing, at the physical state estimator, the set of Doppler frequency observables and received acceleration observables to determine a member of a physical state of the mobile computing device;

determining, at a narrowband signal detector, speed of the mobile computing device from the Doppler frequency observables; and

correcting, at the physical state estimator, inertial drift error based on the speed.

12. The method of claim 11, further comprising:

producing, by the spectral compression positioning sensor, physical characteristics of each observable of the set of Doppler frequency observables in the form of amplitude, phase and temporal derivatives of the two or less intercepted radio frequency emissions.

13. The method of claim 11, further comprising:

receiving, at the physical state estimator, acceleration observables from a rotational accelerometer associated with the mobile computing device.

14. The method of claim 11, further comprising:

receiving, at the physical state estimator, information related to the environment in which the mobile computing device is located from an environmental sensor; and

processing, at the physical state estimator, the received information related to the environment to determine another member of the physical state of the mobile computing device.

15. The method of claim 11, further comprising:

receiving, at the physical state estimator, information related to the location of the mobile computing device from a positioning sensor associated with the mobile computing device; and

processing, at the physical state estimator, the received information related to the location of the mobile computing device to determine another member of the physical state of the mobile computing device.

16. The method of claim 11, further comprising:

comparing, at a map matching module, the member of the physical state of the mobile computing device with map information relative to a current physical location of the mobile computing device from a map cache; and

updating, at the physical state estimator, information associated with the member of the physical state of the mobile computing device.

17. The method of claim 11, further comprising:

estimating, at the physical state estimator, the step-size and step-rate of a person carrying the mobile computing device based on the Doppler frequency observables and acceleration observables; and

updating, at the physical state estimator, the member of the physical state of the mobile computing device based on the estimated step-size and step-rate.