Coded aperture aided navigation and geolocation systems

• US 8,577,539 B1
• Filed: 01/27/2011
• Issued: 11/05/2013
• Est. Priority Date: 01/27/2010
• Status: Expired due to Fees

• Current Assignee: The United States of America As Represented By The Secretary of Agriculture
• Original Assignee: United States Of America As Represented By The Secretary Of The Air Force
• Inventors: Morrison, Jamie R., Raquet, John F., Veth, Michael J.
• Primary Examiner(s): Black, Thomas
• Assistant Examiner(s): PAYNE, ROBERT T
• Application Number:
  US13/015,272
• Time in Patent Office: 1,013 Days
• Field of Search: 701/28, 701/3, 701/445, 359/850, 250/216, 382/154
• US Class Current: 701/28
• CPC Class Codes: G01C 21/1656 with passive imaging devices, e.g. cameras
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G06T 2200/21 involving computational photography
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30244 Camera pose
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/571 from focus
• CPC Class Codes: G06T 7/73 using feature-based methods

Abstract

A micro air vehicle having a navigation system with a single camera to determine position and attitude of the vehicle using changes the direction to the observed features. The difference between the expected directions to the observed features versus the measured direction to the observed features is used to correct a navigation solution.

Claims

1. A method for measuring the flight path of a micro air vehicle having an inertial navigation system, comprising:

providing a plurality of point spread functions, each function representing an observed source of light at a different predetermined distance;

capturing an image with a single camera lens and a coded aperture;

selecting a pixel from the captured image;

comparing the selected pixel with the plurality of point spread functions;

determining from the comparing step a depth measurement for the selected pixel; and

measuring the flight path of the micro air vehicle using the determined depth measurement for the selected pixel.

2. A method for tracking feature locations along the flight path of a micro air vehicle having an inertial navigation system, comprising:

providing a plurality of point spread functions, each function representing an observed source of light at a different predetermined distance;

capturing an image with a single camera lens and a coded aperture;

selecting a pixel from the captured image;

comparing the selected pixel with the plurality of point spread functions;

determining from the comparing step a depth measurement for the selected pixel; and

measuring the location of tracked features using the determined depth measurement for the selected pixel.

3. The method of claim 2, wherein the measuring step comprises dynamic Bayesian network to provide an estimate of a three dimensional feature location of captured image.

4. The method of claim 3, wherein the estimated three dimensional feature locations include an x location, a y location, and a range from the micro air vehicle.

5. The method of claim 4, wherein the dynamic Bayesian network comprises a recursive estimator.

6. The method of claim 5, wherein the recursive estimator comprises a Kalman filter.

7. The method of claim 4, wherein the Kalman filter determines a change in range with respect to the feature location using the equation as follows:

9. The micro air vehicle of claim 7, wherein the dynamic Bayesian network comprises a recursive estimator.

8. A micro air vehicle comprising:

a plurality of sensors;

a navigation system coupled to the plurality of sensors;

a single camera, including a coded aperture and a fixed focal length lens;

a vision system coupled to the single camera; and

a dynamic Bayesian network coupled to the vision system and the navigation system;

the dynamic Bayesian network providing a plurality of signals to the navigation system, wherein the plurality of signals include updated information regarding a change in the range and direction of the vehicle.

10. The micro air vehicle of claim 8, wherein the recursive estimator comprises a Kalman filter.