NAVIGATION BASED ON AT LEAST ONE SENSOR AND A THREE DIMENSIONAL MAP

• US 20150292887A1
• Filed: 04/14/2015
• Published: 10/15/2015
• Est. Priority Date: 04/14/2014
• Status: Active Grant

• Current Assignee: Maxar International Sweden AB (Galileo Parent, Inc.)
• Original Assignee: Saab Vricon System AB (Galileo Parent, Inc.)
• Inventors: Haglund, Leif, Bejeryd, Johan, Carlbom, Per, Sjanic, Zoran
• Granted Patent: US 9,483,842 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/005 with correlation of navigation data from several sources, e.g. map or contour matching G01C21/30 takes precedence
• CPC Class Codes: G01S 19/13 Receivers
• CPC Class Codes: G01S 19/49 whereby the further system is an inertial position system, e.g. loosely-coupled
• CPC Class Codes: G05D 1/08 Control of attitude, i.e. control of roll, pitch, or yaw
• CPC Class Codes: G05D 1/0808 specially adapted for aircraft
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10032 Satellite or aerial image; Remote sensing
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/30244 Camera pose
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/32 using correlation-based methods
• CPC Class Codes: G06T 7/74 involving reference images or patches

Abstract

The invention relates to a method for navigation of an aerial vehicle. The method comprises providing a sensor image from an aerial vehicle sensor. The method also comprises to repeatedly, until at least one predetermined criterion is reached, perform the step of setting input data, where the input data comprises information related to pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle, the step of providing a two-dimensional image from a database based on the input data, where the database comprises three-dimensional geo-referenced information of the environment, and the step of comparing the sensor image and the two dimensional image from the database. The method further comprises using the input data for which the two images correspond best to each other for determining at least one of the following quantities pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle.

Claims

1. A method for navigation of an aerial vehicle, the method comprising providing a sensor image from an aerial vehicle sensor and repeatedly, until at least one predetermined criterion is reached, performing the steps:

setting input data comprising information related to pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle;

providing a two-dimensional image from a database based on the input data, where the database comprises three-dimensional geo-referenced information of the environment,

comparing the sensor image and the two dimensional image from the database; and

using the input data for which the two images correspond best to each other for determining at least one of the following quantities pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle.

2. The method according to claim 1, where the determined at least one quantity comprises the three-dimensional position of the aerial vehicle.

3. The method according to claim 2, further comprising the steps of:

determining a three-dimensional position of the aerial vehicle based on a global navigation satellite system, GNSS; and

comparing the determined three-dimensional position of the aerial vehicle based on the GNSS with the determined three-dimensional position of the aerial vehicle where the input data for which the two images correspond best to each other has been used, so as to determine whether the GNSS is providing reliable data.

4. The method according to claim 1, where the step of comparing the sensor image and the two dimensional image from the database comprises calculating a similarity measure between the two images.

5. The method according to claim 4, where the two images which correspond best to each other are the two images which have the highest calculated similarity measure between the two images.

6. The method according to claim 4, where calculating a similarity measure between the two images comprises calculating a cross-correlation between the two images, preferably a normalised cross-correlation.

7. The method according to claim 1, where the step of providing a two-dimensional image from a database based on the input data comprises providing the two-dimensional image from the database in such a way that it is projected onto the field of view of the aerial vehicle sensor, where it is assumed that the aerial vehicle has its pitch angle, roll angle, yaw angle and three-dimensional position according to the input data, wherein said projection onto the field of view of the aerial vehicle sensor preferably is performed in such a way that said two-dimensional image from the database will have the same or at least basically the same orientation as said sensor image.

8. The method according to claim 1, wherein the setting of the input data is updated in each step in such a way as to find the best correspondence between the two images.

9. The method according to claim 6, wherein a normalised cross-correlation is calculated and the value of the normalised cross-correlation for the two images which correspond best to each other is used for calculating an uncertainty of the least one quantity.

10. The method according to claim 1, where the predetermined criterion is that the steps are repeated a predetermined number of times and/or that the best correspondence between the two images which has been achieved so far converges.

11. The method according to claim 1, where an uncertainty in the three-dimensional geo-referenced information of the environment is used to calculate an uncertainty of the at least one quantity.

12. The method according to claim 1, where sensor images from different aerial vehicle sensors are provided and the method is performed independently for the sensor image of each such aerial vehicle sensor, whereupon the determined at least one quantity is a combination of the determined at least one quantity for each independently performed method.

13. The method according to claim 12, where the combination of the determined at least one quantity for each independently performed method is based on the reliability and/or accuracy of the sensors from which the sensor images are provided.

14. The method according to claim 1, where an initial setting of the input data comprises information related to assumed real values for the aerial vehicle, especially information related to assumed real values for the pitch angle, the roll angle, the yaw angle and the three-dimensional position of the aerial vehicle.

15. The method according to claim 1, where the input data comprises pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle, and where the determined at least one quantity is the corresponding at least one quantity of the input data for which the two images correspond best to each other.

16. A system for navigation of an aerial vehicle, the system comprising

a database containing three-dimensional geo-referenced information of the environment,

at least one aerial vehicle sensor providing a sensor image, and

a processing unit configured to:

receive the sensor image, to set input data comprising information related to pitch angle, roll angle, yaw angle and a three-dimensional position of the aerial vehicle,

provide two-dimensional images from the database based on the input data,

compare the sensor image with a two-dimensional images from the database, to decide which of the two-dimensional images corresponds best to the sensor image,

determine at least one of the following quantities pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle based on the input data for which the best correspondence was achieved between one of the two-dimensional images and the sensor image, and

communicate said at least one quantity.

17. The system according to claim 16, further comprising a steering unit for the aerial vehicle, the steering unit being arranged to receive the communicated said at least one quantity.

18. The system according to claim 16, where the determined at least one quantity comprises the three-dimensional position of the aerial vehicle.

19. The system according to claim 16, where the processing unit is arranged to repeatedly perform the processes of setting input data, providing a two-dimensional image, and comparing the two-dimensional image with the sensor image until at least one predetermined criterion is reached.

20. The system according to claim 16, comprising several aerial vehicle sensors, each providing a sensor image, where the processing unit is further arranged to perform independently for each sensor image said processes of receiving sensor images, setting input data, providing two-dimensional images, comparing images, and determining at least one of the following quantities pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle, and where the processing unit further is arranged to determine a combined at least one quantity based on the corresponding determined at least one quantity for each sensor image.

21. The system according to claim 16, further comprising means for determining a three-dimensional position of the aerial vehicle based on a global navigation satellite system, GNSS, and wherein the processing unit is arranged to determine at least the three-dimensional position of the aerial vehicle based on the input data for which the best correspondence was achieved between one of the two-dimensional images and the sensor image, and wherein the processing unit further is arranged to compare the determined three-dimensional position of the aerial vehicle based on the GNSS with said determined three-dimensional position of the aerial vehicle based on the input data for which the best correspondence was achieved between one of the two-dimensional images and the sensor image, and wherein the processing unit further is arranged to determine whether the GNSS is providing reliable data based on said comparison of the determined three-dimensional positions.

22. The system according to claim 16, where the processing unit is further arranged to calculate an uncertainty for the determined at least one quantity based on an uncertainty in the three-dimensional geo-referenced information of the environment.

23. A non-transitory computer program comprising a program code for navigation of an aerial vehicle, the computer program comprising the step of providing a sensor image from an aerial vehicle sensor and repeatedly, until at least one predetermined criterion is reached, performing the steps:

setting input data comprising information related to pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle;

providing a two-dimensional image from a database based on the input data, where the database comprises three-dimensional geo-referenced information of the environment;

comparing the sensor image and the two dimensional image from the database; and

using the input data for which the two images correspond best to each other for determining at least one of the following quantities pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle.

24. Computer program product comprising a program code stored on a non-transitory computer readable media for navigation of an aerial vehicle, comprising the step of providing a sensor image from an aerial vehicle sensor and repeatedly, until at least one predetermined criterion is reached, performing the steps:

setting input data comprising information related to pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle;

providing a two-dimensional image from a database based on the input data, where the database comprises three-dimensional geo-referenced information of the environment;

comparing the sensor image and the two dimensional image from the database; and

using the input data for which the two images correspond best to each other for determining at least one of the following quantities pitch angle, roll angle, yaw angle and three-dimensional position of the aerial vehicle.