Method for measuring dynamic parameters of an aircraft progressing over an airport zone

• US 8,073,584 B2
• Filed: 01/18/2008
• Issued: 12/06/2011
• Est. Priority Date: 01/19/2007
• Status: Expired due to Fees

• Current Assignee: Thales SA
• Original Assignee: Thales SA
• Inventors: Marty, Nicolas, Francois, Gilles, Meunier, Hugues
• Primary Examiner(s): Black, Thomas
• Assistant Examiner(s): Olsen, Lin B
• Application Number:
  US12/016,979
• Publication Number:
  US 20080177427A1
• Time in Patent Office: 1,418 Days
• Field of Search: 701/28, 701/120
• US Class Current: 701/28
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/20061 Hough transform
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/269 using gradient-based methods
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G08G 5/065 Navigation or guidance aids, e.g. for taxiing or rolling

Abstract

The invention relates to a device for measuring dynamic parameters of an aircraft progressing over an airport zone. The aircraft is in the phase of rolling along a traffic lane. The traffic lane comprises ground markings and notably a center line. The device includes at least one means for acquiring images (101), and means (102) for measuring the deviation of the aircraft with respect to the center line on the basis of the acquired images.

Claims

1. A method of measuring dynamic parameters of an aircraft progressing over an airport zone including a runway, said method comprising:

calculating the polar coordinates (r,θ

) of a first straight line supporting a direction of center line, in an acquired image, wherein the calculation of the polar coordinates (r,θ

) of the first straight line comprises the following steps;

detecting straight lines in an acquired image,

grouping said straight lines into sets according to directions of said straight lines,

if several sets of different directions are created, choosing a direction to be followed by the aircraft and calculating the coordinates of a straight line supporting said direction in a first image reference frame, and

calculating an angular deviation XTK between said first straight line and a second straight line supporting the direction of a current trajectory of the aircraft and calculating a lateral deviation XTE between the first straight line and the second straight line,

wherein the step of detecting the straight lines comprises the following steps;

calculating a black and white binary image (I_B) containing solely the contours of the acquired image (I),

applying an algorithm for extracting lines to the black and white binary image (I_B), making it possible to obtain a third grey level image (I_H),

estimating a number of straight lines (n) to be detected in the black and white binary image (I_B),

searching for local maxima in the third image (I_H), and

determining the straight lines exhibiting the largest probability of occurrence in the black and white binary image (I_B), on the basis of the local maxima of the third image (I_H).

2. The method according to claim 1, wherein the step of calculating the angular deviation XTK and lateral deviation XTE comprises the following steps:

calculating two parameters (a₁,b₁) of the first straight line in the image reference frame on the basis of the polar coordinates (r,θ

) of said first straight line,

calculating a first series of points (LP₁) on the basis of the two parameters (a₁,b₁),

projecting, in an airplane reference frame, of the first series of points (LP₁) to obtain a second series of points (LP₂),

calculating two parameters (a₂,b₂) of a second straight line in the airplane reference frame passing through the second series of points (LP₂), and

calculating the angular deviation XTK and lateral deviation XTE on the basis of the two parameters (a₂,b₂).

3. The method according to claim 1, further comprising a preprocessing step that includes the following steps:

applying a filter to the acquired image (I), making it possible to obtain a first less noisy filtered image (I_F),

applying a filter of Gaussian Laplacian type to the first filtered image (I_F), making it possible to obtain a second filtered image (I_L) where the contours are enhanced.

4. The method according to claim 1, further comprising a ground speed estimation and obstacle detection step on a basis of a square encompassing an obstacle that includes the following steps:

acquiring and storing of a first image (I_t-1),

acquiring a second image (I_t),

calculating optical fluxes on the basis of the first image (I_t-1) and of the second image (I_t),

detecting the square encompassing the obstacle, on the basis of the optical fluxes,

estimating the speed on the basis of the square encompassing the obstacle, and

determining the characteristics of the obstacle, comprising a distance between the aircraft and the obstacle D, the azimuth or bearing of the obstacle ρ and

the height of the obstacle H.