Method for estimating unknown parameters for a vehicle object detection system

• US 20070055446A1
• Filed: 09/02/2005
• Published: 03/08/2007
• Est. Priority Date: 09/02/2005
• Status: Active Grant

• Current Assignee: Aptiv Technologies Limited (Aptiv PLC)
• Original Assignee: Delphi Technologies, Inc. (Aptiv PLC)
• Inventors: Schwartz, David, Schiffmann, Jan
• Granted Patent: US 7,706,978 B2
• Time in Patent Office: Days
• US Class Current: 701/301
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 2013/9322 using additional data, e.g. driver condition, road state or weather data
• CPC Class Codes: G01S 2013/93271 in the front of the vehicles
• CPC Class Codes: G01S 7/4026 Antenna boresight
• CPC Class Codes: G01S 7/403 in azimuth, i.e. in the horizontal plane
• CPC Class Codes: G01S 7/4034 in elevation, i.e. in the vertical plane
• CPC Class Codes: G01S 7/4091 during normal radar operation

Abstract

A method for estimating unknown parameters (pan angle (ψ), instantaneous tilt angle (τ) and road geometry of an upcoming road segment) for a vehicle object detection system. The vehicle object detection system is preferably a forward looking, radar-cued vision system having a camera, a radar sensor and an processing unit. The method first estimates the pan angle (ψ), then corrects the coordinates from a radar track so that pan angle (ψ) can be treated as zero, and finally solves a least squares problem that determines best estimates for instantaneous tilt angle (τ) and road geometry. Estimating these parameters enables the vehicle object detection system to identify, interpret and locate objects in a more accurate and efficient manner.

Claims

1. A method for estimating unknown parameters for a vehicle object detection system, comprising the steps of:

(a) generating a vision track from data provided by a camera;

(b) generating a radar track from data provided by a radar sensor;

(c) generating a matched pair from said vision and radar tracks; and

(d) estimating a camera pan angle (ψ

) and at least one of an instantaneous tilt angle (τ

) and road geometry, wherein said estimates minimize the alignment error between said matched pair.

2. The method of claim 1, wherein a vertical curvature (c) of an upcoming road segment represents said road geometry.

3. The method of claim 1, wherein said vision track is provided in terms of a two-dimensional Cartesian coordinate system (pixels (p, q)), and said radar track is provided in terms of a two-dimensional polar coordinate system (range and azimuth angle (R, θ

)).

4. The method of claim 1, wherein said pan angle (ψ

) estimate is filtered with a low-pass filter to provide a filtered pan angle estimate.

5. The method of claim 1, wherein step (d) further includes solving an optimization problem that minimizes the 3-D world coordinate alignment error between said matched pair.

6. The method of claim 5, wherein step (d) further includes utilizing a least squares problem.

7. The method of claim 1, wherein step (d) further includes linearizing at least one trigonometric equation about a nominal tilt angle (τ

₀) so that said trigonometric equation becomes a linear equation.

8. The method of claim 7, wherein step (d) further includes removing any negligible terms and manipulating said linear equation so that a single linear equation is provided for said matched pair.

9. The method of claim 1, wherein step (d) estimates both said instantaneous tilt angle (τ

) and said road geometry.

10. The method of claim 1, wherein step (d) further includes using said estimated camera pan angle (ψ

) and said radar track to provide a pan corrected matched pair having a radar track that has been generally corrected for errors attributable to a camera pan angle.

11. The method of claim 10, wherein step (d) further includes using said pan corrected matched pair to estimate at least one of an instantaneous tilt angle (τ

) and road geometry.

12. The method of claim 1, wherein the vehicle object detection system is a forward looking, radar-cued vision system.

13. A method for estimating unknown parameters for a vehicle object detection system, comprising the steps of:

(a) generating a vision track from data provided by a camera;

(b) generating a radar track from data provided by a radar sensor;

(c) generating a matched pair from said vision and radar tracks;

(d) estimating a camera pan angle (ψ

) that best fits said matched pair;

(e) using said estimated camera pan angle (ψ

) and said radar track to provide a pan corrected matched pair(s) having a radar track that has been generally corrected for errors attributable to a camera pan angle; and

(f) using said pan corrected matched pair(s) to estimate at least one of an instantaneous tilt angle (τ

) and road geometry.

14. A method for estimating an unknown pan angle, instantaneous tilt angle and vertical curvature for a vehicle object detection system, comprising the steps of:

(a) generating a plurality of vision tracks from data provided by a camera;

(b) generating a plurality of radar tracks from data provided by a radar sensor;

(c) generating a plurality of matched pairs from said vision and radar tracks;

(d) estimating a camera pan angle (ψ

) that best fits said plurality of matched pairs;

(e) using said estimated camera pan angle (ψ

) and said plurality of radar tracks to provide a plurality of pan corrected matched pairs each having a radar track that has been generally corrected for errors attributable to a camera pan angle;

(f) using said plurality of pan corrected matched pairs to generate a least squares problem, said least squares problem treats said estimated camera pan angle (ψ

) as 0;

(g) linearizing one or more trigonometric equations about a nominal tilt angle (τ

₀) so that said trigonometric equations become linear equations; and

(h) solving said least squares problem to estimate both said instantaneous tilt angle (τ

) and said vertical curvature (c).