Dual disimilar sensing object detection and targeting system
First Claim
1. A method of performing object detection within a collision warning and countermeasure system comprising:
- generating an object detection signal;
generating an image detection signal;
determining at least one center-of-reflection and at least one center-of-intensity in response to said object detection signal and said image detection signal;
associating said at least one center-of-intensity with said at least one center-of-reflection;
determining difference between said at least one center-of-reflection and said at least one center-of-intensity for a plurality of frames and generating a sensor difference signal; and
classifying at least one object in response to said sensor difference signal.
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Abstract
A method of performing object detection within a collision warning and countermeasure system (10) is provided. The method includes generating an object detection signal and generating an image detection signal. Centers-of-reflection (56) and centers-of-intensity (59) are determined in response to the object detection signal and the image detection signal. The centers-of-intensity (59) are associated with the center-of-reflection (56). Differences between the centers-of-reflection (56) and the centroids (62) are determined for a plurality of frames (65) and a sensor difference signal is generated. An object (36) is classified in response to the sensor difference signal.
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Citations
20 Claims
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1. A method of performing object detection within a collision warning and countermeasure system comprising:
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generating an object detection signal;
generating an image detection signal;
determining at least one center-of-reflection and at least one center-of-intensity in response to said object detection signal and said image detection signal;
associating said at least one center-of-intensity with said at least one center-of-reflection;
determining difference between said at least one center-of-reflection and said at least one center-of-intensity for a plurality of frames and generating a sensor difference signal; and
classifying at least one object in response to said sensor difference signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
performing a perspective transform of said world coordinates into image coordinates; and
determining said at least one center-of-reflection in response to said image coordinates.
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8. A method as in claim 1 further comprising determining at least one centroid in response to said at least one center-of-intensity.
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9. A method as in claim 8 wherein determining at least one centroid comprises determining a current frame region-of-interest in response to a prior frame region-of-interest.
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10. A method as in claim 8 wherein determining at least one centroid comprises adjusting size of a current frame region-of-interest in response to a prior frame region-of-interest and in response to said sensor difference signal.
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11. A method as in claim 8 wherein determining at least one centroid comprises:
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determining whether an object is a false object or a ghost object and generating an error signal; and
determining whether to use said sensor difference signal when determining a subsequent region-of-interest in response to said error signal.
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12. A method as in claim 8 further comprising:
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determining a first set of vectors between said at least one center-of-reflection and said at least one centroid for a prior frame region-of-interest;
determining a second set of vectors between said at least one center-of-reflection and at least one updated centroid for a current frame region-of-interest; and
generating said sensor difference signal in response to said first set of vectors and said second set of vectors.
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13. A method as in claim 12 wherein generating said sensor difference signal comprises averaging differences between said second set of vectors and said first set of vectors.
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14. A method as in claim 1 wherein generating said sensor difference signal comprises accounting for errors between said at least one center-of-reflection and said at least one center-of-intensity.
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15. A collision warning and countermeasure system for an automotive vehicle comprising:
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at least one object detection sensor generating an object detection signal;
at least one image generating sensor generating an image detection signal; and
a controller electrically coupled to said at least one object detection sensor and said at least one image generating sensor, said controller determining at least one center-of-reflection and at least one center-of-intensity in response to said object detection signal and said image detection signal, associating said at least one center-of-intensity with said at least one center-of-reflection, determining difference between said at least one center-of-reflection and said at least one center-of-intensity for a plurality of frames and generating a sensor difference signal, and classifying at least one object in response to said sensor difference signal. - View Dependent Claims (16, 17, 18, 19)
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20. A method of performing object detection within a collision warning and countermeasure system comprising:
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generating an object detection signal by performing an upramp sweep and a downramp sweep;
generating an image detection signal;
determining at least one center-of-reflection and at least one center-of-intensity in response to said object detection signal and said image detection signal;
associating said at least one center-of-intensity with said at least one center-of-reflection;
determining difference between said at least one center-of-reflection and said at least one center-of-intensity for a plurality of frames and generating a sensor difference signal;
determining at least one centroid in response to said center-of-intensity;
determining a set of vectors between said at least one center-of-reflection and said at least one centroid;
comparing differences between said set of vectors and an average distance parameter to determine an updated average distance parameter;
determining a subsequent set of regions-of-interest in response to said updated average distance parameter;
determining updated centroids in response to said subsequent set of regions-of-interest; and
classifying and tracking at least one object in response to said updated centroids.
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Specification