초록 ▼

A method for inferring precise sensor attitude information in a tracking sensor system begins with storing at a first time a reference image in a memory associated with tracking sensor. Next, the method includes sensing it a second time second image. The sensed image comprises a plurality of sensed

A method for inferring precise sensor attitude information in a tracking sensor system begins with storing at a first time a reference image in a memory associated with tracking sensor. Next, the method includes sensing it a second time second image. The sensed image comprises a plurality of sensed feature locations. The method further includes determining the position of the tracking sensor at the second time relative to its position at the first time and then forming a correlation between the sensed feature locations and the predetermined feature locations as a function of the relative position. The method results in an estimation of a tracking sensor pose that is calculated as a function of the correlation. Because the method is primarily computational, implementation requires no new hardware in a tracking sensor system other than that which may be required to provide additional computational capacity.

대표청구항 ▼

[ What is claimed is:] [1.] A method for inferring precise sensor attitude information in a tracking sensor system, comprising the steps of:sensing at a first time a reference image using the tracking sensor to provide signals representing reference feature locations in the reference image;storing i

[ What is claimed is:] [1.] A method for inferring precise sensor attitude information in a tracking sensor system, comprising the steps of:sensing at a first time a reference image using the tracking sensor to provide signals representing reference feature locations in the reference image;storing in a memory signals representing said reference feature locations;sensing at a second time a second image using the tracking sensor to provide signals representing second time sensed feature locations;determining the relative translational position of the tracking sensor at said second time relative to the sensor position at said first time without using any information extracted from said second image; anddetermining the pose of said tracking sensor by using mathematical steps to form a correlation between a plurality of said second time sensed feature locations in said second image and a plurality of said reference feature locations in said reference image, wherein determining the sensor nose comprises using said relative translational position to improve the conditioning of at least one mathematical step; reby said pose includes the precise sensor attitude information.