초록 ▼

A deployment method maintains a cluster of subsatellites within a rigid formation relative to and orbiting about a real or fictitious center satellite that in turn orbits the earth in a frozen inclined eccentric reference orbit by determining the subsatellite reference orbits of the each of the subs

A deployment method maintains a cluster of subsatellites within a rigid formation relative to and orbiting about a real or fictitious center satellite that in turn orbits the earth in a frozen inclined eccentric reference orbit by determining the subsatellite reference orbits of the each of the subsatellites based upon position and velocity vectors of the center satellite. The determined subsatellite reference orbits can then be maintained through fuel efficient microthrusting so as to maintain the rigid formation for coherently combining communication signals within a very large sparse antenna array formed by the cluster having improved beam directionality for improved signal communications.

대표청구항 ▼

A deployment method maintains a cluster of subsatellites within a rigid formation relative to and orbiting about a real or fictitious center satellite that in turn orbits the earth in a frozen inclined eccentric reference orbit by determining the subsatellite reference orbits of the each of the subs

A deployment method maintains a cluster of subsatellites within a rigid formation relative to and orbiting about a real or fictitious center satellite that in turn orbits the earth in a frozen inclined eccentric reference orbit by determining the subsatellite reference orbits of the each of the subsatellites based upon position and velocity vectors of the center satellite. The determined subsatellite reference orbits can then be maintained through fuel efficient microthrusting so as to maintain the rigid formation for coherently combining communication signals within a very large sparse antenna array formed by the cluster having improved beam directionality for improved signal communications. from adjacent sets of said coordinates.9. The system of claim 5 wherein said processor divides said curved feature into four quadrants and defines four groups by sets of said coordinates corresponding to each of said quadrants.10. The system of claim 1 wherein said image acquisition device produces multiple spaced, incremental scans in two orthogonal directions.11. The system of claim 10 wherein said processor determines an averaged radius of curvature by averaging the radius of curvature results for both said orthogonal directions.12. A method for determining the radius of curvature of a two-dimensional curved feature, the method comprising: providing a target with a curved feature;producing multiple spaced, incremental one-dimensional scans in at least one direction across said curved feature;obtaining n sets of coordinates corresponding to peaks of intensities from said scans;choosing at least three sets of said coordinates to define at least one group;fitting each set of said coordinates from each said group to an equation for a circle; anddetermining a radius of curvature by solving each equation simultaneously.13. The method of claim 12 wherein said radius of curvature “R” is determined utilizing the following formula:R 2=(x−h)2+(y−k)2where the symbols “x” and “y” correspond to a set of said coordinates and where the symbols “h” and “k” correspond to a center of curvature. 14. The method of claim 12 further comprising: determining a diameter using said radius of curvature.15. The method of claim 12 further comprising:determining a circularity by calculating and averaging the variance in at least two radius of curvature results.16. The method of claim 12 wherein said curved feature is closed.17. The method of claim 12 wherein said curved feature is open.18. The method of claim 16 wherein:sixteen spaced, incremental one-dimensional scans are produced across said curved feature;four of said scans are chosen centered about, but not including a scan corresponding to the set of coordinates with a maximum spacial distance therebetween;eight sets of said coordinates that correspond to said four chosen scans are determined; andtwo groups corresponding to a first side of said curved feature and two groups corresponding to a second side of said curved feature are defined by choosing from said sets of Cartesian coordinates corresponding to said first side and said second side of said curved feature.19. The method of claim 12 wherein said groups are chosen from adjacent sets of said coordinates.20. The method of claim 16 wherein:said curved feature is divided into four quadrants and four groups are defined by sets of said coordinates corresponding to each of said quadrants.21. The method of claim 12 wherein said scans are produced in two orthogonal directions.22. The method of claim 21 wherein an averaged radius of curvature is determined by averaging the radius of curvature results for both said orthogonal directions.23. A storage medium encoded with machine-readable computer program code for determining a radius of curvature of a two-dimensional curved feature, the storage medium including instructions for causing a processor to implement a method comprising: producing multiple spaced, incremental one-dimensional scans in at least one direction across a target with a curved feature;obtaining n sets of coordinates corresponding to peaks of intensities from said scans; choosing at least three sets of said coordinates to define at least one group;fitting each set of said coordinates from each said group to an equation for a circle; anddetermining a radius of curvature by solving each equation simultaneously.24. The storage medium of claim 23 wherein said radius of curvature “R” is determined utilizing the following formula:R 2=(x−h)2+(y−k)2where the symbols “x” and “y” correspond to a set of said coordinates and where the symbols “h” and “k” correspond to a center of curvature. 25. The storage medium of claim 23 further comprising instructions for causing the processor to implement:determining a diameter using said radius of curvature.26. The storage medium of claim 23 further comprising instructions for causing the processor to implement:determining a circularity by calculating and averaging the variance in at least two radius of curvature results.27. The storage medium of claim 23 wherein said curved feature is closed.28. The storage medium of claim 23 wherein said curved feature is open circular.29. The storage medium of claim 27 wherein:sixteen spaced, incremental one-dimensional scans are produced across said curved feature;four of said scans are chosen centered about, but not including a scan corresponding to the set of coordinates with a maximum spacial distance there between;eight sets of said coordinates that correspond to said four chosen scans are determined; andtwo groups corresponding to a first side of said curved feature and two groups corresponding to a second side of said curved feature are defined by choosing from said sets of coordinates corresponding to said first side and said second side of said curved feature.30. The storage medium of claim 23 wherein said groups are chosen from adjacent sets of said coordinates.31. The storage medium of claim 27 wherein:said curved feature is divided into four quadrants and four groups are defined by sets of said n coordinates corresponding to each of said quadrants.32. The storage medium of claim 23 wherein said scans are produced in two orthogonal directions.33. The storage medium of claim 32 wherein an averaged radius of curvature is determined by averaging the radius of curvature results for both said orthogonal directions.34. The system of claim 1 wherein said processor processes a plurality of groups and a center is chosen by averaging the center determined from each group.35. The system of claim 34 wherein said processor determines edge-roughness by processing the radius from the center to a plurality of points on the edge of the curved feature.36. The system of claim 1 wherein the curved feature is a contact hole formed in an integrated circuit device and the image acquisition device obtains images from a plurality of levels in the via.37. The system of claim 36 wherein the processor determines a center at each of the plurality of levels.38. The method of claim 12 further comprising determining a center for the curved feature by averaging the center from each of a plurality of groups.39. The method of claim 38 further comprising determining the edge-roughness of the curved feature by measuring the radius from the center to a plurality of points on the edge of the curved feature.40. The method of claim 12 wherein the curved feature is a contact hole formed in an integrated circuit device and the contact hole is scanned at a plurality of levels.41. The method of claim 40 further comprising determining the center in each level of the contact hole which is scanned.42. The storage medium of claim 23 further comprising instructions for the processor to implement determining a center for the curved feature by averaging the center from each of a plurality of groups.43. The storage medium of claim 42 further comprising instructions for the processor to implement determining the edge-roughness of the curved feature by measuring the radius from the center to a plurality of points on the edge of the curved feature.44. The storage medium of claim 23 further comprising instructions for the processor to implement scanning in images from a plurality of level s in a contact hole.45. The storage medium of claim 44 further comprising instructions for the processor to implement determining the center in each level of the contact hole in which an image is scanned.