Abstract
We present a rigorous geometric analysis of the computation of the global positions of an airborne video camera and ground based objects using aerial images of known landmarks. This has also been known as the perspective-n-point (PnP) problem. A robust Hough transform-like method, facilitated by a class of CORDIC-structured computations is developed to find the camera position followed by a method of computing the position of a ground object from images of that object and three known landmarks. The results enable fast and effective visual terrain navigation of aerial surveillance systems when the global positioning and inertial navigation sensors become faulty, inaccurate, or dysfunctional. These new hardware implementable algorithms can also be used with MEMS based INS sensors through a multisensory fusion process.
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