Optimal uav localisation in vision based navigation systems

Optimal determination of a UAV using a vision-based system to match images against a database is an important problem. It can be reformulated to the problem of using multiregion scene registration to match areas of a noisy and distorted image to a geo-referenced image. Under the assumptions that the mapping between sensed and geo-referenced images preserves gradients of straight lines cross mapping points on images and registration errors are all Gaussian distributed, we derive a two-stage weighted linear least square algorithm which localises the UAV optimally. Performance of the proposed algorithm is demonstrated via Monte Carlo multiple runs along with those available in literature.