SPACE RESECTION IN PHOTOGRAMMETRY USING COLLINEARITY CONDITION WITHOUT LINEARISATION

Space resection in photogrammetry involves determining the spatial position and orientation of a photo bayed on image measurements of ground control points that appear in the photo. Since space resection is a nonlinear problem, existing methods involve linearisation of the collinearity condition and the use of on iterative process to determine the final solution using the least-squares method. The process also requires initial approximate values of the unknown parameters, some of which must be estimated by another least-squares solution. This paper presents an optimisation model for space resection with or without redundancy that requires no linearisation, iterations, or initial approximate values. The model, which is nonlinear and noncovex, is solved using advanced Excel-based optimisation software that has been recently developed Application of the model is illustrated using two numerical examples. The proposed model is simple and converges to the global optimal solution very quickly. The presented concept has many potential applications in solving nonlinear land surveying problems without the need for linearisation, and as such should be of interest to surveying anti geomatics engineers.