The traditional methods of DEM matching without control points are based on least squares matching and their pull-in-range are poor. Aimed at this problem

a new method combining genetic algorithm with least squares matching was proposed by this paper . In order to avoid the scaling coefficient converge to the false extreme value 0 easily when using genetic matching method based on traditional matching model

this paper established a new matching model using distance grading. Accordingly

this paper designed the matching procedures of the method combining genetic algorithm with least squares matching. Results from experiments with simulated data and actual data show that the new method proposed by the paper keeps the least squares matching's merit of higher accuracy and the genetic algorithm's merit of larger pull-in-range and has better robustness and higher converging efficiency.