Review of Nonlinear Adjustment Algorithms

Abstract

The nonlinear models exist in surveying adjustment widely. In surveying adjustment, the theoretical basis of the data processing method is the linear least square method. Usually dealing with the nonlinear models is linearization. In modern surveying and mapping technology, the nonlinear strength of most nonlinear models is strong. Therefore, the high-precision measurements cannot be obtained by linearization. So it is urgent to study the theory of the nonlinear data processing method. In this paper, we introduce several algorithms for solving nonlinear adjustment model: Newton iterative method, gauss - Newton method, and the improved gauss - Newton method, damped least square method, genetic algorithm and simulated annealing algorithm, homotopy algorithm.