Improved PSO algorithm to solve the adjustment model of 3D edge measuring network
The 3D spatial edge measuring network is a typical rank-loss free network.For the problems of complex linearization derivation and a large amount of computation in the least squares algorithm commonly used in network adjustment at present,this paper,based on the high-precision ranging val-ues,takes the minimum sum of the difference between the inverse distance of control point coordinates and the observed distance as the goal,establishes nonlinear equations and function models.It introduces particle swarm optimization(PSO)intelligent optimization algorithm and constructs an improved PSO al-gorithm by considering such advantages of intelligent optimization algorithm as no derivation and simple formula derivation in solving nonlinear equations.The results show that the improved PSO algorithm pro-posed in the paper can be used to ensure the accuracy of the adjustments,and it has faster optimization speed compared with traditional PSO algorithm,which not only provides a new idea for the solution of 3D spatial edge measuring network,but also provides a theoretical support for the establishment of 3D spatial edge measuring network.
3D edge measuring networkadjustment modelimproved PSO algorithm
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