改进型PSO算法解算三维测边网平差模型

Improved PSO algorithm to solve the adjustment model of 3D edge measuring network

空间三维测边网属于典型的秩亏自由网。针对目前网平差常用的最小二乘算法存在线性化求导复杂,计算量大等问题,本文基于高精度测距值,以控制点坐标反算距离与观测距离差值之和最小为目标,构成非线性方程组,建立函数模型;考虑到非线性方程组求解方法中智能优化算法无需求导和公式推导简单等优点,引入粒子群(PSO)智能优化算法,并构建改进型PSO算法。研究结果表明,根据本文提出的改进型PSO算法进行平差解算,可保证解算结果的准确性,且该算法较传统PSO算法的寻优速度更快,不仅可为空间三维测边网的解算提供新思路,还可为建立空间三维测边网提供理论支撑。

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 values,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 algorithm 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 proposed 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.