基于插入点法构建Delaunay三角网的室内定位优化算法OA

To address the inefficiency of serial construction of Delaunay triangulations under massive data,this paper proposes a parallel optimization algorithm based on the point insertion method.By evenly dividing the point set and assigning it to multiple threads,a triangle structure containing the attributes ID,IsLock,and Isflag is designed to manage resource competition and network construction status among threads;each thread independently performs point insertion and local triangulation reconstruction,with a locking mechanism ensuring data consistency.Experiments show that for a dataset of 2 600 points,when the number of threads is 6,the parallel speedup reaches 1.69,significantly improving the construction efficiency of large-scale triangulations and making it suitable for processing large-volume indoor positioning data.