基于几何覆盖率算法的传感器覆盖优化策略

区域覆盖率是传感器网络节点调度过程中的一项重要指标。现有的栅格统计法会因为栅格大小划分而导致计算精度与计算速度的矛盾，不利于大面积传感器网络的规划调度。针对栅格统计法的不足，提出了一种基于圆弧并面积算法的几何覆盖率算法，这种算法使用简单的几何运算代替栅格统计法中大量的循环统计，是一种快速且精确的算法。结合遗传算法，并利用几何覆盖率算法设计判冗余机制，形成了传感器网络覆盖优化策略，仿真结果表明利用几何覆盖率算法的优化策略能有效提高规划效率和计算精度。

A Optimized Strategy of Sensor Coverage based on Geometry Coverage Algorithm

Regional coverage is an important index of sensor network scheduling. The existing grid statistics can lead to a contradiction between the calculation accuracy and the calculation speed because of the grid size, it is not conducive to the planning and scheduling of large area sensor networks. In view of the deficiency of grid statistics, a new geometric coverage algorithm based on arcs union algorithm is proposed. It is a fast and accurate algorithm, which uses simple geometric operations to replace a large number of circular in grid statistics. This paper combines genetic algorithm a redundant mechanism based on geometric coverage algorithm to form a sensor network coverage optimization strategy. The simulation results show that this optimization strategy can effectively improve the planning speed and calculate accuracy.