摘要
无线电传播路径受多种干扰影响,其中建筑物的影响较大。为降低建筑物对无线电传播模型预测精度的影响,GB/T 14617.1—2012《陆地移动业务和固定业务传播特性第1部分:陆地移动业务传播特性》引入了建筑物密度修正因子对模型加以改进,但现有地理信息系统不能提供建筑物密度信息;为此,文章利用卫星图像光谱特性与数字图像分割技术进行建筑物识别并自动提取密度,再将提取的密度值作为修正因子应用到改进的传播模型中。与图像处理阈值法和K-均值法进行对比的结果表明,采用本方法提取建筑物密度速度较快、精度较高,可明显改善现有传播模型在复杂建筑环境下的预测精度。
Radio transmission path has a variety of interference and building on the transmission path is one of great influence factor. In order to reduce building effect on the prediction accuracy of radio propagation model,GB/T 14617. 1—2012 Propagation characteristics in land mobile service and fixed service—Part 1: Propagation characteristics in land mobile service,introduced the building density correction factor. But the geographic information system does not provid the building density. Therefore,this paper proposes a method using satellite image spectrum characteristic and digital image processing technology to identify buildings and automatically extract the building density. We carried out comparative analysis experiments with threshold method and K-Clustering method and the research results show that this method can calculate the density of buildings quickly and accurately from the satellite images,and significantly improve the accuracy of the radio propagation model.
出处
《西华大学学报(自然科学版)》
CAS
2016年第6期97-102,共6页
Journal of Xihua University:Natural Science Edition
基金
国家科技支撑计划"西藏自然科学博物馆基于物联网的信息管理系统关键技术研究及集成示范"(2011BAH26B03)
四川省教育厅重点项目"无线电监测电磁环境自动生成与可视化研究"(14ZA0118)
关键词
建筑密度
无线电传播模型
卫星图像
图像分割
building density
radio propagation model
satellite image
image segmentation