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作 者:邹东尧[1] 刘碧微 李晨[1] ZOU Dong-yao LIU Bi-wei LI Chen(College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China)
机构地区:[1]郑州轻工业学院计算机与通信工程学院,河南郑州450001
出 处:《轻工学报》2017年第1期89-96,共8页Journal of Light Industry
基 金:河南省高等学校重点科研项目(15A520109);河南省科技厅科技攻关项目(112102210321);河南省产学研合作项目(122107000022);研究生科技创新基金项目
摘 要:针对基于RSSI定位精度易受外界环境因素干扰这一缺点,提出一种带有加权函数的质心改进定位算法:1)通过对通信距离与测距误差之间关系的分析,采取最优通信距离来提高定位精度;2)根据整体环境的情况对区域进行划分,采用蜂窝正六边形布局信标节点,对划分的各区域进行环境参数最小二乘法拟合;3)利用高斯分布模型对实验数据进行预处理,通过对参考节点的加权运算来保证其可靠性.仿真实验表明,这一改进算法与传统的加权三角形质心定位算法相比,在效率与精度上都有一定的提高.Aiming at the problem that the positioning accuracy based on received signal strength (RSSI) algo- rithm was easily affected by environmental disturbance, an improved weighted centroid positioning algorithm was proposed. First, an optimal length was adopted to improve localization accuracy by analyzing the relation- ship between the communication distance and ranging error. Then, the localization area was divided into several honeycomb sub-regions with the optimal length according to the situation of the overall environment. And these honeycomb sub-regions developed their environmental parameters by the least squares fitting method. Last, RSSI values were filtrated by Gaussian distribution model and weighted arithmetic to ensure the reliability. The simulation results showed the improved algorithm had better efficiency and positioning accuracy, compared with the traditional weighted triangular centroid positioning algorithm.
关 键 词:质心定位算法 RSSI 加权函数 最小二乘法拟合 高斯分布模型
分 类 号:TP397[自动化与计算机技术—计算机应用技术]
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