情境自适应的RSSI分段异构拟合定位方法

发布时间：2018-03-14 14:19

本文选题：接收信号强度指示　切入点：室内定位　出处：《计算机工程与科学》2017年07期 　论文类型：期刊论文

【摘要】：室内定位在公共安全、健康监护、定位服务等领域具有重要价值,提高定位精度和模型对环境的适应性已经成为室内定位的核心问题。其中通过接收信号强度指示RSSI值来获取距离是比较通用的方法。针对室内复杂环境中传统的对数距离损耗路径模型适用性不高的情况,提出了一种情境自适应的RSSI分段异构拟合定位方法。该方法利用信号在不同应用情境下传播损耗的差异性,将RSSI数据分为多个不同的拟合段,根据RSSI数据的区分特性寻找最优的分段拟合点,并为每个分段选择最优的拟合函数,使得分段数、分段位置和每个分段的拟合函数都适应相应的应用场景,从而实现高精度的RSSI信号拟合。实验结果表明,本文所提出的方法在RSSI拟合精度上均优于传统的单一拟合函数,可明显提高定位算法的精度。
[Abstract]:Indoor positioning is of great value in the fields of public safety, health monitoring, positioning services, etc. Improving positioning accuracy and the adaptability of the model to the environment has become the core problem of indoor positioning. It is a common method to obtain the distance by using the signal strength to indicate the RSSI value, aiming at the traditional method in the complex indoor environment. The applicability of logarithmic distance loss path model is not high, In this paper, a situational adaptive RSSI segmented heterogeneous fitting localization method is proposed, in which the RSSI data are divided into different fitting segments by using the difference of the propagation loss of the signal in different application situations. According to the distinguishing characteristics of RSSI data, the optimal fitting points are found, and the optimal fitting functions are selected for each segment, so that the number of segments, the location of segments and the fitting functions of each segment are adapted to the corresponding application scenarios. The experimental results show that the proposed method is superior to the traditional single fitting function in the accuracy of RSSI fitting and can improve the accuracy of the localization algorithm.
【作者单位】：湘潭大学信息工程学院;中国科学院计算技术研究所;
【基金】：国家自然科学基金(61173066,61572471,61472399) 广东省科技计划项目(2015B010105001) 中科院计算所所创新课题(20156010)
【分类号】：TN92

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