复杂环境下无线传感器网络定位误差分析及鲁棒定位算法研究

项目名称： 复杂环境下无线传感器网络定位误差分析及鲁棒定位算法研究

项目编号： No.61203218

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 自动化学科

项目作者： 郑建颖

作者单位： 苏州大学

项目金额： 25万元

中文摘要： 位置信息是无线传感器网络实现在线实时监测不可或缺的信息，获取位置信息的定位技术是无线传感器网络应用的关键使能技术。传统的无线传感器网络定位技术应用在障碍物多、电磁干扰严重以及动态变化的复杂环境时，存在定位精度低和定位可靠性低等问题。本项目针对复杂环境下无线传感器网络定位问题，从三个方面开展研究工作：①针对测量噪声满足概率统计分布情形，采用测量数据的统计分布特征参数设计概率分布条件下的优化函数；②针对测量噪声分布特征未知但有界情形，采用集员估计理论确定位置的可行区域和上下界以及与之对应的置信参数；③针对测量噪声为异常数据情形，采用均方差中值为特征参量判断和剔除异常数据。通过以上三个方面，分析和确定可以适用于复杂环境、具备抗干扰能力的无线传感器网络鲁棒定位算法，从而构建复杂环境下无线传感器网络实现鲁棒定位的基础理论，完善无线传感器网络定位方法体系，为无线传感器网络在复杂环境中的应用奠定基础。

中文关键词： 无线传感器网络；定位误差；鲁棒定位算法；RSSI测距；

英文摘要： In wireless sensor networks, location information is viewed as one of the most significant contexts. As a result of the demand of context-aware applications, determining the location for sensor nodes becomes very necessary and important. Traditional localization approaches are not suitable for complex environments due to various reasons, for example, the low accuracy and low reliability. Therefore, this project will discuss the localization problem in complex environments from the following three aspects. First of all, when statistics for the measurement data meet the probability distribution, the optimal function will be designed based on the statistical distribution of the characteristic parameters of measurement data. Secondly, when the measurement noise is unknown but bounded, the set-membership estimation theory will be used to determine the range of location of sensor nodes and their corresponding confidence. Finally, when the measurement data is extremely large or seen as outlier of measurements, the method of least median of squares will be used to deal with outlier measurements. Based on the three aspects above, we aim to analyze and establish robust localization alogirithms, with the ability to fight interference and suitable for complex environments. Thus, we shall build the basic theory of robust loc

英文关键词： Wireless Sensor Networks；Localization Error；Robust Localization Algorithm；RSSI Ranging；