基于MEMS传感器的室内个人定位技术研究

项目名称： 基于MEMS传感器的室内个人定位技术研究

项目编号： No.61301021

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 王宇

作者单位： 南京理工大学

项目金额： 27万元

中文摘要： 采用MEMS技术制造的传感器（如陀螺、加速度计、地磁传感器、气压计等）构建多传感器的个人定位系统是室内定位领域的研究热点。目前，室内个人定位系统存在的问题是体积、成本、功耗与精度的矛盾。采用MEMS传感器可以满足体积、成本和功耗的要求，但是精度受到限制。本项目提出一种带有支持向量机辅助的多MEMS传感器组合的室内个人定位技术以解决长时间定位精度问题。首先，针对MEMS传感器误差模型的不准确问题，利用支持向量机的模型逼近能力，建立MEMS传感器的在线误差模型，提高多传感器信息融合模型的准确度；其次，针对多传感器带来的信息多元化，设计一种信息匹配方式智能切换方法，以实现信息融合的自适应最优解；最后，基于非线性滤波理论和准确的信息融合模型，设计适合室内环境的多传感器定位误差非线性滤波估计方法。提高室内封闭环境下个人定位系统的精确定位能力和环境适应能力，具有重要的理论意义和工程实用价值。

中文关键词： 个人定位系统；MEMS传感器；支持向量机；信息融合；

英文摘要： The multi-sensor personal positioning system built by MEMS technology (such as gyroscopes, accelerometers, the geomagnetic sensor, the barometer, etc.) has become a hot issue in the research field of indoor positioning. At present, the problem of the indoor personal positioning systems is the conflict among size, cost, power consumption and accuracy. MEMS sensors could be applied to meet the requirements of size, cost and power consumption, but the accuracy is limited. Therefore, a multi-MEMS sensor personal indoor positioning technology assisted with support vector machine is proposed in this project to solve the problem of long-term positioning accuracy. First, targeting at the inaccurate MEMS sensor error model, MEMS sensor online error model is established with the support vector machine model approximation ability, and the online error compensation filter is constructed to improve the accuracy of the multi-sensor data fusion model; Second, to deal with the information diversity caused by using multi-sensor unit, a intelligent switching method of information matching is designed to achieve the optimal solution of the adaptive data fusion; Finally, based on the nonlinear filtering theory and accurate data fusion model, the multi-sensor positioning nonlinear error estimation method is designed for indoor envir

英文关键词： personal positioning system；MEMS sensor；support vector machine；information fusion；