中文摘要：

室内定位技术的关键在于获取距离参数,在这一问题的研究中运用RSSI信号获得距离参数一直是比较通行的方法.本文针对室内环境复杂,接收RSSI信号存在较大噪声的情况,提出了一种运用卡尔曼滤波器对信号数据进行平滑预处理,随后利用最小二乘法进行分段曲线拟合从而实现定位的算法.通过实验测试结果表明,本文所提出的算法平均定位精度可达0.9 m,与普通数据平均值预处理算法和曲线直接拟合方法相比较,定位精度更高;比直接应用对数距离损耗路径模型的定位算法更为合理可靠,能够在一定程度上满足无线传感器网络室内定位需求.

英文摘要：

The key of Indoor positioning technology is to get the distance parameter.Nowdays,using the RSSI signal to obtain the distance parameter in the study of this issue is a general approach.Considering the complexity of the indoor environment and a large noise in the RSSI signal,an Indoor locating algorithm based on Kalman smoothing filter and piecewise curve fitting is proposed.The experimental result indicated that the accuracy of 0.9m is obtained with the proposed algorithm,and it has higher accuracy of indoor positioning than general data preprocessing and curve fitting directly.Also,it can be more reasonable and reliable compared with the log-distance path loss model.It would be able to meet the needs of indoor positioning in wireless sensor networks.