中文摘要：

为了改善以往室内接收信号强度指示定位方法精度不高的问题，提出了一种运用单形采样和协方差修正策略的尺度优化迭代无迹卡尔曼滤波器（SIUKF），对节点坐标和信道衰减参数进行联合估计解算，从而实现对目标位置获取的改进定位方法．该方法针对室内环境复杂、干扰因素较多、接收RSSI信号存在较大的噪声的情况，使用kernel平滑法对原始数据进行预处理校正，并将定位问题转换为非线性状态最优化估计问题．实验和仿真结果表明，与扩展卡尔曼滤波（EKF）和标准无迹卡尔曼滤波法（UKF）相比，采用具有更高非线性近似精度的SIUKF解决接收信号强度指示室内定位估计问题，可以较好地提高目标位置估计精度，且计算复杂度适中，稳定性更好，平均定位精度可达0．65m，能满足室内定位的需求．

英文摘要：

To improve the precision of received signal strength indicator （RSSI）wireless localization in traditional indoor positioning technology, using simplex sampling and covariance correction, a method of coordinate position and channel parameter simultaneous estimation is presented based on iterated unscent- ed Kalman filter （IUKF） algorithm. Due to the complexity of indoor environment, there exists a big noise in RSSI signal, so the raw data is calibrated by using kernel smoother. The RSSI localization problem is conveyed into the optimal estimation problem of nonlinear equations. Simulation indicates that SIUKF al- gorithm has higher estimation accuracy compared with extended Kalman filter （EKF） and unscented Kal- man filter （UKF）. It shows strong robustness, and the computational complexity is appropriated. The ac- curacy up to O. 65m is obtained with the proposed method and can meet the needs of indoor positioning.