基于RSSI滤波的改进型泰勒级数室内定位算法

Indoor Localization Algorithm of Improved Taylor Series Based on RSSI Filter

针对基于RSSI测距的无线传感网络室内定位算法中,RSSI值易受环境影响、定位精度差的问题,文中提出了一种RSSI值优化处理、泰勒级数进行改进的定位算法。该算法先将采集的RSSI值进行高斯-卡尔曼滤波处理,然后在不用求模型参数的情况下,引入降维思想求出了测距值,最后对泰勒级数进行改进,并用加权极大似然和改进的泰勒级数相结合的定位算法求出了定位位置。仿真结果表明：经过RSSI滤波的改进型泰勒级数定位算法,优化了RSSI值,提高了测距精度,使得定位算法的定位误差维持在0.9~1.2 m,提高了定位的稳定性和精确度。

Aiming at the problem that the RSSI is susceptible to the environment and the accuracy is poor in the indoor localization of wireless sensor networks,a kind of positioning algorithm is proposed by the optimized RSSI and the improved Taylor series. Firstly,all measured RSSI that the node received are processed by the Gauss- Kalman filtering. Although it does not introduce the model parameters,the value of ranging is got by thought of dimension reduction. Finally,the Taylor series is improved and the position is got by the weighted maximum likelihood estimation method and the improved Taylor series. The simulation shows that the RSSI is optimized and the accuracy of ranging is improved by the indoor localization algorithm of the improved Taylor series based on RSSI filter. It made the accuracy kept between 0. 9 to 1. 2 m,improving the accuracy and stability of the indoor positioning.