融合RSSI测距定位的室内PDR算法

在室内定位系统中，针对RSSI测距定位系统接收到的信号会因环境的不确定性出现不可预测的随机变化和行人航迹推算(PDR)定位系统漂移误差长时间的累积效果，提出融合RSSI测距定位的室内行人航迹推算算法，以扩展卡尔曼滤波器实现两者定位信息的融合，获得系统的最优定位结果。仿真结果表明，该融合定位算法的平均定位误差约为0.83205 m,范围维持在0.51948 m～1.13529 m内，并在定位稳定性方面表现出良好的性能，验证了该方法的合理性和有效性。

Indoor PDR Algorithm Based on RSSI Ranging Positioning

In the indoor positioning system， the RSSI ranging positioning system encounters unpredictable random variation due to environmental uncertainty and Pedestrian Dead Reckoning positioning (PDR) system drift errors causes cumulative effect of prolonged positioning. An indoor PDR algorithm based on RSSI ranging positioning is proposed, which the final positioning result is based on extended Kalman filter output of fusion location information. The simulation results indicate that the fusion positioning algorithm shows up its good performance in the aspects of stability, which average location error is about 0.83205 m, maintaining from 0.51948 m to 1.13529 m. The rationality and availability of the scheme are verified.