RSSI曲线拟合的误差分析与分段方法

Error analysis and ranging algorithm of RSSI polynomial piecewise fitting

针对接收信号强度(RSSI)测距算法常用Shadowing模型在一些实际测距中固定节点受到地形等环境因素影响致使其使用受限的问题,提出了一种基于多项式分段拟合的RSSI测距算法.该算法利用最小二乘拟合函数法,将采样的有限个RSSI数据分段拟合成连续的三次多项式函数,以便更准确地模拟特定环境下的RSSI衰减情况.利用该算法进行实验和仿真,寻求合适的分段数和分割点,结果表明:用2段法进行拟合可将平均误差由2.25 m降低至0.877 8 m.

Aiming at the problem that the Shadowing model commonly used of received signal strength indicator（ RSSI） ranging algorithm was limited due to the effect of environmental factors such as the terrain in practice,a RSSI ranging algorithm was proposed based on piecewise polynomial fitting. This method,using of least-squares fitting function,fitted the sampling of a finite number of RSSI data to a continuous piecewise cubic polynomial function,which could simulate more accurately RSSI attenuation under specific circumstances. Using this algorithm and simulation experiments to seek appropriate number of segments and split points,the results showed that the average error was decreased from 2. 25 m to 0. 877 8 m using twopiecewise fitting method.