传感器定位测距过程的改进方法研究与仿真

The Sensor Positioning Ranging Algorithm Based on Weighted Data Fusion

针对在实现传感器定位测距的过程中,由于节点的特征参数与自身损耗功率存在一定的局限性,导致定位不准确的问题。提出采用加权数据融合的传感器定位测距算法,将节点定位模型划分成两部分,路径损耗模型将接近发送端某距离处的平均接收功率当做参考,对另一距离上的平均接收功率进行计算,模型的另一部分指出距离不变时,传感器节点接收的信号能量满足对数正态随机变化。充分利用多测距源提供的冗余信息,通过自适应加权数据融合测距算法,依据先验知识或仿真数据得到所有单一测距算法在不同情况下的加权系数,完成对单一算法测距结果的加权融合。仿真结果表明,改进算法的定位测距准确度高、速度快。

In view of the problem of inaccurate positioning because the characteristics parameter of node and itself loss power have certain limitation,in the process of realizing the sensor positioning and ranging,a sensor positioning and ranging algorithm based on weighted data fusion is presented in this paper.The node positioning model is divided into two parts,in path loss model,the average received power which is close to a certain distance of the sending end is as a reference,to calculate the average received power of another distance,another part of the model points out that when the distance is constant,the signal energy received by the sensor node satisfies lognormal random variation.Making full use of redundant information provided by multi-ranging source,through the adaptive weighted data fusion ranging algorithm,on the basis of prior knowledge or simulation data,the weighted coefficients of all single ranging algorithm under different circumstances are gotten,to complete the weighted fusion of ranging results by using single algorithm.The simulation experimental results show that the improved algorithm has high accuracy and fast speed of positioning and ranging.