传感器数据定位测距算法优化仿真与研究  

A Sensor Positioning Ranging Algorithm and Its Simulation

作　　者：程钢[1] 郑富娥[1] 

机构地区：[1]中州大学,河南郑州470000

出　　处：《计算机仿真》2015年第12期284-286,446,共4页Computer Simulation

摘　　要：由于传感器易受到周围环境的干扰,使得信号各节点之间存在随机性动态变化,传统的定位测距算法,主要是以先固定一个节点为前提计算节点之间的距离,当所有节点动态变化时,只是对节点进行简单的加权处理进行测距,不能使所有节点进行固定,导致定位精确度低、鲁棒性弱的问题。提出基于改进最小二乘原理加权数据融合算法的传感器数据定位测距方法。先依据加权最小二乘法WLS解方程组获取信号源的初始位置估计点,按顺序选择基站进行TDOA定位,获得传感器初始坐标位置估计值,在利用最小二乘原理和方差的遗忘信息将传感器的全部测量方差进行比较,计算传感器的每个权重之后进行加权融合,进而有效地实现了对传感器精确的定位测距。仿真结果表明,基于改进RSSI加权数据融合算法的传感器定位测距方法定位精确度高,鲁棒性强。A sensor data positioning and ranging method based on improved weighted least square （WLS） data fusion algorithm is proposed. First of all, on the basis of WLS to solve equations to obtain the initial position estimation point of signal source, the base station is orderly selected to make TDOA location, and the estimated value of sensor＇s initial coordinate position is obtained. Then, by using the principle of least squares and the forgotten information of variance, all of the measurement variances of sensors are compared. After calculating each weight of sensor, weighted fusion is performed, so as to effectively realize the precision positioning and ranging of sensor. Simulation results show that the proposed algorithm has high positioning accuracy and strong robustness.

关 键 词：数据融合 多传感器 定位测距 

分 类 号：TN014[电子电信—物理电子学]