多传感器网络中目标定位的改进算法

为提高多传感器网络中的目标定位精度,基于优胜劣汰的进化思想提出一种改进算法.该算法通过循环运算,剔除明显异常的测距数据后,再对目标点进行定位.首先利用最小二乘法,拟合出目标点的初始概位,然后计算各节点到初始概位的距离与测量数据的相对误差的绝对值及相对误差的平均值,判断该平均值是否达到某一经验值,若未达到经验值,则剔除相对误差最大的节点数据,再进行下一轮运算,直到平均值达到经验值,且确保节点数多于3时,此轮次中估算的概位坐标即为目标点坐标.Matlab仿真实验表明,本算法可有效地提高定位精度.

A new algorithm on localization of sensor network including multi-nodes

To improve the localization precision in the sensor network including multi-nodes,a localization algorithm based on evolution theory was proposed.The algorithm eliminated the obviously abnormal datas through iteration,and then located the objective.This algorithm first fit the approximate position with least square(LS) and calculated the relative errors as well as the average of relative errors which are difference between measure distance and the distance of the initial position and nodes,then compared the average with a experience data,if not match case,eliminates the data with maximum relative error,otherwise,the approximate position was objective position when number of node was great three.Simulated experiment based on Matlab indicated that this algorithm effectively improved the localization precision.