三维传感网空间RSS与AOA混合测量的精确定位方法

摘要

由于位置坐标参数的增加,三维传感网空间的定位难度较二维平面有所增大.单一的依靠接收信号强度(RSS)确定节点位置坐标的方法将使定位的不确定性增加,定位误差也较大.新型的阵列与智能天线的出现为节点间的到达角度(AOA)测量提供了方便,为此本文提出了一种三维传感网空间RSS与AOA混合测量的精确定位方法.将采用混合测量建立的非线性优化模型转化为线性方程,分别提出了节点位置坐标估计的非约束线性最小二乘(ULLS)及约束线性最小二乘(CLLS)方法.仿真测试了所设计算法的有效性,分析了不同测量噪声对位置坐标估计误差的影响.仿真表明所设计的ULLS和CLLS方法的计算速度快,相比于ULLS方法,采用约束后的CLLS方法的定位误差更小.在较小测量噪声范围内,ULLS和CLLS估计方法具有较高的稳定性和定位精度.%It is more difficult for the 3-D WSN space localization compared with 2-D plane due to the addition of the position coordinate parameters.The method to locate a sensor node will make the increasing of positioning uncertainty by the single received signal strength(RSS),and the position error is also big.The emergence of new array and smart antenna provides the convenience of the arrival of angle(AOA)measurements,so a precise positioning method is proposed by using the hybrid RSS and AOA measurements in 3-D WSN space.The built nonlinear optimization model using the hybrid measurements is converted into the linear equations,then the unconstrained linear least squares(ULLS)and constrained linear least squares(CLLS)methods are put forward for the estimation of the node position coordinates.The simulations show that the ULLS and CLLS run fast and the positioning error of CLLS is less than that of ULLS due to the constraint condition.In a small range of measurement noise,the estimation methods of ULLS and CLLS have high stability and positioning accuracy.