基于测距最小二乘的方位融合多传感器定位算法

在多部2D传感器组网目标定位中,为减小地球曲率对观测的影响,充分利用各传感器量测并解决观测方程的非线性最小二乘问题,提出了融合方位量测的测距最小二乘算法。该算法的实质是基于多部2D传感器设备的测距以及方位角信息,考虑地球曲率的影响建立等效的观测模型和非线性方程,通过数学变换将非线性系统转化为线性系统;利用纯距离最小二乘定位原理初步估算出目标的位置,然后融合各传感器的方位量测得到关于目标的最终位置估计。仿真实验表明,本方法在3部以上2D传感器观测并且测距误差较大而方位误差较小的情况下,可以修正测距最小二乘法在某些位置的定位误差,从而整体提高目标的定位精度。

An Azimuth Fusion Locating Algorithm Based on RangeOnly Least Squares for Multi-Senor Network

In the process of target locating in two dimensional multi sensor network,a least squares algorithm fused with azimuth information was proposed in order to diminish the influence of earth curvature to the observation,and to make full use of the measurements from all the sensors and deal with the problem of none liner observation equations.The presented algorithm was based on the range and azimuth information obtained from the sensors in the network.The equivalent observation model and the non linear equations were established taking the effect of earth curvature into consideration.The equations were transformed into linear equations and solved by least squares theory to get the primary location of the target.Finally location estimation was implemented by fusing all the azimuths from the sensors.The result of the simulation experiment indicated that: in the network of more than three 2D sensors with large range error and small azimuth error,the algorithm can correct the locating error in some positions and improve the locating precision accordingly.