基于最小二乘拟合法的分布式POS全局估计方法

针对无法保证各子阵天线附近均安装高精度子惯性测量单元（IMU）的问题，提出了一种基于最小二乘拟合的分布式位置姿态测量系统（POS）全局估计方法。首先，建立了考虑一维柔性变形角的主/子传递对准误差模型；然后，采用卡尔曼滤波（KF）估计已安装子IMU的子阵天线运动参数；最后，在已获取运动参数的基础上，采用最小二乘拟合估计未安装子IMU的子阵天线运动参数。半物理仿真实验结果表明，所提方法精确实现了阵列天线运动参数的全局估计，且未安装子IMU的子阵天线运动参数估计精度与相邻的子阵天线运动参数估计精度相当。 

Global estimation method based on least square fitting for distributed POS

Aimed at the problem that it is impossible to install high-precision sub-Inertial Measurement Unit (IMU) on every sub-array in engineering practice, a global estimation method based on the least square fitting for distributed Position and Orientation System (POS) is proposed. Firstly, a transfer alignment error model from master system to slave system considering one-dimensional flexibility deformation is built. Secondly, Kalman Filter (KF) is used to estimate motion parameters of array antenna of the sub-arrays with sub-IMUs. Finally, the least square fitting is used to estimate the motion parameters of the sub-arrays without sub-IMU. The semi-physical simulation results show that the proposed method can realize the global estimation of the motion parameters of array antenna, and the estimation precision of the motion parameters of sub-arrays without sub-IMU is almost the same as that of its neighboring sub-arrays.