在对远程高速运动目标进行定位的过程中,提高定位精度是工程研究的重要内容之一.针对最小二乘法受测量误差影响较大的问题,提出了基于最小二乘和牛顿迭代法的混合算法.该算法结合了最小二乘法估计性好和牛顿迭代法收敛速度快的优点.仿真结果表明,时差测量精度为5ns时,均方根误差较最小二乘法定位结果减少了43m.
In the positioning process of the remote and high speed moving target,improving localization accuracy is one of the important aspects of engineering.Aiming at the problem that least squares influenced by measuring error seriously,this paper puts forward the blending algorithm which based on least squares and Newton iterative algorithm.The algorithm combines the advantages of least squares good performance in estimation and Newton iterative method high speed of convergence in iteration.The simulation results indicate that the RMSE reduced by 43m compare with the localization result of least square method when the time measurement accuracy is 5ns.