基于SRUKF的机载多平台传感器数据配准算法  

Algorithm forairborne multi-platform sensor registration based on square root unscented kalman filter

作　　者：孟宏峰[1] 刘兆磊[1] 胡学成[1] 俞建国[1] 马岳飞[1] 

机构地区：[1]南京电子技术研究所,南京210003

出　　处：《电子测量技术》2016年第2期111-114,共4页Electronic Measurement Technology

摘　　要：提出一种基于平方根UKF的机载多平台传感器数据配准方法。首先给出多平台传感器偏差配准模型,将目标的运动模型和传感器配准误差组合在同一个状态方程中,然后讨论模型的可观测性,利用平方根UKF算法估计目标的运动状态和传感器配准误差,避免了对非线性方程的线性化,相比传统UKF算法减少了计算量。Monte-Carlo仿真表明,该方法能同时有效估计目标运动状态和多平台传感器配准误差,且系统偏差的估值迅速收敛到真实值附近,相比传统UKF方法,在相当的估计精度下,具有更快的运算速度和收敛速度。The problem of registration for airborne multi-platform sensor based on the square root unscented kalman filter（SRUKF）in a fusion system is considered.First,a registration model for misaligned sensors was given.Then,the sensor misalignments and target states were incorporated into an augmented dynamic model,then the observability of the model was discussed and SR-UKF was proposed to estimate target states and register these sensors simultaneously.The linearization of the nonlinear equation was not needed and the amount of calculation was reduced compared to UKF.Simulations demonstrate the effectiveness of the proposed algorithm.SRUKF has faster convergence speed and computational speed compared to UKF simultaneously.

关 键 词：机载多平台 数据配准 平方根UKF 

分 类 号：TN953[电子电信—信号与信息处理]