摘要
误差配准是消除传感器系统误差必不可少的过程。针对非合作目标情况下如何估计传感器系统误差的问题,提出了一种基于线性卡尔曼和最小二乘的三维误差配准算法。该算法考虑了地球曲率的影响,解决了传统的二维算法无法估计俯仰角系统误差的问题。通过构造系统模型,将传感器系统误差和目标运动情况统一到同一量测方程中,并结合线性卡尔曼和最小二乘得到系统误差的估计。仿真结果表明,该方法能有效地估计包括俯仰角误差在内的多种系统误差。
Bias registration is an essential process for correcting the system bias of sensors. In order to estimate the sensor system bias without cooperation targets, a three-dimensional bias registration algorithm was proposed based on linear Kalman and least squares. This algorithm takes the curvature of the earth into account and can estimate the system bias of elevation angle that can＇t be calcuXated with the traditional 2D method. The system bias of sensors and the motion of target are combined into the same measurement equation by constructing a system model. Then the estimation of system bias is completed by using the linear Kalman and least squares. Simulation results show that system biases can be estimated effectively, including elevation angle bias.
出处
《电光与控制》
北大核心
2014年第1期38-41,共4页
Electronics Optics & Control
关键词
信息融合
误差配准
多传感器
线性卡尔曼
系统误差
information fusion
bias registration
multi-sensor
Linear Kalman
system bias
