| 摘要:摘要：针对多传感器的系统误差配准问题，研究了系统误差时变的情况，提出了一种基于迭代扩展卡尔曼滤波（IEKF）的配准算法。该算法将目标的运动状态和传感器系统误差组合在同一状态方程中，构建扩维状态的系统动态方程，采用IEKF的方法对目标状态和系统误差进行联合估计。仿真结果表明，与采用EKF和UKF的方法相比，该算法能取得和UKF相似估计精度，并且时间效率和EKF相当。 |
| 关键词: 多传感器网络 误差配准 迭代EKF 数据融合 |
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| A Real-Time Registration Algorithm for Multi-Sensor |
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| Abstract:Abstract: For the systematic registration errors of multi-sensor, a registration model for space biases is given and a registration algorithm based on iterated extend Kalman filter(IEKF) is presented. By incorporating target states and systematic registration errors into one state equation, the dynamic equation of the augmented state equation is constructed. Then a registration algorithm based on IEKF is proposed to estimate target states and systematic registration errors simultaneously. To compare with EKF and UKF, the result shows the proposed method has the same or even better accuracy to UKF and the similarity computation with EKF. |
| Key words: multi-sensor network space registration iterated extend Kalman filter data fusion |