用卡尔曼滤波方法实现运动平台多传感器配准

目的针对运动平台的多传感器系统，研究一种能有效地估计配准误差并消除其影响的算法．方法提出用卡尔曼滤波方法估计失调误差和姿态误差，该方法首先估计失调误差，然后利用不含失调误差的模型，估计并消除姿态误差．结果该算法能有效地估计多传感器系统的配准误差，使融合数据确定性明显增强．结论将卡尔曼滤波算法应用于运动平台的多传感器数据配准，它能有效估计配准误差，对于传感器的数据融合有重要的意义．

Kalman Fliter Approach to Multisensor Registration of Moving Platform

Aim To find an effective method to remove the registration error in multi-sensor systems. Methods A Kalman filtering technique was proposed to estimate and remove sensor bias and sensor fare tilt errors in multisensor systems with a moving platform. Results Simulation results are presented to demonstrate the performance of the approach. Conclusion The Kalman filter algorithm am detect registration errors and use this information to converge tracks from independent sensors. This is particularly important if the data from the sensors are to fused.