UKF和KF两级滤波的雷达与红外配准算法

Registration Algorithm of Radar and IR Sensor Based on Two Stage Filtering of UKF and KF

针对雷达与红外传感器的时间和空间偏差配准问题,给出时空偏差配准模型,提出了一种时空偏差实时估计算法。该算法将目标的运动状态和传感器偏差组合在同一状态方程中,构建扩维状态的系统动态方程和量测方程,并通过对量测方程的非线性分析,采用UKF和KF两级滤波的方法进行目标状态和配准偏差的联合估计。仿真结果表明,与采用UKF滤波的方法相比,该算法具有更高的估计精度,而且减小了计算量。

For the space-time registration errors of radar and IR sensor, a registration model for space and time biases is given and a registration algorithm for on-line biases estimation is presented. By incorporating sensor misalignments and target states into an augmented dynamic model, the dynamic equation of the augmented state and the augmented measurement equation are constructed. Then through the analysis for nonlinearity of the augmented measurement equation, a method of two stage filtering of Unscented Kalman Filter （UKF） and KF is proposed to estimate target states and register radar and IR sensor simultaneously. Furthermore, by comparison with the method of only using UKF, the proposed method has higher accuracy of estimation and less computation. The simulation results show the availability and practicability of the proposed algorithm.