考虑量测滞后的INS/SAR组合导航非等间隔滤波算法研究

由于INS／SAR组合导航系统中图像匹配定位需要耗用不等的匹配计算时间，从而造成了量测的不等间隔频率输出和量测信息滞后。针对上述问题，采用常规的卡尔曼滤波算法难以获得高的滤波精度。本文首先分析了常规卡尔曼滤波器工作过程；然后在此基础上，提出了采用非等间隔并解决滞后的滤波算法以解决上述问题。本文利用系统状态转移矩阵的特性，设计了相应的非等间隔卡尔曼滤波算法，以解决非等间隔量测的问题；同时，在该非等间隔卡尔曼滤波算法的基础上，提出了解决量测滞后的方案。并通过协方差分析的方法对比分析了常规卡尔曼滤波器，非等间隔卡尔曼滤波器和解决滞后效应的滤波算法三种情况下的滤波精度。仿真结果验证了本文提出的算法具有较高的滤波精度。

Processing the measurement delay INS/SAR integrated navigation in-coordinate interval filtering algorithm study

Because of the images matching position in INS/SAR integrated navigation system needing the unequal matching calculation time,which resulted in in-coordinate interval and delay characters of measurement output.The integrated filtering with the common kalman filtering algorithms couldn't get high degree of accuracy for the problem.At first,the paper analyzed the common kalman filtering work process.And then the paper gave the filtering algorithms for solving the problem of in-coordinate interval and measurement delay.The paper utilized the character of the system state transition matrix,and designed the corresponding in-coordinate interval kalman filtering algorithms to solve the problem of in-coordinate interval measurement.And based on the in-coordinate interval kalman filtering algorithms,the paper gave the scheme of solving the measurement delay.With the analysis of the covariance,the paper analyzed the filtering accuracy of all of the common kalman filtering,the in-coordinate interval kalman filtering and the algorithms of solving the measurement delay.And the simulation results have verified the high degree of accuracy of the algorithms presented in paper.