自适应两步滤波器及其在导弹被动制导中的应用

两步滤波器由Ｋａｌｍａｎ滤波器和Ｇａｕｓｓ－Ｎｅｗｔｏｎ迭代算法所构成，它适用于一类由线性动态模型和非线性测量模型所组成的非线性系统。本文将这种滤波器与时变测量噪声统计估值器相结合，得到一种自适应两步滤波器，在测量噪声统计特性无法验前已知的情况下，此滤波器仍然性能良好。最后，本文将自适应两步滤波器应用于导弹的被动制导问题，数字仿真结果证明了这种算法的有效性。

ADAPTIVE TWO-STEP FILTER WITH APPLICATIONS TO MISSILE GUIDANCE WITH PASSIVE MEASUREMENTS

The two step filter suits a class of nonlinear systems which include a linear dynamic model and a nonlinear measurement model.This filter consists of a Kalman filter and a Gauss Newton iterative algorithm.We integrate the two step filter with a time varying measurement noise statistical estimator to obtain an adaptive two step filter,which still performs well in the case where the statistical properties of the measurement noise are unknown apriori.The adaptive two step filter is applied to missile guidance with passive measurements and the numerical results show that this filter is really effective.