基于扩展卡尔曼滤波的射程修正落点预测模型

Prediction Model of Range Correction Falling Points Based on Extended Kalman Filter

针对一维弹道修正引信修正效能评估采用传统试验方法存在试验条件一致性差、用弹量大的问题,提出了基于扩展卡尔曼滤波的射程修正落点预测模型。传统方法是修正弹与非修正弹各打一组,对比落点;而该方法只打一组修正弹,依据修正点前的实测弹道参数预测非修正弹落点,然后以非修正弹预测落点与修正弹落点对比。通过实弹射击试验对该模型预测的落点进行了验证,试验结果表明:采用该模型预测得到的落点精度较高,与实际弹道在射程和密集度上无显著性差异,可用于评估一维弹道修正引信的修正效能。

In order to solve the problems that the trodictional experiment was of poor consistence on experiment condition and large amount of projectile concuming when evaluating the correction ability of one-dimensional range-correction fuze, a ballistic model of falling points prediction based on extended Kalman filtering was estab- lished. In the traditional method, each group of non-corrected and corrected ammunition were fired, then their differences of falling points were compared. In the proposed method, just one group of correted ammunition was fired, and the falling points of non-corrected ammunition was predicted, then the falling points differences be- tween the prediction and the correction was compared. The feasibility of the method had been demonstrated in tests. The tests results showed that the predicted trajectory precision was high, which could be used to assess the correction ability of one-dimensional range-correction fuze.