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作 者:曹树新 李岩[1] 李帅孝 徐树威 CAO Shuxin;LI Yan;LI Shuaixiao;XU Shuwei(School of Energy and Power Engineering,Nanjing University of Science and Technology,Nanjing 210094,China;The SecondMilitary Representative Office of the Military Representative Bureau in Shenyang,Army Equipment Department,Shenyang 110004,China;Qiqihar Jianhua Machinery Company Limited,Qiqihar 161006,China)
机构地区:[1]南京理工大学能源与动力工程学院,江苏南京210094 [2]陆军装备部沈阳地区军事代表局驻沈阳地区第二军事代表室,辽宁沈阳110004 [3]齐齐哈尔建华机械有限公司,黑龙江齐齐哈尔161006
出 处:《弹道学报》2020年第4期34-38,62,共6页Journal of Ballistics
摘 要:为了快速准确获取弹道解算用数值天气预报中风的预报误差,实现对弹道解算用数值天气预报中风预报误差的数值修正,提升火炮气象保障精度,以原始预报气象数据为基础气象条件,以质点弹道模型为系统模型,以风修正系数描述风的预报误差,基于无迹卡尔曼滤波算法,对实测弹道数据进行处理,提取风的预报误差。以一段实测弹道数据和WRF模式原始预报气象数据为例,对该方法的辨识效果进行检验。结果表明:与实测的风修正系数相比,辨识所得纵风修正系数和横风修正系数的相对误差分别为7.20%和3.97%;原始预报气象数据中的纵风和横风经修正后,其误差分别减小85.19%和79.27%。In order to obtain the wind prediction error of numerical weather prediction(NWP)for trajectory calculation quickly and accurately,realize the numerical correction of the wind prediction error of the NWP for trajectory calculation,and improve the accuracy of artillery meteorological support,the particle trajectory model was used as the system model based on the original prediction meteorological data.The wind correction coefficients was used to describe wind prediction error,and the unscented Kalman filter algorithm was used to process the measured trajectory data and extract the wind prediction error.The identification effect of this method was verified by a segment of measured trajectory data and original meteorological data predicted by WRF model.The results show that compared with the measured wind correction coefficient,the relative errors of longitudinal wind modified coefficient and cross wind modified coefficient are 7.20%and 3.97%respectively.After correction,the errors of longitudinal wind and cross wind in the original prediction meteorological data are reduced by 85.19%and 79.27%respectively.
分 类 号:TJ012.3[兵器科学与技术—兵器发射理论与技术]
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