论文部分内容阅读
为了改善雷达回波反演大气波导(RFC)方面存在的单时次、单方位角反演的问题,提出利用扩展卡尔曼滤波和不敏卡尔曼滤波的反演算法对大气波导结构的多方位角实时跟踪反演.在卡尔曼滤波方法中分别给出大气波导结构的参数化方程、观测方程、滤波算法的状态转移方程,最后导出滤波反演算法的迭代求解流程.在大气波导结构不随时间变化和随时间变化的两种条件下,对扩展卡尔曼滤波和不敏卡尔曼滤波算法进行数值实验.实验结果表明,不敏卡尔曼滤波更适用于RFC这高度非线性反演问题,它可能今后为大气波导结构多方位角实时跟踪反演的业务化运行提供理论基础与技术保证.
In order to improve the single-time and single-azimuth inversion problems of radar echo retrieval atmospheric guide (RFC), the multi-azimuth and azimuth inversion algorithms based on Extended Kalman Filter and Unstirred Kalman Filter Angle real-time tracking inversion.The parametric equation, observation equation, state transition equation of the filter algorithm are given respectively in the Kalman filter method, and the iterative solution flow of the filter inversion algorithm is derived.When the atmospheric waveguide structure does not change with time And under time-varying conditions, numerical experiments on extended Kalman filter and unstiguifable Kalman filter are carried out.The experimental results show that unstiguigted Kalman filter is more suitable for the highly nonlinear inverse problem of RFC, which may be In the future, the theoretical basis and technical assurance will be provided for the operationalization of the multi-azimuth real-time tracking inversion of the atmospheric waveguide structure.