低通滤波与卡尔曼滤波相结合的制导律识别

A LPF enhanced adaptive Kalman filter for guidance law recognition

摘要:

为利用观测数据对执行追踪任务的非合作目标飞行器进行制导律识别，采用一种通用的隐式制导函数对制导行为进行统一描述，并且给出了一种采用时变制导系数的模型来逼进隐式制导函数.在此模型基础上，利用低通滤波与卡尔曼滤波相结合的频域分离自适应卡尔曼滤波方法对观测数据进行实时处理分析，最终得到目标飞行器的制导律识别结果.仿真结果表明，在目标飞行器采用比例导引律或Bang-Bang变结构制导律的情况下，识别算法能够从观测数据出发，对目标飞行器的制导律完成有效和快速识别.

Abstract:

The recognition of the guidance law of a non-cooperative target vehicle is very useful for the counteraction design of the pursuing vehicle. A generic implicit guidance function is presented to describe all known guidance laws, and a practical model with time-varying guidance parameters is used to approximate the generic implicit guidance function. Based on this model, a LPF enhanced Adaptive Kalman Filter is proposed to recognize the guidance law in real-time. Simulation results show that the proposed algorithm can recognize the guidance law fast and effectively when the non-cooperative vehicle employs either the Proportional Navigation guidance law or the Bang-Bang guidance law.