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假设某些目标能作正交于其速度矢量的规避机动,提出一种新的随机动态目标模型.利用增益修正广义卡尔曼滤波器来估计目标状态和在线建立目标机动的角速率.推导出可使二次型性能指标极小化的制导律,对于二维的只有角测量的情况,数值仿真表明,所提出的目标模型会使目标状态的估计得到明显的改进.此外,还给出采用这种新制导方法对终端脱靶距离的影响,并与高斯-马尔可夫模型作了比较.
Assuming that some targets can act as an avoidance maneuver orthogonal to their velocity vectors, a new stochastic dynamic target model is proposed. The gain-modified generalized Kalman filter is used to estimate the target state and establish the angular rate of the target maneuver. For the guidance law that minimizes the quadratic performance index, for the two-dimensional only angular measurement, the numerical simulation shows that the proposed target model can significantly improve the estimation of the target state. In addition, The effect of the new guidance method on the off-target distance of the terminal is compared with that of the Gaussian-Markov model.