一种基于Particle Filter的攻击目标高度估计算法

利用目标高度估计确定目标攻击要害点是精确制导武器信息处理中的一个重要内容。传统方法主要有直接利用几何方法估计和扩展卡尔曼滤波器方法,这两种方法精度都不高。Partic le F ilter是一种新出现的滤波方法,在解决非线性问题中得到了广泛应用。利用Partic le F ilter设计了一种新的目标高度估计算法。该算法通过贝叶斯递推方法,避免了在测量方程非线性很强的时候,扩展卡尔曼滤波器不合理的线性化所带来的误差。仿真结果表明,这种基于Partic le F ilter的目标高度估计算法提高了估计精度和收敛的鲁棒性。

Attacked Target Height Estimation Based on Particle Filtering

Target height estimation is a key for precision guidance weapons to decide the point of a target to be attacked.Traditional methods include direct geometrical method and extended Kalman filter,with low precision.Particle filter is a recently-developed filtering method and is applied widely in resolving nonlinear problems.Proposes a new method based on particle filter to estimate the target height.The new method absolutely gets rid of unreasonable linearation by means of bayesian iteration.The simulation result shows that the new method exceeds the former ones with robustness and high precision.