基于固定滞后滤波平滑的弹道重构算法

为有效利用雷达测量的飞行数据进行弹箭的实际弹道重构，建立了弹道重构需要的状态方程和量测方程，考虑模型的非线性和重构状态非高斯分布的可能性，结合Bootstrap粒子滤波给出一种一步固定滞后滤波平滑算法的实现，并将其作为弹道重构的估计工具。算例仿真表明，相比于Bootstrap粒子滤波和无迹卡尔曼滤波，该Monte Carlo平滑算法可以进一步提高估计的精度，为弹道重构提供一种新的有效工具。

Trajectory reconstruction algorithm based on fixed-lag filter-smoother

To reconstruct the practical trajectory via effectively using flight data measured by radar for projectiles, reconstruction model with state equations and observation equations is established. Taking account of the inherent model nonlinearity and potential non-Gaussian distribution of reconstruction states, a one-step fixed lag filter-smoother algorithm is proposed as the estimation method combined with Bootstrap particle filtering. Simulation results show that the proposed Monte Carlo smoothing algorithm can achieve much more accurate estimates than the Bootstrap particle filtering and unscented Kalman filter. Consequently, the proposed algorithm provides a novel effective estimation approach to trajectory reconstruction.