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在外弹道数据处理中,奇异点处理、特征点求取与随机误差削弱都是精度估计的关键环节。首先利用小波变换在处理奇异点、特征点、噪声消除方面的特点,对观测数据进行基于小波变换的分解、融合、重构处理,剔除奇异点,查找特征点,削弱随机误差。其次利用节点自由分布B样条描述导弹运动轨迹,使该弹道确定方法转化为关于求解导弹轨道样条表示参数和测量系统误差的多模型融合的非线性优化问题,采用非线性最优化方法,进而得到待估参数的最优估计,完成弹道的最佳逼近。最后仿真表明,该应用在奇异点处理、特征点提取与随机误差削弱方面效果很好,能减少计算量,且能切实提高精度。
In the external ballistic data processing, the singular point processing, the feature point seeking and the weakening of the random error are the key links of the precision estimation. Firstly, the wavelet transform is used to decompose, merge and reconstruct the observed data based on the characteristics of singular points, feature points and noise elimination. The singular points are eliminated, the feature points are found, and the random errors are weakened. Secondly, the free trajectory of the missile is described by means of the node free distribution B-spline. The trajectory determination method is transformed into the nonlinear optimization problem of multi-model fusion for solving the parameters of the missile trajectory spline and the measurement system error. The nonlinear optimization method is adopted, Get the optimal estimation of the parameters to be estimated, to achieve the best approximation of the trajectory. The simulation results show that the proposed method is effective in singular point processing, feature point extraction and random error reduction, which can reduce the computational complexity and improve the accuracy.