摘要
在脱靶量处理中,准确选取弹道的拟合函数是计算脱靶参数的关键.本文首先利用假设检验的回归模型算法,合理选取模型并确定函数阶次,提高函数逼近程度,减小了经验选模的函数拟合误差.其次,通过运用双弹道的数据融合算法解算脱靶量参数,消除了传统算法在弹道参数衔接点的跳跃现象,并通过理论仿真和实测数据验证了算法的有效性.
Accurately selecting the fitting function of trajectory is the key step to calculate the target-missing parameters properly in target-missing Quantity processing. In this paper, we firstly utilize the regression model with hypothesis testing, choose the reasonable fitting model and confirm the order-number of the function. It is found that this method improves the function approximation and decreases the error of fitting function during choosing the model based on our experience. Secondly, we calculate the parameters of target-missing using dual-trajectory data fusion algorithm. This method eliminates the jump phenomenon of the connections between the trajectory parameters. The results of real-data processing indicate that the algorithm proposed in this paper performs better than the traditional methods, which validate the feasibility and superiority of this approach.
出处
《动力学与控制学报》
2017年第1期39-43,共5页
Journal of Dynamics and Control
关键词
矩阵构造
假设检验
回归模型
脱靶量
matrix construction, hypothesis testing, regression model, target-missing quantity
