基于样条函数表征目标运动轨迹事后数据融合方法研究

Data Fusion Algorithm for Target Trajectory Determination Based on Spline Function Representation

针对靶场小型、机动目标多体制跟踪定位模式,提出一种基于样条函数描述目标运动轨迹并进而转换,实现以其为基函数对测控设备测元进行表征的数据融合方法。在最小二乘准则下,采用非线性最优化方法对样条函数最优节点分布进行搜索,使自由节点分布适应目标运动特性,极大减小截断误差,联合误差方程待估参数被极大压缩,计算效率提高。通过工程应用分析,该方法不仅目标轨迹参数计算精度高,而且能够准确自校准各测元系统误差。

A data fusion algorithm for target trajectory determination based on spline function representa- tion is presented. Under least squares criterion, a nonlinear optimization strategy is applied to search the optimal spline nodes according to different trajectory characteristics. The truncation error can be elimina- ted and the estimated parameters in the fusion model can be reduced greatly. Therefore, the computation- al efficiency and estimation accuracy for the trajectory parameters will be enhanced. Finally, the calcula- tion show the validity of the proposed algorithm, and the system errors for each measuring data can be compensated accurately.