论文部分内容阅读
针对弹道跟踪数据融合处理中的大计算量环节研究了快速算法。用样条函数表示弹道参数,建立了多测元的联合观测模型和弹道参数的非线性融合计算模型,给出了弹道参数的求解算法,分析了弹道参数融合计算中的大型矩阵运算问题,利用基础线性代数函数库提高了大型矩阵的运算速度。建立了样条模型计算的非线性约束优化模型,给出了确定样条节点位置的优化算法,通过分析样条模型的计算原理设计了并行算法,实现了样条模型的并行化计算。仿真结果表明,弹道参数融合计算和样条模型计算的效率都得到了显著提高,计算时间减少了65.47%,对缩短数据处理周期有重要意义。
Aiming at the large amount of calculation in the ballistic tracking data fusion processing, the fast algorithm is studied. The spline parameters are used to represent the ballistic parameters. The joint observation model with multiple data elements and the nonlinear fusion model of ballistic parameters are established. The algorithm for solving the ballistic parameters is given. The problem of large matrix operations in ballistic parameter fusion calculation is analyzed. The basic linear algebra library improves the speed of large matrices. A nonlinear constrained optimization model for spline model calculation is established. An optimization algorithm for determining the spline node location is given. The parallel algorithm is designed by analyzing the spline model calculation principle, and the spline model is parallelized. The simulation results show that both the efficiency of ballistic parameter fusion calculation and spline model calculation have been significantly improved, and the calculation time has been reduced by 65.47%, which is of great significance to shorten the data processing cycle.