基于IPSO的B样条插值航空器轨迹重构算法研究  

Research on IPSO-based B-spline Interpolation Aircraft Trajectory Reconstruction Algorithm

作　　者：李宏赢 任艳丽[1] 邓雪云 

机构地区：[1]上海大学通信与信息工程学院,上海200444 [2]中国商飞上海飞机设计研究院,上海201000

出　　处：《工业控制计算机》2025年第1期82-84,共3页Industrial Control Computer

基　　金：运输航空可视导航技术与验证(2022YFB3904300)。

摘　　要：在民用航空器飞行轨迹实时预测和重构研究中,针对航空器轨迹仿真在三维空间下的飞行运动方程计算复杂,普通B样条轨迹重构算法拟合度差的问题,提出了基于B样条插值与改进粒子种群算法结合的航空器轨迹重构的方法。首先,对飞行器三维飞行轨迹重构进行样条函数建模,在真实航迹点上随机获取节点,采用B样条插值方法对飞行器轨迹重构,然后使用混沌初始化和自适应学习因子策略相结合的改进粒子种群算法优化样条节点,实现重构飞行轨迹的优化。最后,针对三维空间下的飞行器轨迹重构算法进行仿真。仿真结果对比表明,该方法有效提升了重构轨迹的精度和效率。In the real-time flight trajectory prediction and reconstruction research,he method of aircraft trajectory reconstruction based on the combination of B spline interpolation and IPSO is proposed to address the problem of the complicated computation of the flight equations of motion of the aircraft in three-dimensional space and the poor fit of the ordinary B-spline trajectory reconstruction algorithm.Firstly,the spline function modeling is carried out for the reconstruction of the three-dimensional flight trajectory of the aircraft.The nodes are randomly obtained at the real trajectory points,and then the spline nodes are optimized using the improved particle population algorithm which is a combination of the chaotic initialization and the adaptive learning factor strategy to achieve the optimization of the reconstructed flight trajectory.Finally,the simulation is carried out for the aircraft trajectory reconstruction algorithm in three-dimensional space.

关 键 词：混沌初始化 自适应学习因子策略 改进型粒子种群算法 B样条插值 轨迹仿真 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] V355[自动化与计算机技术—控制科学与工程]