考虑时间约束的纵侧向综合调控再入滑翔轨迹快速规划

doi:10.12382/bgxb.2024.0154

摘要/Abstract

摘要：

针对飞行时间约束下再入滑翔飞行器轨迹规划问题,提出一种基于阻力加速度剖面解析预测校正和倾侧反转点迭代的纵侧向综合调控再入轨迹快速规划方法。该方法将再入轨迹规划问题分为纵向规划与侧向规划。在纵向规划部分,设计与飞行时间一一对应的单参数阻力加速度剖面,并基于时间解析预测对剖面参数进行校正,完成参考剖面设计,同时满足终端高度、速度和飞行时间约束。在侧向规划部分,分析轨迹长度和终端位置调控机理,设计基于双倾侧反转点迭代的侧向规划方法,在满足终端位置约束的同时,通过调整轨迹长度,进而实现飞行时间的有效控制。在此基础上,引入基于时间误差的轨迹迭代修正策略,完成时间可控高精度3自由度再入轨迹生成。最终,以CAV-H再入滑翔为例进行仿真,验证了新方法的有效性、快速性及适应性;与现有时间可控再入轨迹规划方法相比,新方法在计算效率与精度相当情况下,可综合发挥纵侧向的时间调控能力,具有较大的时间可调范围和较少的倾侧反转次数,亦可对时间可调范围与可达域边界进行快速预示。

关键词: 再入轨迹规划, 时间约束, 纵侧向综合调控, 剖面解析预测校正, 时空边界快速预示

Abstract:

A rapid longitudinal-lateral comprehensive control trajectory planning method is proposed for the trajectory planning of reentry gliding vehicles under flight time constraints,which is based on the analytical prediction-correction of drag acceleration profile and the iteration of banked reversal points.In this method,the gliding trajectory planning issue is divided into longitudinal and lateral trajectory planning.In the longitudinal trajectory planning,a single-parameter drag acceleration profile corresponding to the flight time is designed.Furthermore,the profile parameter is corrected based on the time-of-flight analytical prediction,so as to complete the design of the reference drag acceleration profile to meet the terminal altitude,velocity and time-of-flight constraints simultaneously.In the lateral planning,a lateral planning method based on the iteration of the double bank reversal points is designed by analyzing the trajectory length and terminal position control mechanism.The longitude and latitude of target point are introduced to iteratively solve the bank reversal times,which can realize the effective control of the flight time by adjusting the trajectory length while satisfying the terminal position constraints.On this basis,a trajectory iterative correction strategy based on time error is introduced to complete the generation of a time-controllable high-precision three-degree-of-freedom reentry trajectory.Finally,CAV-H reentry gliding is simulated as an example to verify the effectiveness,rapidity and adaptability of the proposed method.Compared with the existing time-controllable reentry trajectory planning methods,the proposed method can comprehensively exert the longitudinal and lateral time control ability in the same computational efficiency and accuracy.Moreover,it boasts a wider range of time adjustability and minimizes the number of bank reversal instances.Additionally,it enables the rapid prediction of the time-adjustable range and the boundaries of reachable domain.

Key words: reentry trajectory planning, time constraint, longitudinal-lateral comprehensive control, analytical profile prediction correction, spatiotemporal boundary rapid prediction

南汶江, 闫循良, 杨宇轩, 王培臣. 考虑时间约束的纵侧向综合调控再入滑翔轨迹快速规划[J]. 兵工学报, 2025, 46(3): 240154-.

NAN Wenjiang, YAN Xunliang, YANG Yuxuan, WANG Peichen. Rapid Planning of Longitudinal-lateral Comprehensive Control Reentry Gliding Trajectory Considering Time Constraints[J]. Acta Armamentarii, 2025, 46(3): 240154-.

图/表 15

图1 阻力加速度剖面

Fig.1 Schematic diagram of drag acceleration profile

图2 2次倾侧反转所对应的地面轨迹

Fig.2 The ground trajectory corresponding to two bank reversals

图3 3自由度轨迹生成方法流程图

Fig.3 Flowchart of 3-DOF trajectory generation algorithm

图4 轨迹长度-飞行时间可调范围

Fig.4 Trajectory length and flight time adjustable range

图5 给定飞行时间下的可达区域

Fig.5 Reachable area at a given flight time

图6 固定目标点情况下的轨迹长度-飞行时间可调范围

Fig.6 Length and time adjustable range for fixed target point

表1 不同方法时间可调范围占比对比

Table 1 Comparison of the proportions of adjustable time range in different methods

时间调控方法	时间可调范围占比/%
本文方法	15.4
文献[7]方法	13.5
文献[10]方法	8.5
文献[14]方法	5.8
文献[15]方法	5.4
文献[16]方法	5.0

表2 轨迹规划方法仿真条件设置

Table 2 Simulation conditions for trajectory planning algorithm

算例	λ₀/ (°)	σ₀/ (°)	$λ f *$ / (°)	$ϕ f *$ / (°)	$t f *$ /s
1	0	50	50	10	1190
2	0	50	50	10	1390
3	3	60	45	45	1410
4	0	50	50	40	1520

表2 轨迹规划方法仿真条件设置

Table 2 Simulation conditions for trajectory planning algorithm

算例	λ₀/ (°)	σ₀/ (°)	$λ f *$ / (°)	$ϕ f *$ / (°)	$t f *$ /s
1	0	50	50	10	1190
2	0	50	50	10	1390
3	3	60	45	45	1410
4	0	50	50	40	1520

表3 不同仿真条件对应的终端误差

Table 3 Terminal errors corresponding to different simulation conditions

算法性能参数	算例1	算例2	算例3	算例4
Δh_f/m	0.7921	0.7922	0.7923	0.8062
Δv_f/(m·s^-1)	0.1778	0.1712	0.1839	0.1721
Δs/m	254.88	142.83	454.27	318.71
Δt_f/s	0.1681	0.1382	0.1329	0.1187
计算耗时/s	1.52	1.56	1.57	1.63

图7 多任务轨迹规划仿真结果

Fig.7 Simulation results of multi-task trajectory planning

表4 初始状态和气动参数扰动设置

Table 4 Perturbation settings of initial state and aerodynamic parameters

不确定参数	3σ	不确定参数	3σ
h₀/km	3	σ₀/(°)	0.5
λ₀/(°)	0.5°	ρ/%	10
ϕ₀/(°)	0.5°	C_L/%	10
v₀/(m·s^-1)	100	C_D/%	10
θ₀/(°)	0.5°

表5 蒙特卡洛仿真终端误差

Table 5 Terminal errors of Monte Carlo simulation

终端参数	Δh_f/m	Δv_f/(m·s^-1)	Δs/m	Δt_f/s
平均值	0.7946	0.1797	284.48	0.0027
标准差	0.0153	0.0084	114.51	0.0633

图8 蒙特卡洛仿真结果曲线

Fig.8 Monte Carlo simulated results

表6 不同轨迹规划方法的仿真结果对比

Table 6 Comparison of simulated results for different trajectory planning methods

算法性能参数	本文方法	文献[14]方法
Δh_f/m	0.8062	3.201
Δv_f/(m·s^-1)	0.1721	0.2960
Δs/m	318.71	403.90
Δt_f/s	0.1187	0.1371
轨迹迭代次数	3	5
计算耗时/s	1.63	1.28

图9 同一再入任务下不同轨迹规划方法的仿真结果

Fig.9 Simulated results for different trajectory planning methods under the same reentry mission

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