面向目标定位精度提升的无人机航迹规划

doi:10.12382/bgxb.2023.0776

摘要/Abstract

摘要：

针对机动目标定位的精度提升问题,给出两种典型任务场景下机动目标定位的在线协同航迹规划方法。建立测向交叉目标定位模型,基于几何精度因子确定影响定位精度的因素,分析影响要素对定位精度的影响规律;对于低速机动目标定位,以几何精度因子为评估指标,提出一种基于变曲率杜宾斯曲线的在线协同航迹生成方法,实现协同定位最优构型的快速航迹生成;对于高速机动目标协同定位问题,建立面向目标定位精度的最优控制模型,提出一种基于内点法的罚函数协同航迹规划方法;进行数字与半实物仿真验证。研究结果表明:在两种典型任务场景下,目标协同定位精度提升36.9%和23.5%,验证了新方法的有效性,新方法对于集群协同目标定位具有工程应用价值。

关键词: 无人机, 航迹规划, 协同定位, 定位精度, 定位构型, 最优控制

Abstract:

An online cooperative path planning method for maneuvering target positioning in two typical mission scenarios is presented to improving the accuracy of maneuvering target positioning. Firstly, a direction-finding cross-target positioning model is established. The factors affecting the positioning accuracy are determined based on the geometric dilution of precision, and the effect of the influencing factors on the positioning accuracy is analyzed. Secondly, for the positioning of low-speed maneuvering target, an online cooperative track generation method based on variable curvature Dubins curve is proposed with a geometric accuracy factor as the evaluation index, and the fast track generation of the optimal configuration of cooperative positioning is realized. For the cooperative positioning of high-speed maneuvering targets, an optimal control model for target positioning accuracy is established, and a penalty function cooperative path planning method based on interior point method is proposed. Finally, the digital and semi-physical simulation verification is carried out. The results show that the target cooperative positioning accuracy is improved by 36.9% and 23.5%, respectively, in two typical task scenarios, which verifies the effectiveness of the proposed method. This method has the engineering application value for cluster cooperative target positioning.

Key words: unmanned aerial vehicle, path planning, collaborative positioning, positioning accuracy, positioning configuration, optimal control

中图分类号:

V249

傅晋博, 张栋, 王孟阳, 赵军民. 面向目标定位精度提升的无人机航迹规划[J]. 兵工学报, 2023, 44(11): 3394-3406.

FU Jinbo, ZHANG Dong, WANG Mengyang, ZHAO Junmin. Unmanned Aerial Vehicle Path Planning for Improved Target Positioning Accuracy[J]. Acta Armamentarii, 2023, 44(11): 3394-3406.

图/表 19

图1 测向交叉定位示意图

Fig.1 Schematic diagram of direction-finding cross-positioning

图2 模拟场景示意图

Fig.2 Simulated scenario diagram

图3 不同高度下目标位置与GDOP关系

Fig.3 Relationship between target position and GDOP at different altitudes

图4 低速目标绕飞协同定位策略

Fig.4 Low-speed target go-around co-positioning strategy

图5 绕飞协同定位模型示意图

Fig.5 Schematic diagram of fly-by-wire co-positioning model

图6 Dubins曲线4种基本形式

Fig.6 4 basic forms of Dubins curves

图7 航迹规划流程

Fig.7 Path planning process

图8 高速机动目标协同定位场景示意图

Fig.8 Schematic diagram of high-speed maneuvering target co-positioning scenario

图9 算法流程图

Fig.9 Flowchart of the proposed algorithm

表1 仿真参数

Table 1 Simulation parameters

参数	数值
无人机1初始状态	P₁=[ $993 m - 843 m - 0.3602 r a d$ ]
无人机2初始状态	P₂=[ $- 786 m 924 m - 3.1125 r a d$ ]
无人机3初始状态	P₃=[ $550 m 635 m 2.3166 r a d$ ]
无人机4初始状态	P₄=[ $- 831 m - 200 m - 1.5088 r a d$ ]
目标初始位置/m	P_T=[0 0]
基准点速度方向/rad	$π 2$
最低飞行高度/m	100
最小转弯半径/m	100

表1 仿真参数

Table 1 Simulation parameters

参数	数值
无人机1初始状态	P₁=[ $993 m - 843 m - 0.3602 r a d$ ]
无人机2初始状态	P₂=[ $- 786 m 924 m - 3.1125 r a d$ ]
无人机3初始状态	P₃=[ $550 m 635 m 2.3166 r a d$ ]
无人机4初始状态	P₄=[ $- 831 m - 200 m - 1.5088 r a d$ ]
目标初始位置/m	P_T=[0 0]
基准点速度方向/rad	$π 2$
最低飞行高度/m	100
最小转弯半径/m	100

图10 协同航迹规划结果航迹对比

Fig.10 Comparison of cooperative path planning result paths

图11 不同方法定位误差对比

Fig.11 Comparison of errors of different methods

表2 定位误差对比

Table 2 Comparison of positioning errors

航迹规划方法	平均误差/m	航迹规划方法	平均误差/m
Dubins	1.2845	直线圆弧联合	2.7979
本文方法	0.8101	自适应等角螺线	1.7824

表3 在线规划仿真参数

Table 3 Online planning simulation parameters

仿真参数	数值
无人机1初始位置/m	P₁=[ $10000$ ]
无人机2初始位置/m	P₂=[ $000$ ]
无人机3初始位置/m	P₃=[ $- 100 00$ ]
目标初始位置/m	P_T=[ $0100000$ ]
无人机初始速度/(m·s^-1)	30
目标速度大小/(m·s^-1)	30
无人机速度范围/(m·s^-1)	[20,40]
加速度范围/(m·s^-2)	[-1,1]
视线角范围/(°)	-15≤λ≤15
最大通信距离/m	3000

表3 在线规划仿真参数

Table 3 Online planning simulation parameters

仿真参数	数值
无人机1初始位置/m	P₁=[ $10000$ ]
无人机2初始位置/m	P₂=[ $000$ ]
无人机3初始位置/m	P₃=[ $- 100 00$ ]
目标初始位置/m	P_T=[ $0100000$ ]
无人机初始速度/(m·s^-1)	30
目标速度大小/(m·s^-1)	30
无人机速度范围/(m·s^-1)	[20,40]
加速度范围/(m·s^-2)	[-1,1]
视线角范围/(°)	-15≤λ≤15
最大通信距离/m	3000

图12 不同方法轨迹对比

Fig.12 Comparison of paths of different methods

图13 不同在线方法定位误差对比

Fig.13 Comparison of positioning errors with different online methods

图14 虚实结合半实物仿真实验平台

Fig.14 Semi-physical simulation experiment platform with combinination of virtuality and reality

图15 三机协同定位在线规划仿真

Fig.15 Simulation of online planning for three-UAV cooperative positioning

图16 无人机控制输出

Fig.16 UAV control outputs

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