基于AVSIMM算法的高超声速再入滑翔目标跟踪

肖楚晗; 李炯; 雷虎民; 王华吉

doi:10.13700/j.bh.1001-5965.2018.0314

基于AVSIMM算法的高超声速再入滑翔目标跟踪

doi: 10.13700/j.bh.1001-5965.2018.0314

1.
空军工程大学研究生学院, 西安 710051
2.
空军工程大学防空反导学院, 西安 710051

基金项目:

国家自然科学基金 61573374

国家自然科学基金 61503408

详细信息

作者简介:
肖楚晗女, 硕士研究生。主要研究方向:临近空间高超声速目标跟踪

李炯男, 博士, 副教授。主要研究方向:导航制导与控制

通讯作者:
李炯, E-mail: graceful1001@126.com

中图分类号: TJ765.1
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- 被引次数: 0
出版历程
- 收稿日期: 2018-05-30
- 录用日期: 2018-08-10
- 网络出版日期: 2019-02-20

Hypersonic reentry gliding target tracking based on AVSIMM algorithm

1.
Master Student College, Air Force Engineering University, Xi'an 710051, China
2.
Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China

Funds:

National Natural Science Foundation of China 61573374

National Natural Science Foundation of China 61503408

More Information

Corresponding author: LI Jiong, E-mail: graceful1001@126.com

摘要

摘要:
针对跟踪高超声速目标的交互式多模型（IMM）算法中存在模型数量过多，模型之间竞争导致滤波精度降低的问题，在自适应网格交互式多模型（AGIMM）算法的基础上，提出了一种自适应变结构交互式多模型（AVSIMM）算法跟踪高超声速再入滑翔目标。根据高超声速无动力再入滑翔目标当前机动状态的角速度参数，在自适应调整当前时刻模型集中参数的同时，针对AGIMM算法运动学模型的单一性，设计了具有多种跟踪滤波运动学模型的AVSIMM算法，通过模型集参数与算法结构的双重自适应调整实现了对目标高精度的跟踪。仿真结果表明，与AGIMM算法相比，所设计的AVSIMM算法不仅对结构和参数都具有更强的自适应性，同时提高了高超目标的跟踪精度和跟踪效率。
- 临近空间 /
- 目标跟踪 /
- 滤波 /
- 自适应变结构交互式多模型(AVSIMM) /
- 自适应网格交互式多模型(AGIMM)算法
Abstract:
Aimed at the decrease of filtering accuracy caused by too many models and competitions between them in interactive multi-model (IMM) algorithm for tracking hypersonic targets, an adaptive variable structure interactive multi-model (AVSIMM) algorithm is proposed based on adaptive grid IMM (AGIMM) algorithm for tracking hypersonic non-powered reentry gliding targets. Based on the angular velocity parameters of the real-time maneuvering state of gliding hypersonic target without power load, AVSIMM algorithm with various dynamitic models is designed to focus on the unicity of models in AGIMM algorithm. AVSIMM algorithm realizes high-precision tracking through adaptive adjustments in both model set parameters and algorithm structure. Simulation results show that, compared with AGIMM algorithm, the designed AVSIMM algorithm not only is more adaptive in structure and parameters but also improves accuracy and efficiency in tracking hypersonic targets.
- near space /
- target tracking /
- filter /
- adaptive variable structure interactive multi-model (AVSIMM) /
- adaptive grid interactive multi-model (AGIMM)

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图 1 AHW目标与基站相对位置示意图

Figure 1. Schematic diagram of relative position of AHW target to base station

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图 2 目标运动真实轨迹

Figure 2. True trajectory of target moving

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图 3 目标真实轨迹与4种算法估计轨迹

Figure 3. True trajectory of target and estimation trajectories in four algorithms

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图 4 目标跟踪位置误差

Figure 4. Position error of target tracking

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图 5 目标速度误差

Figure 5. Velocity error of target tracking

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图 6 位置均方根误差

Figure 6. Root mean square error of position

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图 7 速度均方根误差

Figure 7. Root mean square error of velocity

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表 1 位置、速度估计误差绝对值之和

Table 1. Sum of absolute value of position and velocity estimation error

算法	x方向位置误差/ km	y方向位置误差/ km	x方向速度误差/(km·s^-1)	y方向速度误差/(km·s^-1)
AVSIMMⅠ	14.97	150.44	8.11	27.02
AVSIMMⅡ	20.27	169.79	9.02	34.19
AGIMM	35.05	222.14	34.59	73.63
IMM	45.83	306.13	28.30	185.63

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表 2 位置、速度均方根误差之和及仿真时间

Table 2. Sum of root mean square error of position and velocity and simulation time

算法	位置RMSE/km	速度RMSE/ (km·s^-1)	单次仿真时间/s
AVSIMMⅠ	188.0	34.50	1.47
AVSIMMⅡ	213.70	44.15	1.45
AGIMM	302.79	132.30	1.44
IMM	3 896.73	234.55	4.32

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