高超声速滑翔目标自适应跟踪方法

黄景帅; 李永远; 汤国建; 包为民

doi:10.7527/S1000-6893.2019.23786

航空学报 >

2020 , Vol. 41 >Issue 9: 323786 - 323786

DOI: https://doi.org/10.7527/S1000-6893.2019.23786

电子电气工程与控制

高超声速滑翔目标自适应跟踪方法

黄景帅 ,
李永远 ,
汤国建 ,
包为民

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1. 国防科技大学空天科学学院, 长沙 410073;
2. 中国运载火箭技术研究院, 北京 100076;
3. 中国航天科技集团有限公司, 北京 100048

收稿日期: 2019-12-30

修回日期: 2020-02-07

网络出版日期: 2020-09-29

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Adaptive tracking method for hypersonic glide target

HUANG Jingshuai ,
LI Yongyuan ,
TANG Guojian ,
BAO Weimin

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1. College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China;
2. China Academy of Launch Vehicle Technology, Beijing 100076, China;
3. China Aerospace Science and Technology Corporation, Beijing 100048, China

Received date: 2019-12-30

Revised date: 2020-02-07

Online published: 2020-09-29

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摘要

针对机动模式复杂多变的高超声速滑翔目标跟踪问题，提出了一种机动频率自适应跟踪方法。采用介于常速度和常加速度模型之间的Singer模型来表征目标气动力加速度的变化，从而建立跟踪系统的状态方程。根据地基雷达量测量获得系统的量测方程，鉴于距离和角度信息的量级相差较大将其由球形量测量转换为位置量测量。为了适应高超声速滑翔目标灵活多样的机动模式，基于正交性原理和无迹卡尔曼滤波算法实现了Singer模型中机动频率参数的自适应。利用滤波信息计算得到能够反映状态模型误差大小的调整因子，用于放大Singer模型中的机动频率，进而调整状态方程的过程噪声以降低模型误差。通过对2种典型机动轨迹的跟踪仿真，并与交互式多模型等方法进行比较，结果表明所提方法的跟踪精度高、计算量小，能够较好地适应阶跃机动和连续幅值变化的机动。

关键词： 高超声速滑翔目标; 目标跟踪; Singer模型; 机动频率自适应; 无迹卡尔曼滤波

本文引用格式

黄景帅 , 李永远 , 汤国建 , 包为民 . 高超声速滑翔目标自适应跟踪方法[J]. 航空学报, 2020 , 41(9) : 323786 -323786 . DOI: 10.7527/S1000-6893.2019.23786

Abstract

A tracking approach with adaptive maneuver frequency is proposed in terms of tracking a Hpersonic Glide Target (HGT) with a variety of maneuver modes. The Singer model between the Constant Velocity (CV) and Constant Acceleration (CA) models is employed to represent the change of aerodynamic acceleration, followed by the establishment of a state equation for the tracking system. The measurement equation is then obtained based on the measurements for ground-based radar. In view of significantly different magnitudes between the range and angle, spherical measurements are transformed into position ones. To adapt to flexible and diverse maneuver modes of HGT, the adaptation of maneuver-frequency parameter is achieved in the Singer model based on the orthogonal principle and the Unscented Kalman Filter (UKF). An adjustment factor which can reflect the state model error is calculated via innovation of filtering and used to enlarge the maneuver frequency in the Singer model. The process noise is subsequently modified in the state equation, reducing the model error. Finally, by tracking two typical trajectories with maneuvers and making comparisons with other methods such as the interacting multiple model, the simulation results indicate that the proposed method has high tracking accuracy and little computational cost, and can well adapt to the step maneuver and the continuous maneuver with various intensity.

Key words： hypersonic glide target; target tracking; Singer model; maneuver frequency adaptation; unscented Kalman filter

参考文献

[1] 张远龙. 基于三维剖面的滑翔飞行器弹道规划与制导方法研究[D]. 长沙:国防科技大学, 2018:1-11. ZHANG Y L. Research on entry trajectory generation for hypersonic glide vehicles based on three-dimensional profile[D]. Changsha:National University of Defense Technology, 2018:1-11(in Chinese).
[2] 雍恩米, 钱炜褀, 何开锋. 基于雷达跟踪仿真的滑翔式再入弹道突防性能分析[J]. 宇航学报, 2012, 33(10):1370-1376. YONG E M, QIAN W Q, HE K F. Penetration ability analysis for glide reentry trajectory based on radar tracking[J]. Journal of Astronautics, 2012, 33(10):1370-1376(in Chinese).
[3] ZHANG K, XIONG J J, FU T T. Coupled dynamic model of state estimation for hypersonic glide vehicle[J]. Journal of System Engineering and Electronics, 2018, 29(6):1284-1292.
[4] LI X R, JILKOV V P. Survey of maneuvering target tracking. Part I:Dynamic models[J]. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(4):1333-1364.
[5] 吴楠, 陈磊. 高超声速滑翔再入飞行器弹道估计的自适应卡尔曼滤波[J]. 航空学报, 2013, 34(8):1960-1971. WU N, CHEN L. Adaptive Kalman filtering for trajectory estimation of hypersonic glide reentry vehicles[J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(8):1960-1971(in Chinese).
[6] 李广华. 高超声速滑翔飞行器运动特性分析及弹道跟踪预报方法研究[D]. 长沙:国防科学技术大学, 2016:71-99. LI G H. Motion characteristics analysis and trajectory prediction for hypersonic glide vehicles[D]. Changsha:National University of Defense Technology, 2016:71-99(in Chinese).
[7] 张凯, 熊家军, 韩春耀, 等. 一种基于气动力模型的高超声速滑翔目标跟踪算法[J]. 宇航学报, 2017, 38(2):123-130. ZHANG K, XIONG J J, HAN C Y, et al. A tracking algorithm of hypersonic glide reentry vehicle via aerodynamic model[J]. Journal of Astronautics, 2017, 38(2):123-130(in Chinese).
[8] 王国宏, 李俊杰, 张翔宇, 等. 临近空间高超声速滑跃式机动目标的跟踪模型[J]. 航空学报, 2015, 36(7):2400-2410. WANG G H, LI J J, ZHANG X Y, et al. A tracking model for near space hypersonic slippage leap maneuvering target[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(7):2400-2410(in Chinese).
[9] 李凡, 熊家军. 临近空间高超声速跳跃滑翔式目标自适应跟踪模型[J]. 航空学报, 2018, 39(12):322355. LI F, XIONG J J. Adaptive tracking model for near space hypersonic jumping gliding target[J]. Acta Aeronautica et Astronautica Sinica, 2018, 39(12):322355(in Chinese).
[10] 张凯, 熊家军, 付婷婷, 等. 高超声速滑翔导弹气动参数自适应跟踪建模[J]. 国防科技大学学报, 2019, 41(1):101-107. ZHANG K, XIONG J J, FU T T, et al. Aerodynamic parametric modeling of hypersonic gliding missile for adaptive tracking[J]. Journal of National University of Defense Technology, 2019, 41(1):101-107(in Chinese).
[11] 肖楚晗, 李炯, 雷虎民, 等. 基于AVSIMM算法的高超声速再入滑翔目标跟踪[J]. 北京航空航天大学学报, 2019, 45(2):413-421. XIAO C H, LI J, LEI H M, et al. Hypersonic non-powered reentry gliding target tracking based on AVSIMM algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(2):413-421(in Chinese).
[12] 何睿智. 高超声速助推滑翔飞行器全程弹道规划方法研究[D]. 长沙:国防科技大学, 2017:35-49. HE R Z. Study of all-course trajectory planning approach for hypersonic boost-glide vehicles[D]. Changsha:National University of Defense Technology, 2017:35-49(in Chinese).
[13] MEHRA R K. Approaches to adaptive filtering[J]. IEEE Transactions on Automatic Control, 1972, 17(5):693-698.
[14] 刘畅, 杨锁昌, 汪连栋, 等. 基于自适应强跟踪CQKF的目标跟踪算法[J]. 北京航空航天大学学报, 2018, 44(5):982-990. LIU C, YANG S C, WANG L D, et al. Target tracking algorithm based on adaptive strong tracking CQKF[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(5):982-990(in Chinese).
[15] WANG N, LI L Y, WANG Q. Adaptive UKF-based parameter estimation for Bouc-Wen model of magnetorheological and elastomer materials[J]. Journal of Aerospace Engineering, 2019, 32(1):0401830.
[16] YUAN Y X, GAO W G. An optimal adaptive Kalman filter[J]. Journal of Geodesy, 2006, 80(4):177-183.
[17] HUANG Y L, ZHANG Y G, WU Z M, et al. A novel adaptive Kalman filter with inaccurate process and measurement noise covariance matrices[J]. IEEE Transactions on Automatic Control, 2018, 63(2):594-601.
[18] ZHOU D H, FRANK P M. Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise:Application to parameter estimation and empirical robustness analysis[J]. International Journal of Control, 1996, 65(2):295-307.
[19] WANG Y D, SUN S M, LI L. Adaptively robust unscented Kalman filter for tracking a maneuvering vehicle[J]. Journal of Guidance, Control, and Dynamics, 2014, 37(5):1696-1701.
[20] 崔乃刚, 张龙, 王小刚, 等. 自适应高阶容积卡尔曼滤波在目标跟踪中的应用[J]. 航空学报, 2015, 36(12):3885-3895. CUI N G, ZHANG L, WANG X G, et al. Application of adaptive high-degree cubature Kalman filter in target tracking[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(12):3885-3895(in Chinese).
[21] JIANG Y Z, MA P B, BAOYIN H X. Residual-normalized strong tracking filter for tracking a noncooperative maneuvering spacecraft[J]. Journal of Guidance, Control, and Dynamics, 2019, 42(10):2304-2309.
[22] ZHANG H W, XIE J W, GE J A, et al. Strong tracking SCKF based on adaptive CS model for manoeuvring aircraft tracking[J]. IET Radar, Sonar & Navigation, 2018, 12(7):742-749.
[23] 蒋冬婷, 宁静, 万洪容. 基于似然函数的自适应Singer模型滤波算法[J]. 西南师范大学学报(自然科学版), 2019, 44(1):89-94. JIANG D T, NING J, WAN H R. An adaptive Singer model filter based on likelihood function[J]. Journal of Southwest China Normal University (Natural Science Edition), 2019, 44(1):89-94(in Chinese).
[24] LI X R, JILKOV V P. Survey of maneuvering target tracking. part Ⅱ:Motion models of ballistic and space targets[J]. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(1):96-119.
[25] SINGER R A. Estimating optimal tracking filter performance for manned maneuvering targets[J]. IEEE Transactions on Aerospace and Electronic Systems, 1970, 6(4):473-483.
[26] 赵琳. 非线性系统滤波理论[M]. 北京:国防工业出版社, 2012:52-134. ZHAO L. Nonlinear system filtering theory[M]. Beijing:National Defense Industry Press, 2012:52-134(in Chinese).
[27] ZHOU H R, KUMAR K S P. A "current" statistical model and adaptive algorithm for estimating maneuvering targets[J]. Journal of Guidance, Control, and Dynamics, 1984, 7(5):596-602.
[28] LI X R, JILKOV V P. Survey of maneuvering target tracking. part V:Multiple-model methods[J]. IEEE Transactions on Aerospace and Electronic Systems, 2005, 41(4):1255-1321.

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