Information Fusion

Composite guidance technology based on active radar/infrared information fusion

  • CHEN Linxiu ,
  • YANG Xiangyu ,
  • ZHANG Hang ,
  • ZHAO Jiajia ,
  • HAO Mingrui
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  • 1. Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory, Beijing 100074, China

Received date: 2022-02-21

  Revised date: 2022-04-11

  Online published: 2022-05-23

Abstract

To improve the target tracking accuracy and anti-jamming performance of the active radar/infrared composite guidance system in complex environments and take full advantage of its observation data, this paper proposes an information fusion scheme based on state-angle joint estimation. Under long distance conditions, the volume Kalman filter algorithm, chi-square distribution theory and information fusion algorithm are used to complete aircraft-target relative state estimation, sensor disturbance state judgment, and target consistency correlation and fusion. Under the condition of close range, angle filtering correction and angle fusion estimation are completed based on the Kalman filter algorithm. The simulation results show that the scheme and algorithm proposed can effectively eliminate false information, and can reliably obtain stable and high-precision guidance information when sensor information is missing. The results can provide a basis for confrontation decision-making in complex environments and precise strikes against targets.

Cite this article

CHEN Linxiu , YANG Xiangyu , ZHANG Hang , ZHAO Jiajia , HAO Mingrui . Composite guidance technology based on active radar/infrared information fusion[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022 , 43(S1) : 727058 -727058 . DOI: 10.7527/S1000-6893.2022.27058

References

[1] SUN H, LIU X G. Development trend of guidance technology for future anti-ship missile [J]. Aerodynamic Missile Journal, 2020(3): 88-91 (in Chinese). 孙航, 刘晓光. 未来反舰导弹的制导技术发展趋势[J]. 飞航导弹, 2020(3): 88-91.
[2] LIU Y, YANG J, ZHU J, et al. Review of anti-ship missile guidance technologies[J]. Computer Simulation, 2016, 33(2): 10-16 (in Chinese). 刘永, 杨健, 朱剑, 等. 反舰导弹制导技术发展综述[J]. 计算机仿真, 2016, 33(2): 10-16.
[3] SUN S J. Active radar/infrared imaging guidance anti-interference technology[J]. Ship Electronic Engineering, 2016, 36(2): 61-63, 82 (in Chinese). 孙少军. 主动雷达/红外成像复合制导抗干扰技术[J]. 舰船电子工程, 2016, 36(2): 61-63, 82.
[4] BAI S, WEI X. Research on jamming method against radar/infrared imaging composite guidance anti-ship missile[J]. Command Control & Simulation, 2020, 42(4): 117-122 (in Chinese). 白爽, 卫鑫. 雷达/红外成像复合制导反舰导弹干扰方法[J]. 指挥控制与仿真, 2020, 42(4): 117-122.
[5] LIU Z, ZHANG N, WU X Y. Development status and trend of multi-mode compound seeker[J]. Aerodynamic Missile Journal, 2019(10): 90-96 (in Chinese). 刘箴, 张宁, 吴馨远. 多模复合导引头发展现状及趋势[J]. 飞航导弹, 2019(10): 90-96.
[6] SUN J, YU Y M, SUN C M. Development analysis of multimode compound guidance technology and equipment[J]. Guidance and Fuze, 2005, 26(3): 5-10 (in Chinese). 孙静, 于艳梅, 孙昌民. 多模复合制导技术与装备发展分析[J]. 制导与引信, 2005, 26(3): 5-10.
[7] WANG Z, ZHANG J, XIONG W, et al. Research on state estimation and optimal control of active radar homing guidance based on EKF[J]. Astronautical Systems Engineering Technology, 2018, 2(3): 46-50 (in Chinese). 王智, 张婕, 熊伟, 等. 基于EKF的主动雷达寻的制导状态估计与最优控制研究[J]. 宇航总体技术, 2018, 2(3): 46-50.
[8]
[9] LI S G, LI Y, ZHI X, et al. A distributed information fusion concept for radar and IR combined guidance system[J]. Fire Control Radar Technology, 2021, 50(1): 81-85, 93 (in Chinese). 李时光, 李云, 职晓, 等. 一种分布式雷达/红外复合制导信息融合方案[J]. 火控雷达技术, 2021, 50(1): 81-85, 93.
[10]
[11] ZHANG C, HE F S, ZHENG S Y, et al. Central currency structure of radar and IRST complex tracking[J]. Command Control & Simulation, 2021, 43(1): 97-102 (in Chinese). 张存, 贺丰收, 郑世友, 等. 战斗机群集中式雷达/红外复合跟踪通用架构[J]. 指挥控制与仿真, 2021, 43(1): 97-102.
[12] ZHANG L Z, WANG B B, ZHANG H. Expectation maximization cubature Kalman filter based on radar/infrared measurement[J]. Journal of Nanjing University of Science and Technology, 2020, 44(5): 624-630 (in Chinese). 张连仲, 王宝宝, 张辉. 基于雷达/红外测量的期望最大化容积卡尔曼滤波[J]. 南京理工大学学报, 2020, 44(5): 624-630.
[13] ZHANG W S, ZHANG A Q, QI H M. Multi-target tracking algorithm based on radar-infrared distributed fusion[J]. Radio Engineering, 2020, 50(9): 769-774 (in Chinese). 张万顺, 张安清, 齐海明. 雷达-红外分布式融合多目标跟踪算法[J]. 无线电工程, 2020, 50(9): 769-774.
[14] SU B Z, MU R J, LONG T, et al. Performance evaluation of HCKF and its application in transfer alignment[J]. Journal of Astronautics, 2019, 40(11): 1313-1321 (in Chinese). 苏炳志, 穆荣军, 龙腾, 等. HCKF性能评估及其在传递对准中的应用[J]. 宇航学报, 2019, 40(11): 1313-1321.
[15] WU P L, LI X X, ZHANG L Z, et al. Tracking algorithm with radar and infrared sensors using a novel adaptive grid interacting multiple model[J]. IET Science, Measurement & Technology, 2014, 8(5): 270-276.
[16] ZHANG A Q, ZHANG W S, QI H M. Multi-target tracking algorithm of centralized rader-infrared sensor data fusion[J]. Shipboard Electronic Countermeasure, 2020, 43(4): 86-90 (in Chinese). 张安清, 张万顺, 齐海明. 集中式雷达-红外传感器数据融合多目标跟踪算法[J]. 舰船电子对抗, 2020, 43(4): 86-90.
[17] ARASARATNAM I, HAYKIN S. Cubature Kalman filters[J]. IEEE Transactions on Automatic Control, 2009, 54(6): 1254-1269.
[18] ARASARATNAM I. Sensor fusion with square-root cubature information filtering[J]. Intelligent Control and Automation, 2013, 4(1): 11-17.
[19] ZHU J, LIU B C, WANG H X, et al. State estimation based on improved cubature Kalman filter algorithm[J]. IET Science, Measurement & Technology, 2020, 14(5): 536-542.
[20] SUN F, TANG L J. Estimation precision comparison of Cubature Kalman filter and Unscented Kalman filter[J]. Control and Decision, 2013, 28(2): 303-308, 312 (in Chinese). 孙枫, 唐李军. Cubature卡尔曼滤波与Unscented卡尔曼滤波估计精度比较[J]. 控制与决策, 2013, 28(2): 303-308, 312.
[21] XU B, ZHANG P, WEN H Z, et al. Stochastic stability and performance analysis of Cubature Kalman Filter[J]. Neurocomputing, 2016, 186: 218-227.
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