临近空间高超声速多目标检测前跟踪算法

doi:10.7527/S1000-6893.2021.25299

电子电气工程与控制

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

临近空间高超声速多目标检测前跟踪算法

薄钧天, 王国宏, 于洪波, 张翔宇

海军航空大学信息融合研究所, 烟台 264001

收稿日期:2021-01-20 修回日期:2021-03-14 发布日期:2022-06-01
通讯作者: 薄钧天 E-mail:752284662@qq.com
基金资助:
国家自然科学基金（61731023，61701519，61671462，61971432）；山东省自然科学基金（ZR2020MF015）

Track-before-detection algorithm for multiple hypersonic targets in near space

BO Juntian, WANG Guohong, YU Hongbo, ZHANG Xiangyu

Institute of Information Fusion, Naval Aeronautical University, Yantai 264001, China

Received:2021-01-20 Revised:2021-03-14 Published:2022-06-01
Supported by:
National Natural Science Foundation of China (61731023,61701519,61671462,61971432);Shandong Provincial Natural Science Foundation (ZR2020MF015)

摘要/Abstract

摘要： 针对临近空间不同径向距离高超声速目标难以同时被有效检测的问题，提出一种通过峰值聚优改进Hough变换积累结果的检测前跟踪（TBD）算法。采用径向距离-时间坐标描述数据，减少量测误差影响，规格化坐标使2个维度处于同一量级。进行Hough变换，分割参数单元进行点数积累和能量积累，采用标签矩阵记录每个量测点曲线经过的参数单元，遍历所有量测点将每个量测点只存于其所能构成能量积累值最大的参数单元，得到新的点数积累和能量积累结果。只对点数积累空间设置门限提取目标航迹，进行航迹约束和合并，输出最终航迹。仿真结果显示，算法将3个目标全部检测出的概率可达到90%，具有较好的多目标检测性能。

关键词: 临近空间, 高超声速目标, 峰值聚优, Hough变换, 检测前跟踪, 多目标

Abstract: To overcome the problem that hypersonic targets with different radial distances in near space are difficult to be effectively detected at the same time, this paper proposes a Track-Before-Detect (TBD) algorithm, which improves the accumulation of Hough transform by peak convergence. First, the radial distance-time coordinate is used to describe the data to reduce the influence of measurement errors, and the normalized coordinate allows the two dimensions to be at the same order of magnitude. Hough transform is carried out, and the parameter unit is divided for point accumulation and energy accumulation. The label matrix is used to record the parameter units that each measurement point curve passes through, and all measurement points are traversed, and each measurement point is stored only in its largest parameter unit of the energy accumulation value. New points accumulation and energy accumulation results are then obtained. The threshold is only set for the point accumulation space to extract the target track, and track constraints and merge are performed to output the final track. The simulation results show that the algorithm proposed can detect all three targets with a probability of 90%, demonstrating good multi-target detection performance.

Key words: near space, hypersonic target, peak convergence, Hough transform, track-before-detect, multiple targets

中图分类号:

V243.2
TN957

薄钧天, 王国宏, 于洪波, 张翔宇. 临近空间高超声速多目标检测前跟踪算法[J]. 航空学报, 2022, 43(5): 325299-325299.

BO Juntian, WANG Guohong, YU Hongbo, ZHANG Xiangyu. Track-before-detection algorithm for multiple hypersonic targets in near space[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(5): 325299-325299.

参考文献

[1] 叶喜发, 张欧亚, 李新其, 等. 国外高超声速巡航导弹的发展情况综述[J]. 飞航导弹, 2019(2):65-68. YE X F, ZHANG O Y, LI X Q, et al.Views of the development of hypersonic cruise missile abroad[J]. Aerodynamic Missile Journal, 2019(2):65-68(in Chinese).
[2] 王李波, 马春娥. 临近空间高超声速目标电磁散射特性分析[J]. 电子世界, 2018(5):68-69. WANG L B, MA C E.Analysis of electromagnetic scattering characteristics of hypersonic targets in nearby space[J]. Electronics World, 2018(5):68-69(in Chinese).
[3] BI X, DU J S, ZHANG Q S, et al. Improved multi-target radar TBD algorithm[J]. Journal of Systems Engineering and Electronics, 2015, 26(6):1229-1235.
[4] YI W, MORELANDE M R, KONG L J, et al. An efficient multi-frame track-before-detect algorithm for multi-target tracking[J]. IEEE Journal of Selected Topics in Signal Processing, 2013, 7(3):421-434.
[5] YI W, MORELANDE M R, KONG L J, et al. A computationally efficient particle filter for multitarget tracking using an independence approximation[J]. IEEE Transactions on Signal Processing, 2013, 61(4):843-856.
[6] CARLSON B D, EVANS E D, WILSON S L. Search radar detection and track with the Hough transform. I. system concept[J]. IEEE Transactions on Aerospace and Electronic Systems, 1994, 30(1):102-108.
[7] CARLSON B D, EVANS E D, WILSON S L. Search radar detection and track with the Hough transform. II. detection statistics[J]. IEEE Transactions on Aerospace and Electronic Systems, 1994, 30(1):109-115.
[8] CARLSON B D, EVANS E D, WILSON S L. Search radar detection and track with the Hough transform. III. Detection performance with binary integration[J]. IEEE Transactions on Aerospace and Electronic Systems, 1994, 30(1):116-125.
[9] MOYER L R, SPAK J, LAMANNA P. A multi-dimensional Hough transform-based track-before-detect technique for detecting weak targets in strong clutter backgrounds[J]. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(4):3062-3068.
[10] 王国宏, 李林, 于洪波. 基于点集合并的修正Hough变换TBD算法[J]. 航空学报, 2017, 38(1):320009. WANG G H, LI L, YU H B. A modified Hough transform TBD algorithm based on point set merging[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(1):320009(in Chinese).
[11] 张传宾. 强杂波下多目标航迹起始算法研究[D]. 哈尔滨:哈尔滨工程大学, 2018. ZHANG C B. Research on the multi-target track initiation under heavy clutter[D]. Harbin:Harbin Engineering University, 2018(in Chinese).
[12] 裴家正, 黄勇, 董云龙, 等. 改进的SMC-CBMeMBer前向后向平滑检测前跟踪算法[J]. 通信学报, 2019, 40(8):102-113. PEI J Z, HUANG Y, DONG Y L, et al. Improved SMC cardinality-balanced multi-Bernoulli forward-backward smoothing track-before-detect algorithm[J]. Journal on Communications, 2019, 40(8):102-113(in Chinese).
[13] 张奕群, 尹立凡, 王硕, 等. 一种改进的直方图概率多假设多目标跟踪方法[J]. 航空学报, 2021, 42(11):524851. ZHANG Y Q, YIN L F, WANG S, et al. An improvedhistogram PMHT multi-target tracking method[J]. Acta Aeronautica et Astronautica Sinica, 2021, 42(11):524851(in Chinese).
[14] 田瑞琦, 林财永, 鲍庆龙, 等. 强目标掩盖下雷达微弱目标检测算法[J]. 系统工程与电子技术, 2017, 39(1):64-70. TIAN R Q, LIN C Y, BAO Q L, et al. Detection algorithm for radar weak target with strong target coverage[J]. Systems Engineering and Electronics, 2017, 39(1):64-70(in Chinese).
[15] 何友, 修建娟, 张晶炜. 雷达数据处理及应用[M]. 第2版. 北京:电子工业出版社, 2009. HE Y, XIU J J, ZHANG J W. Radar data processing with applications[M]. 2nd ed. Beijing:Publishing House of Electronics industry, 2009(in Chinese).
[16] 丁鹭飞, 耿富录, 陈建春. 雷达原理[M]. 第5版. 北京:电子工业出版社, 2014. DING L F, GENG F L, CHEN J C. Radar principles[M]. 5th ed. Beijing:Publishing House of Electronics industry, 2014(in Chinese).
[17] LI L, WANG G H, ZHANG X Y, et al. Adaptive real-time recursive radial distance-time plane Hough transform track-before-detect algorithm for hypersonic target[J]. IET Radar, Sonar & Navigation, 2020, 14(1):138-146.
[18] 王国宏, 李岳峰, 于洪波, 等. 三维空间中高超声速目标修正三级Hough变换-检测前跟踪算法[J]. 电子与信息学报, 2018, 40(4):890-897. WANG G H, LI Y F, YU H B, et al. Modifiedtriple-stage Hough transform track-before-detect algorithm in three-dimensional space for hypersonic target[J]. Journal of Electronics & Information Technology, 2018, 40(4):890-897(in Chinese).
[19] 孔敏.天波超视距雷达目标跟踪技术研究[D].烟台:海军航空工程学院,2007. KONG M.Research on target tracking technology for over-the-horizon radar[D].Yantai:Naval Aeronautical and Astronautical University,2007(in Chinese)
[20] 赵志超, 饶彬, 王雪松, 等. 基于概率网格Hough变换的多雷达航迹起始算法[J]. 航空学报, 2010, 31(11):2209-2215. ZHAO Z C, RAO B, WANG X S, et al. Multi-radartrack initiation algorithm based on probabilistic grid Hough transform[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(11):2209-2215(in Chinese).
[21] YU H B, WANG G H, WU W, et al. A novel RHT-TBD approach for weak targets in HPRF radar[J]. Science China Information Sciences, 2016, 59(12):1-14.
[22] CHEN J, LEUNG H, LO T, et al. A modified probabilistic data association filter in a real clutter environment[J]. IEEE Transactions on Aerospace and Electronic Systems, 1996, 32(1):300-313.
[23] 李林, 王国宏, 于洪波, 等. 一种临近空间高超声速目标检测前跟踪算法[J]. 宇航学报, 2017, 38(4):420-427. LI L, WANG G H, YU H B, et al. A TBDalgorithm for near space hypersonic target[J]. Journal of Astronautics, 2017, 38(4):420-427(in Chinese).

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

临近空间高超声速多目标检测前跟踪算法

Track-before-detection algorithm for multiple hypersonic targets in near space

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	梁超, 杨力, 潘成胜, 戚耀文. 卫星网络动态资源图多QoS约束路由算法[J]. 航空学报, 2023, 44(1): 326422-326422.
[2]	邹子缘, 陈琪锋. 基于决策树搜索的空间飞行器集群对抗目标分配方法[J]. 航空学报, 2022, 43(S1): 726910-726910.
[3]	孙刚, 彭双, 陈浩, 伍江江, 李军. 面向测控数传资源一体化场景的卫星地面站资源多目标优化方法[J]. 航空学报, 2022, 43(9): 326114-326114.
[4]	郑帅, 王子涵, 赵浩然, 杨朋涛, 洪军. 基于差分进化算法的飞机油量传感器布局优化方法[J]. 航空学报, 2022, 43(8): 125809-125809.
[5]	薄钧天, 王国宏, 于洪波, 彭志刚. 基于平行线坐标变换的检测前跟踪算法[J]. 航空学报, 2022, 43(8): 325644-325644.
[6]	林鹏, 庄福建, 曲林锋, 许阳阳, 苏亚东. 高超声速飞机尾喷管设计-制造与验证技术发展综述[J]. 航空学报, 2022, 43(6): 526160-526160.
[7]	薄钧天, 王国宏, 于洪波, 张翔宇. 临近空间伴有尾流高超声速目标检测定位算法[J]. 航空学报, 2022, 43(5): 325255-325255.
[8]	夏存言, 张刚, 耿云海. 共面单脉冲拦截多目标问题[J]. 航空学报, 2022, 43(3): 325093-325093.
[9]	荆涛, 田锡天. 基于蒙特卡洛-自适应差分进化算法的飞机容差分配多目标优化方法[J]. 航空学报, 2022, 43(3): 425278-425278.
[10]	靳标, 邝晓飞, 彭宇, 张贞凯. 基于合作博弈的组网雷达分布式功率分配方法[J]. 航空学报, 2022, 43(1): 324776-324776.
[11]	罗庆, 张涛, 单鹏, 张文涛, 刘子豪. 基于改进Q学习的IMA系统重构蓝图生成方法[J]. 航空学报, 2021, 42(8): 525792-525792.
[12]	李冠雄, 王靖宇, 王运涛. 低压储能的升浮一体飞行器总体参数研究[J]. 航空学报, 2021, 42(7): 224438-224438.
[13]	张军峰, 游录宝, 杨春苇, 胡荣. 基于多目标帝国竞争算法的进场排序与调度[J]. 航空学报, 2021, 42(6): 324439-324439.
[14]	孙刚, 陈浩, 彭双, 杜春, 李军. 一种基于偏好MOEA的卫星地面站资源多目标优化算法[J]. 航空学报, 2021, 42(4): 524475-524475.
[15]	何程, 马东立, 贾玉红, 杨穆清, 陈刚. 联翼布局传感器飞机多目标优化设计[J]. 航空学报, 2021, 42(12): 224761-224761.