基于特征匹配的舰载对陆导弹目标识别模型

doi:10.12305/j.issn.1001-506X.2021.08.26

Abstract

Abstract:

Aiming at the problem that traditional forward-looking template matching algorithm is difficult to identify and track targets such as buildings directly, a target recognition model for land missiles based on feature matching is proposed. Through prepocessing of images of terminal guidance seeker, the model takes advantage of the improved YOLOv3 deep learning target detection algorithm and Deeplabv3+deep learning semantic segmentation algorithm to recognize the target area and the smoke area. Parallel method is used to eliminate the interference of smoke occlusion on the target recognition. Finally, the discriminant analysis rule is used to judge whether the model is successfully identified. The simulation experiment results show that the model can recognize the land target quickly, effectively and accurately, which has good anti-smoke interference ability. It helps to improving the level of target recognition and combat effectiveness of the land missile.

Key words: feature matching, deep learning, automatic target recognition, land missiles, smoke jamming

CLC Number:

Chunsi XIE, Zhiying LIU, Yu SANG. Target recognition model of ship-to-land missile based on feature matching[J]. Systems Engineering and Electronics, 2021, 43(8): 2244-2253.

Figures/Tables 19

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References 30

1	KADA B , ANSARI U , BAJODAH A H . Highly maneuvering target interception via robust generalized dynamic inversion homing guidance and control[J]. Aerospace Science and Technology, 2020, 99, 105749. doi: 10.1016/j.ast.2020.105749
2	UZAIR A , ABDULRAHMAN H , BAJODAH B K . Nonlinear robust generalized dynamic inversion based homing guidance and control of aerial interceptors[J]. IFAC PapersOnLine, 2019, 52 (12): 219- 226. doi: 10.1016/j.ifacol.2019.11.246
3	王建华, 刘鲁华, 王鹏, 等. 带三维落角约束的寻的导弹制导与姿控系统设计[J]. 国防科技大学学报, 2017, 39 (1): 30- 39.
	WANG J H , LIU L H , WANG P , et al. Guidance and control system design for homing missiles with three dimensional impact angle constraints[J]. Journal of National University of Defense Technology, 2017, 39 (1): 30- 39.
4	徐东, 杨健, 徐亚范. 基于机器学习的SAR图像目标识别方法研究[J]. 微电子学与计算机, 2004, (7): 110- 111, 146. doi: 10.3969/j.issn.1000-7180.2004.07.029
	XU D , YANG J , XU Y F . Method and study of machine learning based SAR image target recognition[J]. Microelectronics & Computer, 2004, (7): 110- 111, 146. doi: 10.3969/j.issn.1000-7180.2004.07.029
5	刘志赢, 谢春思, 李进军, 等. 基于改进YOLOv3的对陆导弹目标识别算法[J]. 战术导弹技术, 2021, 4 (2): 127- 134.
	LIU Z Y , XIE C S , LI J J , et al. Land-attack missile target recognition algorithm based on improved YOLOv3[J]. Tactical Missile Technology, 2021, 4 (2): 127- 134.
6	刘云峰, 杨小冈, 齐乃新, 等. 基于模板匹配的前视自动目标识别模型[J]. 兵工自动化, 2016, 35 (7): 4- 6. doi: 10.7690/bgzdh.2016.07.002
	LIU Y F , YANG X G , QI N X , et al. Forward-looking ATR model based on template matching[J]. Ordnance Industry Automation, 2016, 35 (7): 4- 6. doi: 10.7690/bgzdh.2016.07.002
7	张冬青, 张纯学. 导弹自动目标识别技术发展及应用研究[J]. 航天电子对抗, 2008, 24 (1): 4- 6. doi: 10.3969/j.issn.1673-2421.2008.01.002
	ZHANG D Q , ZHANG C X . Development and application of missile ATR technology[J]. Aerospace Electronic Warfare, 2008, 24 (1): 4- 6. doi: 10.3969/j.issn.1673-2421.2008.01.002
8	WANG S C , WANG H , ZHOU Y L , et al. Automatic laser profile recognition and fast tracking for structured light measurement using deep learning and template matching[J]. Measurement, 2021, 169, 108362. doi: 10.1016/j.measurement.2020.108362
9	ALOM M Z , HASAN M , YAKOPCIC C , et al. Inception recurrent convolutional neural network for object recognition[J]. Object Recognition, 2021, 32 (1): 1704- 1721. doi: 10.1007/s00138-020-01157-3
10	AN F P , LIU J E , BAI L . Object recognition algorithm based on optimized nonlinear activation function-global convolutional neural network[J]. The Visual Computer, 2021, 3 doi: 10.1007/S00371-020-02033-X
11	HU H, GU J Y, ZHANG Z, et al. Relation networks for object detection[C]//Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2018.
12	张冬青, 张纯学, 文苏丽. 自动目标识别技术在导弹上的应用研究[J]. 战术导弹技术, 2010, (5): 1- 6.
	ZHANG D Q , ZHANG C X , WEN S L . Research on the application of automatic target recognition on missile[J]. Tactical Missile Technology, 2010, (5): 1- 6.
13	梁杰, 李磊, 任君, 等. 基于深度学习的红外图像遮挡干扰检测方法[J]. 兵工学报, 2019, 40 (7): 1401- 1410. doi: 10.3969/j.issn.1000-1093.2019.07.009
	LIANG J , LI L , REN J , et al. Infrared image occlusion interference detection method based on deep learning[J]. Acta Armamentarii, 2019, 40 (7): 1401- 1410. doi: 10.3969/j.issn.1000-1093.2019.07.009
14	刘志赢, 谢春思, 李进军, 等. Cascade R-CNN和YOLOv3在导弹目标识别中的应用[J]. 图像与信号处理, 2020, 9 (2): 102- 110.
	LIU Z Y , XIE C S , LI J J , et al. Application of cascade R-CNN and YOLOv3 in missile target recognition[J]. Journal of Image and Signal Processing, 2020, 9 (2): 102- 110.
15	LIU W, ANGUELOV D, ERHAN D, et al. SSD: single shot multi-box detector[C]//Proc. of the European Conference on Computer Vision, 2016.
16	REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: unified, real-time object detection[C]//Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2015.
17	REDMON J, FAEHADIA. YOLOV3: an incremental improvement[EB/OL]. [2020-08-05]. https://pjreddie.com/media/files/papers/YOLOV3.pdf.
18	ZHOU X, WANG D, KRAHENBUHL P. Objects as points[EB/OL]. [2020-08-05]. https://arxiv.org/abs/1904.07850v1.
19	齐航, 袁健全, 李磊, 等. 基于深度学习的红外烟幕区域分割技术[J]. 控制与信息技术, 2019, (4): 18- 22, 57.
	QI H , YUAN J Q , LI L , et al. A method of smoke area segmentation for infrared images based on deep learning[J]. Control and Information Technology, 2019, (4): 18- 22, 57.
20	LIU T , CHENG J H , DU X Y , et al. Video smoke detection method based on change-cumulative image and fusion deep network[J]. Sensors, 2019, 19 (23): 5060. doi: 10.3390/s19235060
21	袁飞, 赵绪言, 王一戈, 等. 基于轻量级卷积神经网络的烟雾识别算法[J]. 西南交通大学学报, 2020, 55 (5): 1111- 1116, 1132.
	YUAN F , ZHAO X Y , WANG Y G , et al. Smoke recognition algorithm based on lightweight convolutional neural network[J]. Journal of Southwest Jiaotong University, 2020, 55 (5): 1111- 1116, 1132.
22	王文朋, 毛文涛, 何健, 等. 基于深度迁移学习的烟雾识别方法[J]. 计算机应用, 2017, 37 (11): 3176- 3181, 3193.
	WANG W P , MAO W T , HE J , et al. Smoke recognition based on deep transfer learning[J]. Journal of Computer Applications, 2017, 37 (11): 3176- 3181, 3193.
23	汪梓艺, 苏育挺, 刘艳艳, 等. 一种改进DeeplabV3网络的烟雾分割算法[J]. 西安电子科技大学学报, 2019, 46 (6): 52- 59.
	WANG Z Y , SU Y T , LIU Y Y , et al. Algorithm for segmentation of smoke using the improved DeeplabV3 network[J]. Journal of Xidian University, 2019, 46 (6): 52- 59.
24	HONG J S , SOO H C , JAE Y C , et al. A high image quality organic light-emitting diode display with motion blur reduction for ultrahigh resolution and premium TVs[J]. Journal of the Society for Information Display, 2020, 28 (6): 557- 565. doi: 10.1002/jsid.919
25	LIU Z Y, XIE C S, LI J J, et al. Canny edge detection algorithm based on improved sequential statistical filter[C]//Proc. of the IEEE 39th Conference on Chinese Control Conference, 2020.
26	LI T J , YUAN Y , ZHANG B , et al. Experimental verification of three dimensional temperature field reconstruction method based on Lucy-Richardson and nearest neighbor filtering joint deconvolution algorithm for flame light field imaging[J]. Applied Thermal Engineering, 2019, 162 (5): 114235.
27	ZHANG X H , KANG J S , ZHAO J M , et al. Enhanced fault diagnosis of bearings in gearbox based on Lucy-Richardson deconvolution and discussion[J]. Applied Mechanics and Materials, 2015, 764-765, 264- 268. doi: 10.4028/www.scientific.net/AMM.764-765.264
28	孔方方, 宋蓓蓓. 改进YOLOv3的全景交通监控目标检测[J]. 计算机工程与应用, 2020, 56 (8): 20- 25.
	KONG F F , SONG B B . Improved YOLOv3 panoramic traffic monitoring target detection[J]. Computer Engineering and Applications, 2020, 56 (8): 20- 25.
29	刘志赢, 谢春思, 李进军, 等. 基于改进Deeplabv3+的烟雾区域分割识别算法[J]. 系统工程与电子技术, 2021, 43 (2): 328- 335.
	LIU Z Y , XIE C S , LI J J , et al. Smoke region segmentation recognition algorithm based on improved Deeplabv3+[J]. Systems Engineering and Electronics, 2021, 43 (2): 328- 335.
30	LIU G , LIU S , LIANG L K , et al. Scene matching for infrared and visible images with compressive sensing SIFT feature representation in bandelet domain[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2020, 34 (11): 2054029. doi: 10.1142/S0218001420540294

迭代次数	PPMCC	FPS	迭代次数	PPMCC	FPS
1	0.882	410	32	0.958	25
2	0.887	292	64	0.970	13
4	0.900	172	128	0.973	8.3
8	0.921	55	256	0.960	3.1
16	0.941	47	512	0.921	1.6

模型	P/%	R/%	γ/%	γ＞1比率	FPS	内存/MB
本文	79.8	66.7	27.4	0	9.73	437
NProd	75.2	61.9	24.3	0	13.34	小于10

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Target recognition model of ship-to-land missile based on feature matching

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