激光成像引信的目标识别方法研究

周瑜; 贺伟

doi:doi:10.7510/jgjs.issn.1001-3806.2023.02.017

激光技术, 2023, 47 (2): 267, 网络出版: 2023-04-12

激光成像引信的目标识别方法研究

Target recognition method of laser imaging fuze

论文大纲

周瑜贺伟

作者单位

西安邮电大学通信与信息工程学院, 西安 710100

摘要

为了高效准确地滤掉云烟雾等悬浮粒子, 减少对激光成像引信工作的影响, 采用了改进的Harris+最小核值相似区域（SUSAN）角点检测算法与矩形度结合的目标识别方法。改进算法在原有Harris和SUSAN算法基础上, 利用8邻域模板标准差对目标像素点进行初次筛选获得候选角点, 经高斯滤波后, 利用改进的角点响应函数值进行二次筛选, 再通过非极大值抑制得到最终角点, 最后利用矩形度对目标与干扰进行二次区分。通过理论分析和实验验证可知, 95%的目标能被有效地识别出来。结果表明, 该方法能高效准确地区分目标与干扰, 同时满足实时性要求, 为激光成像引信抗干扰方面提供了一定的理论参考。

Abstract

In order to efficiently and accurately filter out the influence of suspended particles such as cloud smoke on laser imaging fuze,a target recognition method based on the combination of improved Harris+ smallest univalue segment assimilating nucleus (SUSAN) corner detection algorithm and rectangularity was proposed. Based on the original Harris and SUSAN algorithms, the 8-neighborhood template standard deviation was used to perform the initial screening of target pixels to obtain candidate corner points, and after Gaussian filtering, the improved corner point response function value was used for secondary screening, and then the final corner point was obtained by non-maximum suppression, and finally the target and interference were quadratically distinguished by the rectangularity. Through theoretical analysis and experimental verification, 95% of the targets can be effectively identified. The results show that the proposed method can efficiently and accurately distinguish between target and interference, while meeting the real-time requirements, and provides a theoretical reference for the anti-interference of laser imaging fuze.

参考文献

[1] NIU Ch M. Research on the key technology of long-distance circumferential detection system[D]. Ji’nan: Qilu University of Technology, 2021:1-13(in Chinese).

[2] WU Y, HUANG Zh H, GUO K, et al. Research on development and application of laser fuze passive jamming technology[J]. Electro-Optic Technology Application,2021,36(4):1-4 (in Chinese).

[3] LI L K,LI Y,GAO Ch, et al. Study on echo characteristics of narrow pulse laser fuze on targets in cloud[J].Aero Weaponry,2021,28(5):106-109(in Chinese).

[4] CHEN H M, MA Ch, QI B, et al. Study on backscattering characte-ristics of pulsed laser fuze in smoke[J]. Infrared and Laser Engineering,2020,49(4):38-44(in Chinese).

[5] CHEN P,ZHAO J G,SONG Y Sh. Research progress on anti-aerosol interference methods for laser proximity detection[J].Journal of Ordnance Equipment Engineering,2020,41(8):228-233(in Chinese).

[6] REN H G, ZHANG H J, SUN Y K, et al. Study on techniques of anti-aerosol-interference for active optical target-detection device[J]. Infrared and Laser Engineering,2020,49(4):29-37(in Chinese).

[7] WANG G,HE W,DONG W B, et al. Target identification based on morphological point feature[J].Journal of Detection & Control,2010,32(6):18-22(in Chinese).

[8] WEI Y Y, HE W. A method for quick distinguishing between target and clouds[J].Journal of Projectiles,Rockets,Missiles and Guidance,2014,34(2):177-181(in Chinese).

[9] WANG X J,MA H,ZHANG Sh F. Laser gray imaging fuze technology for air-to-air missile[J].Infrared and Laser Engineering,2018,47(3):37-43(in Chinese).

[10] TANG Q,HE W. Target recognition method of laser imaging fuze based on deep transfer learning [C]//2021 the 3rd International Conference on Natural Language Processing (ICNLP). Beijing, Ch-ina:ICNLP, 2021:202-207.

[11] SUN Zh H,DENG J H,YAN X W. Linear array push-broom method in laser imaging fuze detection technology[J].Opto-Electronic Engineering,2009,36(3):16-21(in Chinese).

[12] LIU B H,SONG Ch T,DUAN Y B. Design and simulation of a panoramic laser imaging fuze[J].Infrared and Laser Engineering,2018,47(4):147-154(in Chinese).

[13] DONG K Sh, CAO L P, HAN T, et al. Application research on laser imaging fuze in air-to-air missiles[J].Journal of Air Force Engineering University(Natural Science Edition),2013,14(2):42-46(in Chinese).

[14] ZHU S C, ZHOU D L. Review on image corner detection[J].Computer Systems & Applications,2020,29(1):22-28(in Chinese).

[15] YANG J H, DONG J J, YUAN T, et al. An improved corner detection method based on grayscale changes of image neighboring[J]. Basic Sciences Journal of Textile Universities,2019,32(3):337-344(in Chinese).

[16] WANG H Y, CHEN D L, SHUAI Y Sh, et al. Improved Harris corner detection algorithm based on gray difference preprocessing[J].Electronic Technology & Software Engineering,2019,8(9):72-73(in Chinese).

[17] YU W B, WANG G X, LIU Ch, et al, An algorithm for corner detection based on contour [C]// 2020 Chinese Automation Congress (CAC). Shanghai, China:CAC, 2020:114-118.

[18] CUI L,LI Ch,LI Y. Implementation and analysis of harris algorithm and SUSAN algorithm[J]. Computer & Digital Engineering,2019,47(10):2396-2401(in Chinese).

[19] HUANG X L. Research on the corner detection algorithms based on gray change[D]. Nanchang: East China University of Technology, 2019:21-34(in Chinese).

[20] JIANG Y. Research on scanning imaging technology of terminal-sensitive missile-borne lidar[D]. Nanjing: Nanjing University of Science and Technology, 2020:49-61(in Chinese).

周瑜, 贺伟. 激光成像引信的目标识别方法研究[J]. 激光技术, 2023, 47(2): 267. ZHOU Yu, HE Wei. Target recognition method of laser imaging fuze[J]. Laser Technology, 2023, 47(2): 267.

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