False Alarm Rate Reduction in Infrared Search and Track Systems

SONG Zhihang; ZHANG Jin; ZHU Liang; LIN Dandan; DU Xinyue; LIN Yu

Volume 44 Issue 4

Apr. 2022

Turn off MathJax

Article Contents

Article Navigation > Infrared Technology > 2022 > 44(4): 371-376

SONG Zhihang, ZHANG Jin, ZHU Liang, LIN Dandan, DU Xinyue, LIN Yu. False Alarm Rate Reduction in Infrared Search and Track Systems[J]. Infrared Technology , 2022, 44(4): 371-376.

Citation:

SONG Zhihang, ZHANG Jin, ZHU Liang, LIN Dandan, DU Xinyue, LIN Yu. False Alarm Rate Reduction in Infrared Search and Track Systems[J]. Infrared Technology , 2022, 44(4): 371-376.

SONG Zhihang, ZHANG Jin, ZHU Liang, LIN Dandan, DU Xinyue, LIN Yu. False Alarm Rate Reduction in Infrared Search and Track Systems[J]. Infrared Technology , 2022, 44(4): 371-376.

Citation:

SONG Zhihang, ZHANG Jin, ZHU Liang, LIN Dandan, DU Xinyue, LIN Yu. False Alarm Rate Reduction in Infrared Search and Track Systems[J]. Infrared Technology , 2022, 44(4): 371-376.

PDF( 1135 KB)

False Alarm Rate Reduction in Infrared Search and Track Systems

Kunming Institute of Physics, Kunming 650223, China

Received Date: 2021-02-03
Rev Recd Date: 2021-05-27
Publish Date: 2022-04-20

Abstract

Abstract

Infrared panoramic search and track systems can provide real-time multi-target search and positioning functions for a 360° field of view. However, the involvement of the large view field introduces problems such as increased number of false targets and a large displacement of moving targets between panoramic frames. To address these problems, this study uses the image pyramid transform to reduce the panoramic image resolution and the Lucas-Kanade optical-flow method to calculate the optical flow of all predicted movement areas. Finally, the optical-flow features are analyzed to separate the real target from the false target area. In this way, false targets can be effectively detected in the panorama images, and the interference of such targets in the subsequent processing can be eliminated.
- panoramic search and track,
- false alarm rate,
- Lucas-Kanade optical-flow,
- dichotomy

FullText(HTML)

References(15)

References

[1]	陈洁, 张若岚. 应用于红外搜索跟踪和态势感知系统的全景成像技术[J]. 红外技术, 2016, 38(4): 269-279. http://hwjs.nvir.cn/article/id/hwjs201604001 CHEN Jie, ZHANG Ruolan. Panoramic imaging technology applied in IRST and status awareness system[J]. Infrared Technology, 2016, 38(4): 269-279. http://hwjs.nvir.cn/article/id/hwjs201604001
[2]	朱海滨, 邵毓, 张远健, 等. 可见光/红外双视场全景式航空侦查相机光学系统设计[J]. 应用光学, 2017, 38(1): 7-11. https://www.cnki.com.cn/Article/CJFDTOTAL-YYGX201701002.htm ZHU Haibin, SHAO Yu, ZHANG Yuanjian, et al. Optical system design of visible/infrared and double-FOV panoramic aerial camera[J]. Journal of Applied Optics, 2017, 38(1): 7-11. https://www.cnki.com.cn/Article/CJFDTOTAL-YYGX201701002.htm
[3]	贾俊涛, 唐跃峰, 毛鑫, 等. 红外全景扫描跟踪成像系统设计与实现[J]. 应用光学, 2013, 34(3): 407-412. JIA Juntao, TANG Yuefeng, MAO Xin, et al. Design and implement of infrared panoramic scanning and tracking imaging system[J]. Journal of Applied Optics, 2013, 34(3): 407-412.
[4]	李洁, 孙科峰. 机载红外搜索跟踪系统仿真测试平台设计[J]. 电光与控制, 2019, 26(8): 101-105, 110. doi: 10.3969/j.issn.1671-637X.2019.08.019 LI Jie, SUN Kefeng. Design of a simulation testing platform for airborne IRST system[J]. Electronics Optics & Control, 2019, 26(8): 101-105, 110. doi: 10.3969/j.issn.1671-637X.2019.08.019
[5]	何杰. 机载红外搜索跟踪系统研究与仿真实现[D]. 南京: 南京航空航天大学, 2014. HE Jie. Research and Simulation of Airborne Infrared Search and Tracking System[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2014.
[6]	王辉, 周振彪, 于劲松, 等. 红外搜索跟踪系统的半实物仿真系统设计[J]. 计算机测量与控制, 2012, 20(6): 1672-1675. WANG Hui, ZHOU Zhenbiao, YU Jingsong, et al. Design of hardware-in-the-loop simulation system for infrared search and track system[J]. Computer Measurement & Control, 2012, 20(6): 1672-1675.
[7]	杨旭, 何江宁, 陈洪亮. 一种机载红外搜索跟踪系统多目标跟踪精度测试系统设计[J]. 电光与控制, 2017, 24(4): 80-84. https://www.cnki.com.cn/Article/CJFDTOTAL-DGKQ201704019.htm YANG Xu, HE Jiangning, CHEN Hongliang, et al. Design of a multi-target tracking accuracy test system for airborne IRST system[J]. Electronics Optics & Control, 2017, 24(4): 80-84. https://www.cnki.com.cn/Article/CJFDTOTAL-DGKQ201704019.htm
[8]	王卫华, 李志军, 何艳, 等. 一种基于兴趣区提取的红外搜索系统目标实时检测算法[J]. 中国激光, 2012, 39(11): 187-192. WANG Weihua, LI Zhijun, HE Yan, et al. A real-time target detection algorithm for infrared search and track system based on region of interest extraction[J]. Chinese Journal of Lasers, 2012, 39(11): 187-192.
[9]	陈炳文, 王文伟, 秦前清, 等. 基于时空融合和粒子滤波的红外弱小目标检测[J]. 红外与激光工程, 2010, 39(s): 228-232. https://cpfd.cnki.com.cn/Article/CPFDTOTAL-ZYHG201005001052.htm CHEN Bingwen, WANG Wenwei, QIN Qianqing, et al.   Infrared dim target detection based on space-time integration and particle filter[J]. Infrared and Laser Engineering, 2010, 39(s): 228-232. https://cpfd.cnki.com.cn/Article/CPFDTOTAL-ZYHG201005001052.htm
[10]	王雪梅, 黄自力, 王德胜. 红外弱小目标的单帧捕获[J]. 红外与激光工程, 2006, 35(s): 99-104. https://cpfd.cnki.com.cn/Article/CPFDTOTAL-ZYHG200611001021.htm WANG Xuemei, HUANG Zili, WANG Desheng. Infrared small and weak targets detection in single frame[J]. Infrared and Laser Engineering, 2006, 35(s): 99-104. https://cpfd.cnki.com.cn/Article/CPFDTOTAL-ZYHG200611001021.htm
[11]	罗举平, 贺有, 邰新军. 基于红外图像信息的变门限检测与跟踪方法[C]//第十届全国光电技术学术交流会论文集, 2012: 243. LUO Juping, HE You, TAI Xinjun. Variable threshold detection and tracking method based on infrared image information[C]//The 10th National Conference on Optoelectronic Technology, 2012: 243.
[12]	张艳艳, 娄莉, 梁硕. 基于改进光流算法的运动目标检测技术研究[J]. 智能计算机与应用, 2018, 8(1): 55-58. doi: 10.3969/j.issn.2095-2163.2018.01.013 ZHANG Yanyan, LOU Li, LIANG Shuo. Research on moving object detection technology based on improved optical-flow algorithm[J]. Intelligent Computer and Applications, 2018, 8(1): 55-58. doi: 10.3969/j.issn.2095-2163.2018.01.013
[13]	西北工业大学. 一种基于连续有限帧红外图像的弱小目标检测方法: CN201911073594[P]. 中国: 2020-02-21. Northwest Polytechnic University. A method of small target detection based on continuous finite frame infrared image: CN201911073594[P]. China: 2020-02-21.
[14]	WANG Lei, ZHAO Xu, LIU Yuncai. Reduce false positives for object detection by a priori probability in videos[J]. Neurocomputing, 2016, 208: 325-332. doi: 10.1016/j.neucom.2016.03.082
[15]	Recchia G, Fasano G, Accardo D, et al. An optical-flow based electro-optical see-and-avoid system for UAVs[C]//Proceedings of IEEE 2007 Aerospace Conference, 2007: DOI: 10.1109/AERO.2007.352759.