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基于中波光谱成像中二氧化碳双尖峰的超稳健远程目标检测

Extremely Robust Remote-Target Detection Based on Carbon Dioxide-Double Spikes in Midwave Spectral Imaging.

作者信息

Kim Sungho, Shin Jungsub, Ahn Joonmo, Kim Sunho

机构信息

Department of Electronic Engineering, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, Korea.

Agency for Defense Development, P.O. Box 35, Daejeon 34186, Korea.

出版信息

Sensors (Basel). 2020 May 20;20(10):2896. doi: 10.3390/s20102896.

Abstract

Infrared ship-target detection for sea surveillance from the coast is very challenging because of strong background clutter, such as cloud and sea glint. Conventional approaches utilize either spatial or temporal information to reduce false positives. This paper proposes a completely different approach, called carbon dioxide-double spike (CO-DS) detection in midwave spectral imaging. The proposed CO-DS is based on the spectral feature where a hot CO emission band is broader than that which is absorbed by normal atmospheric CO, which generates CO-double spikes. A directional-mean subtraction filter (D-MSF) detects each CO spike, and final targets are detected by joint analysis of both types of detection. The most important property of CO-DS detection is that it generates an extremely low number of false positive caused by background clutter. Only the hot CO spike of a ship plume can penetrate atmosphere, and furthermore, there are only ship CO plume signatures in the double spikes of different spectral bands. Experimental results using midwave Fourier transform infrared (FTIR) in a remote sea environment validate the extreme robustness of the proposed ship-target detection.

摘要

从海岸进行海上监视的红外舰船目标检测极具挑战性,因为存在强烈的背景杂波,如云和海面反射光。传统方法利用空间或时间信息来减少误报。本文提出了一种截然不同的方法,即中波光谱成像中的二氧化碳双尖峰(CO-DS)检测。所提出的CO-DS基于光谱特征,即热CO发射带比正常大气CO吸收带更宽,这会产生CO双尖峰。方向均值减法滤波器(D-MSF)检测每个CO尖峰,最终目标通过对两种检测类型的联合分析来检测。CO-DS检测最重要的特性是它由背景杂波引起的误报数量极低。只有舰船羽流的热CO尖峰能够穿透大气层,此外,在不同光谱带的双尖峰中只有舰船CO羽流特征。在远程海洋环境中使用中波傅里叶变换红外(FTIR)的实验结果验证了所提出的舰船目标检测的极强鲁棒性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b74/7284358/d414b2807d9f/sensors-20-02896-g001.jpg

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