张骢,权康男,岳明凯,韩自强.基于密度–距离空间的红外引信抗噪声方法研究[J].装备环境工程,2022,19(11):48-53. ZHANG Cong,QUAN Kang-nan,YUE Ming-kai,HAN Zi-qiang.Anti-interference Method of Infrared Fuze Based on Density-Distance Space[J].Equipment Environmental Engineering,2022,19(11):48-53.
基于密度–距离空间的红外引信抗噪声方法研究
Anti-interference Method of Infrared Fuze Based on Density-Distance Space
  
DOI:10.7643/issn.1672-9242.2022.11.007
中文关键词:  红外目标  抗干扰  引信  环境适应性  密度–距离  像素生长法中图分类号:TJ430 文献标识码:A 文章编号:1672-9242(2022)11-0048-06
英文关键词:infrared targets  anti-interference  fuze  environmental adaptability  density-distance  pixel growth method
基金项目:辽宁省教育厅基本科研面上项目(LJKMZ20220605)
作者单位
张骢 沈阳理工大学 装备工程学院,沈阳 110159 
权康男 沈阳理工大学 装备工程学院,沈阳 110159 
岳明凯 沈阳理工大学 装备工程学院,沈阳 110159 
韩自强 沈阳理工大学 装备工程学院,沈阳 110159 
AuthorInstitution
ZHANG Cong School of Equipment Engineering, Shenyang Ligong University, Shenyang 110159, China 
QUAN Kang-nan School of Equipment Engineering, Shenyang Ligong University, Shenyang 110159, China 
YUE Ming-kai School of Equipment Engineering, Shenyang Ligong University, Shenyang 110159, China 
HAN Zi-qiang School of Equipment Engineering, Shenyang Ligong University, Shenyang 110159, China 
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中文摘要:
      目的 通过简易的图像处理和目标检测方法,提高红外引信在复杂环境下的抗干扰能力。方法 分析红外引信在复杂背景中的噪声类别,采用“密度–距离”空间方法与像素生长方法进行预处理和目标检测,赋予像素2种属性,并进行量化分析,确定灰度平坦区域中的红外候选目标,并通过像素生长方法筛选候选目标中的真实目标。结果 计算在不同信噪比环境下算法的抗噪声干扰能力,当红外图像的SNR值在44.1~45.4时,算法检测效果理想。结论 红外引信探测过程中的复杂背景和随机噪声都会降低图像质量,考虑到红外目标所占像素数少,极易受噪声影响,需要运用自适应简易算法提高检测准确性。该算法有良好的实时性和抗干扰能力,为红外引信在目标检测中的环境适应性提供了理论依据。
英文摘要:
      The paper intends to improve the anti-jamming ability of infrared fuze in acomplex environment through simple image processing and target detection methods. To analyze the noise class of infrared fuzes in complex back grounds, the "density-distance" spatial method and pixel growth method are used for preprocessing and target detection. The pixel is assigned with two properties, and under quantitative analysis to determine the infrared candidate target in the gray flat area, and the real target in the candidate target is screened by the pixel growth method. The anti-interference ability of the algorithm in different signal-to-noise ratio environments is calculated, and the object detection effect is ideal when the SNR value of the infrared image is between 44.1 to 45.4.The complex background and random noise in the infrared fuze detection process will reduce the image quality. Considering that the infrared target occupies a small number of pixels and is easily affected by noise, it is necessary to use an adaptive simple algorithm to improve detection accuracy. This algorithm has good real-time performance and anti-jamming ability, which provides a theoretical basis for the environmental adaptability of infrared fuze in target detection.
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