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对图像频谱协作IRST系统的识别距离的评估和实验验证

Yue Lin, Xiang Wang, Yong-Jian Tan

|November 11, 2025

概括

本研究介绍了用于图像频谱协作红外搜索和跟踪 (IRST) 系统的光谱识别距离模型. 与传统的仅用成像方法相比,它在远距离上表现出优异的目标识别能力.

科学领域:

光学和光子学在光学和光子学.
航空航天工程航空航天工程
信号处理信号处理

背景情况:

远距离的空中目标识别是具有挑战性的,因为点目标的外观.
传统的红外搜索和跟踪 (IRST) 系统在空间分辨率和对比度方面存在局限性.
现有的图像频谱协作IRST模型缺乏系统验证.

研究的目的:

为图像频谱协作IRST系统提出光谱识别距离模型.
建立识别距离和光谱信号与干扰比 (SIR) 之间的定量关系.
实验验证模型对合作和非合作目标的性能.

主要方法:

为图像频谱协作IRST开发光谱识别距离模型.
使用合作和非合作目标进行实验验证.
基于光谱信号与干扰比率 (SIR) 和信号与噪声比率 (SNR) 的识别性能分析.

主要成果:

拟议的模型实现了对合作目标的0.1以下的正常化平均平方误差 (NMSE).
对于非合作目标,观察到0.09的相对偏差.
通过光谱通道成功识别远距离目标 (25.5公里),性能优于成像通道.

结论:

频谱识别距离模型提供了对图像频谱协作IRST性能的定量评估.
图像频谱协作IRST系统比传统的仅用于成像的IRST显示了增强的识别能力.
频谱通道在具有挑战性的远距离空中目标检测场景中提供了卓越的性能.

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