大气对红外制导波段透过特性的影响分析

红外制导武器对目标的发现、识别和跟踪主要依据目标与背景的红外辐射特性及其对比特性。随着红外技术的不断发展和在军事上的广泛运用,红外辐射在大气中的传输研究越来越受到关注。针对大气透过率是研究红外辐射传输的重要参数,提取既定区域实际观测大气数据构建大气参数廓线并嵌入成熟、通用的大气辐射传输模型中,探讨了红外波段实际大气透过特性的变化特征,并分析了用模型自带大气近似可能带来的误差。结果表明,基于实际大气廓线计算出的大气透过特性准确度基本吻合国际公认理论分析值,我国区域内的大气透过率的准确计算必须考虑我国的实际大气,这对最大限度分析利用战场气象环境确保武器作战性能的充分发挥具有重要价值。     

典型飞机红外辐射特性及探测仿真研究

依据红外辐射的基本原理,针对隐身飞机的发动机尾焰、尾喷口和飞机蒙皮三大主要辐射源,建立了隐身飞机的红外辐射模型,提出了基于温度场分布的飞机红外辐射计算方法,并对某型飞机的红外隐身效果进行了仿真。根据红外探测器的工作原理,得到经大气传输和目标与背景对比后探测器接收到的有效目标信息,仿真计算了探测距离随波长的变化情况。研究结果对隐身飞机的设计以及红外制导防空导弹武器系统的设计和应用提供了重要的参考依据。     

地面热成像系统观察条件下目标能见度模型

本文在研究大气自我传输特性的基础上,对目标与背景的辐射传输特性进行了分析,提出了大气干扰辐射度,视辐射对比度和视辐射对比阈的概念,推导了地面热成像系统观察条件下的目标能见度模型公式,并通过实验初步验证了该能见度模型公式的可信性。     

北约空中目标红外辐射模型

北约空中目标红外辐射模型张赛金,张常国编译精确预测空中目标的红外辐射特性具有极其重大的实际意义。红外搜索跟踪系统、警戒系统和导弹红外制导系统的探测识别都依赖于准确的目标辐射数据,飞机、导弹等空中目标的设计者们也要根据这些数据采取相应的被动对抗措施,如...     

海空背景下目标红外辐射特征分析

根据海空复杂背景下点目标的红外特征 ,提出了目标红外特征的一般计算方法 .根据不同的气象条件、不同海域背景 ,计算分析了环境对红外辐射两个大气窗口 ,即 3～ 5 μm和 8～ 12 μm双波段大气透过率的影响 ,并给出了相应结论     

反舰导弹红外辐射特性研究

从舰载红外警戒系统的实际需要出发,针对海空背景下低空来袭反舰导弹目标,深入研究导弹的红外辐射特征,并建立其红外辐射简化模型.通过导弹尾喷管、尾喷焰及蒙皮的气动加热3个导弹主要辐射源,计算某型反舰导弹在长波段(红外警戒系统主要工作波段)的红外辐射强度,并针对计算结果进行了相关分析.     

红外隐身技术:让水面舰艇变“冷”

红外探测是现代海战场上除雷达探测之外的另一种主要探测手段。由于水面舰艇排热量大,而海上背景环境相对较冷且一致性较好,因此,水面舰艇的红外特征较之其他武器系统更易被探测与识别。再加上红外制导导弹只要接受一定强度的热辐射信号就能有效命中目标,红外辐射特征于是成为水面舰艇防御中一个突出的问题;降低红外特征已引起各国海军的特别重视,成为提高水面舰艇生存能力的主要措施之一。     

武装直升机应用红外干扰弹作战效能评估

为解决武装直升机在近距空战中因发动机红外热辐射而易被敌红外制导导弹截获的问题,首先根据火控系统以及武器配置特点,给出一种用于评估武装直升机使用红外干扰弹抑制敌方红外制导导弹的效能评估方法;然后结合具体算例分析,计算和确定为保障对武装直升机的防护概率不低于某一给定概率所需的红外干扰弹数量及其发射方式.     

基于热物理仿真分析的红外点目标特征提取与识别

根据弹道中段空间目标和诱饵的表面温度分布规律，从热物理的角度分析了目标和诱饵的红外光谱辐射特性，指出了弹道中段目标和诱饵红外辐射特性的本质差别，并据此提出了红外目标识别中的特征基函数，用特征基函数构造红外点目标识别的四维特征矢量。仿真实验表明，这一特征矢量用于红外点目标识别非常成功。     

大气辐射对热辐射对比度的影响

本文在分析大气中红外辐射传输规律的基础上,导出了大气自身辐射所形成的干扰辐射亮度对热工外辐射对比度的影响及其数字表达式,理论分析,推导表明此表达式是正确的,所述论点是建立热红外伪装定量评价模型的理论基础,同时也为模拟热红外图象提供了一条新的研究思路。     

激光武器对红外导引头的软破坏研究

针对舰载激光武器破坏反舰导弹的问题,研究了激光对红外制导反舰导弹导引头的软破坏。以激光辐照红外探测器为例,建立了舰载激光武器对红外制导反舰导弹探测器的破坏模型,计算了1.06μm激光海上大气传输的大气透过率,进行了0.632μm激光辐照CCD成像系统的实验,估算了对远距离红外制导反舰导弹探测器实现有效破坏所需发射的激光能量,得出了一些有价值的数据和结论。     

A pixel-level local contrast measure for infrared small target detection

Infrared (IR) small target detection is one of the key technologies of infrared search and track (IRST) systems. Existing methods have some limitations in detection performance, especially when the target size is irregular or the background is complex. In this paper, we propose a pixel-level local contrast measure (PLLCM), which can subdivide small targets and backgrounds at pixel level simultaneously. With pixel-level segmentation, the difference between the target and the background becomes more obvious, which helps to improve the detection performance. First, we design a multiscale sliding window to quickly extract candidate target pixels. Then, a local window based on random walker (RW) is designed for pixel-level target segmentation. After that, PLLCM incorporating probability weights and scale constraints is proposed to accurately measure local contrast and suppress various types of background interference. Finally, an adaptive threshold operation is applied to separate the target from the PLLCM enhanced map. Experimental results show that the proposed method has a higher detection rate and a lower false alarm rate than the baseline algorithms, while achieving a high speed.     

An infrared target intrusion detection method based on feature fusion and enhancement

Infrared target intrusion detection has significant applications in the fields of military defence and intelligent warning. In view of the characteristics of intrusion targets as well as inspection difficulties, an infrared target intrusion detection algorithm based on feature fusion and enhancement was proposed. This algorithm combines static target mode analysis and dynamic multi-frame correlation detection to extract infrared target features at different levels. Among them, LBP texture analysis can be used to effectively identify the posterior feature patterns which have been contained in the target library, while motion frame difference method can detect the moving regions of the image, improve the integrity of target regions such as camouflage, sheltering and deformation. In order to integrate the advantages of the two methods, the enhanced convolutional neural network was designed and the feature images obtained by the two methods were fused and enhanced. The enhancement module of the network strengthened and screened the targets, and realized the background suppression of infrared images. Based on the experiments, the effect of the proposed method and the comparison method on the background suppression and detection performance was evaluated, and the results showed that the SCRG and BSF values of the method in this paper had a better performance in multiple data sets, and it’s detection performance was far better than the comparison algorithm. The experiment results indicated that, compared with traditional infrared target detection methods, the proposed method could detect the infrared invasion target more accurately, and suppress the background noise more effectively.     

红外目标分割方法研究

红外目标分割算法对红外目标检测、跟踪具有非常重要的价值。本文利用背景和目标灰度特征,提出一种实现红外目标有效分割的方法,克服红外目标内部温度不稳定造成的误分割问题。本文方法首先采用基于灰度-显著度最大相关准则的二维直方图分割算法进行图像分割;然后,在分割后二值图上进行基于随机种子点选取的区域增长,提取背景;最后,采用形态学方法优化分割结果。相对传统的红外目标检测算法,这种算法具有更好的抗干扰能力,更强的鲁棒性。不仅可以应用于红外图像的目标分割,而且可以应用于其他类似的目标分割问题。     

【专题】基于深度学习及FPGA的装备目标检测研究

本文应用深度学习技术实现海天背景下基于可见光、红外方式成像的舰船及角反、烟幕干扰的目标检测,这也是反舰导弹作战使用的关键技术之一。采集的可见光与红外成像目标检测数据集涵盖实施典型干扰下的态势场景,贴近实战;结合四种不同的目标检测机制,选取YOLOV3、Faster R-CNN、SSD及CenterNet四种典型模型分别进行训练与验证,通过对比分析进一步提高弱小目标、复杂干扰态势的的检测,可以实现端到端的高精度装备目标检测模型。在确保精度的前提下基于现场可编程门阵列（FPGA）进行软硬件协同设计,通过对比分析选定基于Vitis AI的实施方案,经过模型的量化、编译与优化,可在保证检测效率的前提下快速实现模型的小型化部署,便于进行装备移植。研究结果表明,该研究内容可有效提高现役反舰导弹目标检测的准确率。     

基于小波变换与数学形态学的红外图像分割方法

提出一种基于小波变换和形态学相结合的红外图像分割方法,该方法利用小波变换和形态学消除红外图像的混合噪声,抑制背景干扰和增强目标;通过选择适当的结构元素进行系列形态组合运算,自适应确定阈值,提取目标;利用形态学水线区域分割法对图像进行分割,分离目标区域。实验结果表明,该方法能有效检测和分割出低信噪比复杂背景红外图像中的目标。     

基于跟踪精度控制的多传感器管理方法

针对地面机动目标跟踪过程中的多传感器管理问题展开了研究,设计了一种基于跟踪精度控制的多传感器多目标分配方法。首先,在考虑目标与目标之间、目标与传感器之间和传感器与传感器之间等的多种约束条件下运用基于协方差控制的思想建立了多传感器多目标分配问题的优化模型;接着将等价伪量测的异步融合算法与IMM算法结合,计算各目标在不同融合周期的跟踪精度估计值;最后,以目标的跟踪精度需求为出发点,结合蚁群算法的思想,设计了一种求解所建立的多传感器多目标分配问题的优化模型的算法。仿真结果表明：该管理方法能在确保跟踪精度需求的前提下,根据对各目标跟踪任务的重要程度,合理地调度传感器资源。     

Fuzzy recognition of missile borne multi-line array infrared detection based on size calculating

In order to improve the infrared detection and discrimination ability of the smart munition to the dy-namic armor target under the complex background, the multi-line array infrared detection system is established based on the combination of the single unit infrared detector. The surface dimension features of ground armored targets are identified by size calculating solution algorithm. The signal response value and the value of size calculating are identified by the method of fuzzy recognition to make the fuzzy classification judgment for armored target. According to the characteristics of the target signal, a custom threshold de-noising function is proposed to solve the problem of signal preprocessing. The multi-line array infrared detection can complete the scanning detection in a large area in a short time with the characteristics of smart munition in the steady-state scanning stage. The method solves the disadvan-tages of wide scanning interval and low detection probability of single unit infrared detection. By reducing the scanning interval, the number of random rendezvous in the infrared feature area of the upper surface is increased, the accuracy of the size calculating is guaranteed. The experiments results show that in the fuzzy recognition method, the size calculating is introduced as the feature operator, which can improve the recognition ability of the ground armor target with different shape size.     

Evaluation of infrared camouflage effectiveness via a multi-fractal method

This paper reports an alternative approach to the evaluation of infrared camouflage effectiveness via a multi-fractal method. By calculating multi-fractal spectra of the target region and the background re-gions in an infrared image, the spectrum shape features and the discrete Fréchet distances among these spectra were used to analyze the camouflage effectiveness of the target qualitatively and quantitatively, and the correlation coefficients of the spectra were further used as the index of camouflage effectiveness. It was found that the camouflaged target had better camouflage effectiveness than the target without camouflage in the same one background, and the same one camouflaged target had different camouflage effectiveness in different backgrounds. On the whole, the target matching well with its background had high camouflage effectiveness value. This approach can expand the application of multi-fractal theory in infrared camouflage technology, which should be useful for the research of infrared camouflage mate-rials, the design of camouflage patterns as well as the deployment of military equipment in battlefield.