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 dynamic 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 disadvantages 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.

A review on the developments and space applications of mid- and long-wavelength infrared detection technologies

Mid-wavelength infrared(MWIR)detection and long-wavelength infrared(LWIR)detection constitute the key technologies for space-based Earth observation and astronomical detection.The advanced ability of infrared(IR)detection technology to penetrate the atmosphere and identify the camouflaged targets makes it excellent for space-based remote sensing.Thus,such detectors play an essential role in detecting and tracking low-temperature and far-distance moving targets.However,due to the diverse scenarios in which space-based IR detection systems are built,the key parameters of IR technologies are subject to unique demands.We review the developments and features of MWIR and LWIR detectors with a particular focus on their applications in space-based detection.We conduct a comprehensive analysis of key performance indicators for IR detection systems,including the ground sampling distance(GSD),operation range,and noise equivalent temperature difference(NETD)among others,and their interconnections with IR detector parameters.Additionally,the influences of pixel distance,focal plane array size,and operation temperature of space-based IR remote sensing are evaluated.The development requirements and technical challenges of MWIR and LWIR detection systems are also identified to achieve high-quality space-based observation platforms.

Multifunctional MXene/Carbon Nanotube Janus Film for Electromagnetic Shielding and Infrared Shielding/Detection in Harsh Environments

Multifunctional,flexible,and robust thin films capable of operating in demanding harsh temperature environments are crucial for various cutting-edge applications.This study presents a multifunctional Janus film integrating highly-crystalline Ti_(3)C_(2)T_(x) MXene and mechanically-robust carbon nanotube(CNT)film through strong hydrogen bonding.The hybrid film not only exhibits high electrical conductivity(4250 S cm^(-1)),but also demonstrates robust mechanical strength and durability in both extremely low and high temperature environments,showing exceptional resistance to thermal shock.This hybrid Janus film of 15μm thickness reveals remarkable multifunctionality,including efficient electromagnetic shielding effectiveness of 72 dB in X band frequency range,excellent infrared(IR)shielding capability with an average emissivity of 0.09(a minimal value of 0.02),superior thermal camouflage performance over a wide temperature range(−1 to 300℃)achieving a notable reduction in the radiated temperature by 243℃ against a background temperature of 300℃,and outstanding IR detection capability characterized by a 44%increase in resistance when exposed to 250 W IR radiation.This multifunctional MXene/CNT Janus film offers a feasible solution for electromagnetic shielding and IR shielding/detection under challenging conditions.

A Novel Filtering-Based Detection Method for Small Targets in Infrared Images

Infrared small target detection technology plays a pivotal role in critical military applications,including early warning systems and precision guidance for missiles and other defense mechanisms.Nevertheless,existing traditional methods face several significant challenges,including low background suppression ability,low detection rates,and high false alarm rates when identifying infrared small targets in complex environments.This paper proposes a novel infrared small target detection method based on a transformed Gaussian filter kernel and clustering approach.The method provides improved background suppression and detection accuracy compared to traditional techniques while maintaining simplicity and lower computational costs.In the first step,the infrared image is filtered by a new filter kernel and the results of filtering are normalized.In the second step,an adaptive thresholding method is utilized to determine the pixels in small targets.In the final step,a fuzzy C-mean clustering algorithm is employed to group pixels in the same target,thus yielding the detection results.The results obtained from various real infrared image datasets demonstrate the superiority of the proposed method over traditional approaches.Compared with the traditional method of state of the arts detection method,the detection accuracy of the four sequences is increased by 2.06%,0.95%,1.03%,and 1.01%,respectively,and the false alarm rate is reduced,thus providing a more effective and robust solution.

Infrared Fault Detection Method for Dense Electrolytic Bath Polar Plate Based on YOLOv5s

Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal production.Aiming at the problems of time-consuming and poor accuracy of existing infrared methods for high-temperature detection of dense pole plates in electrolysis tanks,an infrared dense pole plate anomalous target detection network YOLOv5-RMF based on You Only Look Once version 5(YOLOv5)is proposed.Firstly,we modified the Real-Time Enhanced Super-Resolution Generative Adversarial Network(Real-ESRGAN)by changing the U-shaped network(U-Net)to Attention U-Net,to preprocess the images;secondly,we propose a new Focus module that introduces the Marr operator,which can provide more boundary information for the network;again,because Complete Intersection over Union(CIOU)cannot accommodate target borders that are increasing and decreasing,replace CIOU with Extended Intersection over Union(EIOU),while the loss function is changed to Focal and Efficient IOU(Focal-EIOU)due to the different difficulty of sample detection.On the homemade dataset,the precision of our method is 94%,the recall is 70.8%,and the map@.5 is 83.6%,which is an improvement of 1.3%in precision,9.7%in recall,and 7%in map@.5 over the original network.The algorithm can meet the needs of electrolysis tank pole plate abnormal temperature detection,which can lay a technical foundation for improving production efficiency and reducing production waste.

State-of-the-art development about cryogenic technologies to support space-based infrared detection

As a key technology for space-based Earth observation and astronomical exploration,cooled mid-wavelength and long-wavelength Infrared(IR)detection is widely used in national defense,astronomy exploration,medical imaging,environmental monitoring,agricultural and other areas.The performances of IR detectors,including cut-off wavelength,detectivity,sensitivity and temperature resolution,plays a significant role in efficiently observing and tracking the low-temperature far-distance moving targets.Achieving optimal detection performance requires the IR detectors to operate at cryogenic temperatures.The future development of space-based applications relies heavily on the mid-wavelength and long-wavelength IR detection technologies,which should be enabled by the long-life cryogenic refrigeration and high-efficiency energy transportation system operating below 40 K,to support the Earth observation and astronomical detection.However,the efficiency degradation caused by the super low temperature brings tremendous challenges to the life time of cryogenic refrigeration and energy transportation systems.This paper evaluates the influence of cryogenic temperature on the infrared detector performances,reviews the features,development and space applications of cryogenic cooling technologies,as well as the cryogenic energy transportation approaches.Additionally,it analyzes the future development trends and challenges in supporting the space-based IR detection.

Infrared Small Target Detection Algorithm Based on ISTD-CenterNet

This paper proposes a real-time detection method to improve the Infrared small target detection CenterNet(ISTD-CenterNet)network for detecting small infrared targets in complex environments.The method eliminates the need for an anchor frame,addressing the issues of low accuracy and slow speed.HRNet is used as the framework for feature extraction,and an ECBAM attention module is added to each stage branch for intelligent identification of the positions of small targets and significant objects.A scale enhancement module is also added to obtain a high-level semantic representation and fine-resolution prediction map for the entire infrared image.Besides,an improved sensory field enhancement module is designed to leverage semantic information in low-resolution feature maps,and a convolutional attention mechanism module is used to increase network stability and convergence speed.Comparison experiments conducted on the infrared small target data set ESIRST.The experiments show that compared to the benchmark network CenterNet-HRNet,the proposed ISTD-CenterNet improves the recall by 22.85%and the detection accuracy by 13.36%.Compared to the state-of-the-art YOLOv5small,the ISTD-CenterNet recall is improved by 5.88%,the detection precision is improved by 2.33%,and the detection frame rate is 48.94 frames/sec,which realizes the accurate real-time detection of small infrared targets.

PF-YOLOv4-Tiny: Towards Infrared Target Detection on Embedded Platform

Infrared target detection models are more required than ever before to be deployed on embedded platforms,which requires models with less memory consumption and better real-time performance while considering accuracy.To address the above challenges,we propose a modified You Only Look Once(YOLO)algorithm PF-YOLOv4-Tiny.The algorithm incorpo-rates spatial pyramidal pooling(SPP)and squeeze-and-excitation(SE)visual attention modules to enhance the target localization capability.The PANet-based-feature pyramid networks(P-FPN)are proposed to transfer semantic information and location information simultaneously to ameliorate detection accuracy.To lighten the network,the standard convolutions other than the backbone network are replaced with depthwise separable convolutions.In post-processing the images,the soft-non-maximum suppression(soft-NMS)algorithm is employed to subside the missed and false detection problems caused by the occlusion between targets.The accuracy of our model can finally reach 61.75%,while the total Params is only 9.3 M and GFLOPs is 11.At the same time,the inference speed reaches 87 FPS on NVIDIA GeForce GTX 1650 Ti,which can meet the requirements of the infrared target detection algorithm for the embedded deployments.

CAFUNeT:A small infrared target detection method in complex backgrounds

Small infrared target detection has widespread applications in various fields including military,aviation,and medicine.However,detecting small infrared targets in complex backgrounds remains challenging.To detect small infrared targets,we propose a variable-structure U-shaped network referred as CAFUNet.A central differential convolution-based encoder,ASPP,an Attention Fusion module,and a decoder module are the critical components of the CAFUNet.The encoder module based on central difference convolution effectively extracts shallow detail information from infrared images,complemented by rich contextual information obtained from the deep features in the decoder module.However,the direct fusion of the shallow detail features with semantic features may lead to feature mismatch.To address this,we incorporate an Attention Fusion(AF)module to enhance the network performance further.We performed ablation studies on each module to evaluate its effectiveness.The results show that our proposed algorithm outperforms the state-of-the-art methods on publicly available datasets.

Novel detection method for infrared small targets using weighted information entropy

This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy （LMWIE）, is proposed to suppress background. Then, the grey value of targets is enhanced by calculating the local energy. Image segmentation based on the adaptive threshold is used to solve the problems that the grey value of noise is enhanced with the grey value improvement of targets. Experimental results show that compared with the adaptive Butterworth high-pass filter method, the proposed algorithm is more effective and faster for the infrared small target detection.

INFRARED THERMAL IMAGE STUDY ON THE FOREWARNING OF COAL AND SANDSTONE FAILURE UNDER LOAD

In the experimental study, AGE-782 thermal instrument was used to detect the infrared radiation variation of coal and sandstone (wave-length range 3.6～5.5 μm was used). It's discovered that coal and sandstone failure under load have three kinds of infrared thermal features as well as infrared forewarning messages. That are: (1) temperature rises gradually but drops before failure ; (2) temperature rises gradually but quickly rises before failure; (3) first rises,then drops and lower temperature emerges before failure. The further researches and the prospect of micro-wave remote sensing detection .on ground pressure is also discussed.

Use of Fourier-transform infrared spectroscopy to rapidly diagnose gastric endoscopic biopsies

AIM: To determine if Fourier-transform infrared (FT-IR)spectroscopy of endoscopic biopsies could accurately diagnose gastritis and malignancy.METHODS: A total of 123 gastroscopic samples, including 11 cases of cancerous tissues, 63 cases of chronic atrophic gastritis tissues, 47 cases of chronic superficial gastritis tissues and 2 cases of normal tissues, were obtained from the First Hospital of Xi'an Jiaotong University, China. A modified attenuated total reflectance (ATR) accessory was linked to a WQD-500 FT-IR spectrometer for spectral measurement followed by submission of the samples for pathologic analysis. The spectral characteristics for different types of gastroscopic tissues were summarized and correlated with the corresponding pathologic results.RESULTS: Distinct differences were observed in the FTIR spectra of normal, atrophic gastritis, superficial gastritis and malignant gastric tissues. The sensitivity of FT-IR for detection of gastric cancer, chronic atrophic gastritis and superficial gastritis was 90.9%, 82.5%, 91.5%, and specificity was 97.3%, 91.7%, 89.5% respectively.CONCLUSION: FT-IR spectroscopy can distinguish gastric inflammation from malignancy.

A proposal for detecting weak electromagnetic waves around 2.6μm wavelength with Sr optical clock

Infrared signal detection is widely used in many fields.Due to the detection principle,however,the accuracy and range of detection are limited.Thanks to the ultra stability of the^(87)Sr optical lattice clock,external infrared electromagnetic wave disturbances can be responded to.Utilizing the ac Stark shift of the clock transition,we propose a new method to detect infrared signals.According to our calculations,the theoretical detection accuracy in the vicinity of its resonance band of 2.6μm can reach the order of 10-14W,while the minimum detectable signal of common detectors is on the order of 10^(-10)W.

Using deep learning to detect small targets in infrared oversampling images

According to the oversampling imaging characteristics, an infrared small target detection method based on deep learning is proposed. A 7-layer deep convolutional neural network(CNN) is designed to automatically extract small target features and suppress clutters in an end-to-end manner. The input of CNN is an original oversampling image while the output is a cluttersuppressed feature map. The CNN contains only convolution and non-linear operations, and the resolution of the output feature map is the same as that of the input image. The L1-norm loss function is used, and a mass of training data is generated to train the network effectively. Results show that compared with several baseline methods, the proposed method improves the signal clutter ratio gain and background suppression factor by 3–4 orders of magnitude, and has more powerful target detection performance.

Two-dimensional heterostructure promoted infrared photodetection devices

It is a rapidly developed subject in expanding the fundamental properties and application of two-dimensional(2D)materials.The weak van der Waals interaction in 2D materials inspired researchers to explore 2D heterostructures(2DHs)based broadband photodetectors in the far-infrared(IR)and middle-IR regions with high response and high detectivity.This review focuses on the strategy and motivation of designing 2DHs based high-performance IR photodetectors,which provides a wide view of this field and new expectation for advanced photodetectors.First,the photocarriers'generation mechanism and frequently employed device structures are presented.Then,the 2DHs are divided into semimetal/semiconductor 2DHs,semiconductor/semiconductor 2DHs,and multidimensional semi-2DHs;the advantages,motivation,mechanism,recent progress,and outlook are discussed.Finally,the challenges for next-generation photodetectors are described for this rapidly developing field.

On the MOSFET-Based Temperature Sensitive Element for Bolometer Application

This paper focuses on the study of thermal performances of MOS （metal-oxide-semiconductor） transistors for uncooled infrared bolometer applications. Such devices can be used in various applications both military and civil, such as defence and security, medical applications, industrial surveillance, etc. Series of measurements were conducted to obtain TCC （temperature coefficient of current） versus gate voltage and temperature curves. The TCC is a figure of merit for a device used as the sensitive element in a bolometer that represents its sensitivity to temperature and as such is a good indicator of the detector attainable performance. The measurements were confronted to Atlas simulations, and showed that in the subthreshold region the TCC ranges from 4%/K all the way to 9%/K which represents a great improvement compared to state of the art thermistor bolometers. Analytic expressions of the TCC are also derived from current equations of the MOSFET （MOS field effect transistor） drain current to help understanding the effect of drain to source voltage, mobility, temperature and threshold voltage sensibility to temperature, in all three operation modes of the transistor （subthreshold, ohmic and saturation）. It was also determined that gate length does not have an influence on the TCC until short channel effects are factored in.

Sensitive detection of infrared photons using a high-Q microcantilever

A new approach based on microcantilevers is presented to detect infrared photons with high sensitivity. Infrared photons are measured by monitoring the amplitude change of a vibrating microcantilever under light pressure force.The irradiating light is modulated into sinusoidal and pulsed waves,and to be in-phase and anti-phase with the cantilever driving signal.A linear relationship between the amplitude change of the cantilever and the light power distributing on the cantilever was observed.Under a vacuum of 10^（-4） Pa,an infrared light power of 7.4 nW was detected with the cantilever.The in-phase and anti-phase modulation to the cantilever vibration using a pulsed light results in an enhanced response of the cantilever.

An automated water dispensing system for controlling fires in coal yards

In spite of recent moves to wean the world of fossil fuels,coal remains the main source of power in many countries.Coal yards are prone to spontaneous ignition,a problem faced in every country that stores or transports coal.Depending on the environment-temperature,ventilation,and the rank of the coal-heating and self-ignition can be a longer or shorter process,but the possibility can never be entirely dismissed.A plethora of studies have modelled this oxidation behavior and proposed countermeasures.Most often,human intervention is necessary,which is both slow and dangerous for the frefghters involved.In this study,we propose to build a complete frefghting solution which is mounted on a number of towers sufcient to cover the area of an open coal yard,complete with redundancy.Each tower includes an inexpensive infrared detector,a water dispenser and a controller programmed to identify areas of elevated temperature,and actuate the dispenser.The heat direction algorithm calculates the parameters to position the water dispenser so that it covers the area.A prototype has been built from inexpensive components to demonstrate the efectiveness at detecting and extinguishing arising fres,and a solution has been costed for the coal yard in the case study.This work has been conducted in collaboration with the managers of the coal yard of a power plant.

An Effective Method of Threshold Selection for Small Object Image

The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.

Detection of near infrared light illumination with the aid of none-metal plasmonic nanocrystals

With the support by the National Natural Science Foundation of China,the research team led by Prof.Luo LinBao(罗林保)at the College of Electronic Sciences and Applied Physics,Hefei University of Technology,developed a simple and highly efficient near infrared light photodetector,which was published in Laser&Photonics Reviews(2016,10:595—602).