Research on a Measurement Method for Middle-Infrared Radiation Characteristics of Aircraft

Deng, Xuan; Wang, Yueming; Han, Guicheng; Xue, Tianru

doi:10.3390/machines10010044

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…The infrared radiation characteristics of high-altitude flying objects are crucial for target detection, recognition, and tracking [6]. The infrared radiation characteristics of these flying objects are determined by their temperature and surface properties.…”

Section: Introductionmentioning

confidence: 99%

Classification of High-Altitude Flying Objects Based on Radiation Characteristics with Attention-Convolutional Neural Network and Gated Recurrent Unit Network

Dai,

Cao,

Liu

et al. 2023

Remote Sensing

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In the task of classifying high-altitude flying objects, due to the limitations of the target flight altitude, there are issues such as insufficient contour information, low contrast, and fewer pixels in the target objects obtained through infrared detection technology, making it challenging to accurately classify them. In order to improve the classification performance and achieve the effective classification of the targets, this study proposes a high-altitude flying object classification algorithm based on radiation characteristic data. The target images are obtained through an infrared camera, and the radiation characteristics of the targets are measured using radiation characteristic measurement techniques. The classification is performed using an attention-based convolutional neural network (CNN) and gated recurrent unit (GRU) (referred to as ACGRU). In ACGRU, CNN-GRU and GRU-CNN networks are used to extract vectorized radiation characteristic data. The raw data are processed using Highway Network, and SoftMax is used for high-altitude flying object classification. The classification accuracy of ACGRU reaches 94.8%, and the F1 score reaches 93.9%. To verify the generalization performance of the model, comparative experiments and significance analysis were conducted with other algorithms on radiation characteristic datasets and 17 multidimensional time series datasets from UEA. The results show that the proposed ACGRU algorithm performs excellently in the task of high-altitude flying object classification based on radiation characteristics.

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Section: Introductionmentioning

confidence: 99%

Classification of High-Altitude Flying Objects Based on Radiation Characteristics with Attention-Convolutional Neural Network and Gated Recurrent Unit Network

Dai,

Cao,

Liu

et al. 2023

Remote Sensing

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“…In the absence of practical experiments, the IR simulations of targets are widely used in the simulation measurement of aircraft radiation characteristics [ 17 , 18 , 19 , 20 , 21 ]. As for IR signal characteristics of aircraft skin and exhaust plume, Lu et al [ 22 ] established the IR signature synthetic model on the basis of the computational fluid dynamics and the reverse Monte Carlo (RMC) method, which can accurately simulate the IR characteristics of an aircraft.…”

Section: Introductionmentioning

confidence: 99%

Integrated Infrared Radiation Characteristics of Aircraft Skin and the Exhaust Plume

Zhang

Jiang

et al. 2022

Materials

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Infrared radiation (IR) characteristics are important parameters for detecting, identifying, and striking military targets in the context of systematic countermeasures. Accurate calculation of IR characteristics for aircraft is significant for the simulation of war situations and the designation of combat strategy. In this work, integrated IR characteristics of aircraft skin and exhaust plume and their interaction are investigated by considering the reflection based on a bi-directional reflectance distribution function and various influence factors such as solar irradiation, ground reflection, aerodynamic heating, and projection radiation from the background. Combined with infrared emission and reflection characteristics of the skin, omnidirectional IR intensity distributions of 3−5 μm and 8−14 μm at different Mach numbers are obtained. The exhaust plume IR characteristic for different waves and wavebands are also investigated by considering the presence or absence of base and the difference in nozzle inlet temperature. On this basis, integrated IR characteristics between the skin and exhaust plume are investigated. Results show that aircraft IR characteristics of 3−5 μm are concentrated in the exhaust plume and high-temperature skin near the exhaust plume, while the signals of 8−14 μm are concentrated in the skin. The research results are expected to supply guidance for better detection and identification of typical flight targets.

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“…Different temperature targets have higher thermal contrast in the mid-wave infrared band, making it easier to distinguish between them. The corresponding wavelength of the 600-1000 Kelvin object radiation power peak is the mid-wave, which makes the midwave infrared have superior thermal infrared high-temperature object monitoring ability [9].…”

Section: Introductionmentioning

confidence: 99%

A Compact Mid-Wave Infrared Imager System With Real-Time Target Detection and Tracking

Deng

Wang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Research on a Measurement Method for Middle-Infrared Radiation Characteristics of Aircraft

Cited by 7 publications

References 10 publications

Classification of High-Altitude Flying Objects Based on Radiation Characteristics with Attention-Convolutional Neural Network and Gated Recurrent Unit Network

Classification of High-Altitude Flying Objects Based on Radiation Characteristics with Attention-Convolutional Neural Network and Gated Recurrent Unit Network

Integrated Infrared Radiation Characteristics of Aircraft Skin and the Exhaust Plume

A Compact Mid-Wave Infrared Imager System With Real-Time Target Detection and Tracking

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