Aircraft Target Classification Method Based on Texture Feature of Laser Echo Time-Frequency Image

Yunpeng, 王云鹏 Wang; Yihua, 胡以华 Hu; Wuhu, 雷武虎 Lei; Liren, 郭力仁 Guo

doi:10.3788/aos201737.1128004

Cited by 4 publications

(4 citation statements)

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“…In the field of aircraft target classification and identification, the research on broadband radar is widely reported, and most of its main methods are based on high-resolution range profile [1][2][3], inverse synthetic aperture imaging [4,5], and image processing [6][7][8]. New regime radars, such as MIMO radar [9][10][11], have achieved high precision target tracking and superresolution estimation of parameters, and many useful explorations have already been conducted in the field of target identification.…”

Section: Introductionmentioning

confidence: 99%

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Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect

Xia¹,

Zhang²,

Cai³

et al. 2022

Mathematical Problems in Engineering

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For a conventional narrowband radar system, its insufficient bandwidth usually leads to the lack of detectable information of the target, and it is difficult for the radar to classify the target types, such as rotor helicopter, propeller aircraft, and jet aircraft. To address the classification problem of three different types of aircraft target, a joint multifeature classification method based on the micro-Doppler effect in the echo caused by the target micromotion is proposed in this paper. Through the characteristics analysis of the target simulation echoes obtained from the target scattering point model, four features with obvious distinguishability are extracted from the time domain and frequency domain, respectively, that is, flicker interval, fractal dimension, modulation bandwidth, and second central moment. Then, a support vector machine model will be applied to the classification of the three different types of aircraft. Compared with the conventional method, the proposed method has better classification performance and can significantly improve the classification probability of aircraft target. The simulations are carried out to validate the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

“…e first term in (7) is the Doppler frequency caused by target translation f d � 2v Τ n/λ, and the second term is the micro-Doppler frequency caused by rotation. Substituting (6). we can obtain…”

mentioning

confidence: 99%

Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect

Xia¹,

Zhang²,

Cai³

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…It is an important method in communication [1] and detection [2] to use the optical wave as carrier to transmit information. If there is no influence of atmospheric turbulence, the echo signal of detected target [3] [4] remains unchanged. The value of echo signal is determined by transmission shape of transmitter and diffraction effect, which is easy to be observed.…”

Section: Introductionmentioning

confidence: 99%

Influence Characteristics of Laser Transmission Amplitude Fluctuation Based on Turbulent Medium

Yang¹,

Gao²

2020

OPJ

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In order to study the transmission characteristics of laser in atmospheric turbulent medium and understand the influence degree of various factors on amplitude fluctuation, by means of smooth perturbation method, this paper establishes a theory model of amplitude fluctuation of laser propagation in turbulent medium by using the smooth perturbation method and reflects the amplitude fluctuation degree, carries out specific discussion on each influence factor. The results show that the larger the wavelength, the more stable the amplitude fluctuation. With the increase of laser section radius, the amplitude fluctuates sharply and then decreases slowly after reaching the peak. Transmission distance is the main influence factor of amplitude fluctuation. With the increase of transmission distance, the amplitude fluctuation will become more obvious. The amplitude acquisition can be comprehensively modulated in a specific transmission distance by wavelength and section radius, so as to ensure the stability of the received laser and provide a theoretical basis for the interferometry technology.

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“…(1) methods based on image processing [1][2][3][4][5]. In Reference [6], the extracted image, instead of radar data, was fed into a three-layered feed forward artificial neural network for aircraft classification;…”

Section: Introductionmentioning

confidence: 99%

Aircraft Target Classification for Conventional Narrow-Band Radar with Multi-Wave Gates Sparse Echo Data

Wang¹,

Tang²,

Chen³

et al. 2019

Remote Sensing

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For a conventional narrow-band radar system, the detectable information of the target is limited, and it is difficult for the radar to accurately identify the target type. In particular, the classification probability will further decrease when part of the echo data is missed. By extracting the target features in time and frequency domains from multi-wave gates sparse echo data, this paper presents a classification algorithm in conventional narrow-band radar to identify three different types of aircraft target, i.e., helicopter, propeller and jet. Firstly, the classical sparse reconstruction algorithm is utilized to reconstruct the target frequency spectrum with single-wave gate sparse echo data. Then, the micro-Doppler effect caused by rotating parts of different targets is analyzed, and the micro-Doppler based features, such as amplitude deviation coefficient, time domain waveform entropy and frequency domain waveform entropy, are extracted from reconstructed echo data to identify targets. Thirdly, the target features extracted from multi-wave gates reconstructed echo data are weighted and fused to improve the accuracy of classification. Finally, the fused feature vectors are fed into a support vector machine (SVM) model for classification. By contrast with the conventional algorithm of aircraft target classification, the proposed algorithm can effectively process sparse echo data and achieve higher classification probability via weighted features fusion of multi-wave gates echo data. The experiments on synthetic data are carried out to validate the effectiveness of the proposed algorithm.

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Aircraft Target Classification Method Based on Texture Feature of Laser Echo Time-Frequency Image

Cited by 4 publications

References 0 publications

Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect

Aircraft Target Classification Method for Conventional Narrowband Radar Based on Micro-Doppler Effect

Influence Characteristics of Laser Transmission Amplitude Fluctuation Based on Turbulent Medium

Aircraft Target Classification for Conventional Narrow-Band Radar with Multi-Wave Gates Sparse Echo Data

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