Inverse synthetic aperture radar imaging of targets with complex motion based on cubic Chirplet decomposition

Wang, Yong; Zhao, Bin; Jiang, Yicheng

doi:10.1049/iet-spr.2014.0086

Cited by 21 publications

(13 citation statements)

References 41 publications

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“…Figure 10 are the instantaneous radar images at the same time positions as Figure 8 and Figure 9 based on the modified version of Chirplet decomposition algorithm proposed in [31], and the instantaneous radar images based on the novel modified version of Chirplet decomposition algorithm proposed in this paper are shown in Figure 11.…”

Section: Radar Imaging Resultsmentioning

confidence: 99%

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Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation

Wang

2015

Sensors

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A novel radar imaging approach for non-uniformly rotating targets is proposed in this study. It is assumed that the maneuverability of the non-cooperative target is severe, and the received signal in a range cell can be modeled as multi-component amplitude-modulated and frequency-modulated (AM-FM) signals after motion compensation. Then, the modified version of Chirplet decomposition (MCD) based on the integrated high order ambiguity function (IHAF) is presented for the parameter estimation of AM-FM signals, and the corresponding high quality instantaneous ISAR images can be obtained from the estimated parameters. Compared with the MCD algorithm based on the generalized cubic phase function (GCPF) in the authors’ previous paper, the novel algorithm presented in this paper is more accurate and efficient, and the results with simulated and real data demonstrate the superiority of the proposed method.

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Section: Radar Imaging Resultsmentioning

confidence: 99%

“…Radar image based on modified version of Chirplet decomposition algorithm proposed in [31]. ( a ) Radar image at time t = 0.17 s; ( b ) Radar image at time t = 0.22 s.…”

Section: Radar Imaging Resultsmentioning

confidence: 99%

Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation

Wang

2015

Sensors

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“…At present, there are many kinds of optimization methods available in machine learning and deep learning [33][34][35]. The simplest and most commonly used method is the gradient descent method [20,36], so we used this method to accurately estimate the rotation ratio.…”

Section: Accurate Rotation Ratio Estimation Based On Minimum Entropymentioning

confidence: 99%

“…Research shows that target approximation satisfies the first-order linear motion with a short imaging time, so the target scattering point azimuth echo signal can be approximated as a multi-component chirp signal (LFM) [1]. The ratio of the quadratic phase term (chirp rate) to the first-order phase term (central frequency) of the scattering point echo signal is approximately a fixed value and equal to the ratio of the target rotational angular acceleration to the rotational angular velocity [19,20]. Given this feature, an imaging algorithm based on matched Fourier transform (MFT) [21] is proposed in this study, but this algorithm only uses a single sub-echo signal for parameter estimation and the estimation error is large.…”

Section: Introductionmentioning

confidence: 99%

A Novel Inverse Synthetic Aperture Radar Imaging Method for Maneuvering Targets Based on Modified Chirp Fourier Transform

Wang

et al. 2018

Applied Sciences

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When inverse synthetic aperture radar (ISAR) imaging maneuvers targets, the azimuth echo of the target scattering point causes a Doppler frequency time-varying problem, which leads to the blurring and defocusing of the imaging results. Traditional imaging methods struggle to meet the imaging requirements for maneuvering targets due to a poor imaging effect or low efficiency. Given these challenges, a modified chirp Fourier transform (MCFT) imaging method is proposed in this paper, based on the specific relationship between the target rotation parameters and the radar echo signal parameters. Firstly, discrete chirp Fourier transform is used to quickly estimate the target’s coarse rotation ratio. Then, the minimum entropy function and gradient descent method are used to calculate the target’s accurate rotation ratio. Finally, the azimuth focusing image is accomplished by performing MCFT once on the azimuth echo signal using the accurate rotation ratio. This method avoids estimating and separating the sub-echo components one-by-one, considerably improves the imaging speed, and guarantees the best imaging quality by applying the global minimum entropy principle. The experimental results show that the proposed method effectively achieves the two-dimensional, high-quality, and fast imaging of maneuvering targets.

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“…In addition to improving the process of the OMP algorithm, researchers have been the subjects of intense research for selection of the dictionary. Studies show that the dictionary has a great influence on the performance of the OMP algorithm [34,35]. To date, Gabor dictionary is widely used and has a better performance in signal processing.…”

Section: The Dictionarymentioning

confidence: 99%

Enhanced Orthogonal Matching Pursuit Algorithm and Its Application in Mechanical Equipment Fault Diagnosis

Luo

2017

Shock and Vibration

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The vibration signal measured from the mechanical equipment is associated with the operation of key structure, such as the rolling bearing and gear. The effective signal processing method for early weak fault has attracted much attention and it is of vital importance in mechanical fault monitoring and diagnosis. The recently proposed atomic sparse decomposition algorithm is performed around overcomplete dictionary instead of the traditional signal analysis method using orthogonal basis operator. This algorithm has been proved to be effective in extracting useful components from complex signal by reducing influence of background noises. In this paper, an improved linear frequency-modulated (Ilfm) function as an atom is employed in the proposed enhanced orthogonal matching pursuit (EOMP) algorithm. Then, quantum genetic algorithm (QGA) with the OMP algorithm is integrated since the QGA can quickly obtain the global optimal solution of multiple parameters for rapidly and accurately extracting fault characteristic information from the vibration signal. The proposed method in this paper is superior to the traditional OMP algorithm in terms of accuracy and reducing the computation time through analyzing the simulation data and real world data. The experimental results based on the application of gear and bearing fault diagnosis indicate that it is more effective than traditional method in extracting fault characteristic information.

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Inverse synthetic aperture radar imaging of targets with complex motion based on cubic Chirplet decomposition

Cited by 21 publications

References 41 publications

Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation

Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation

A Novel Inverse Synthetic Aperture Radar Imaging Method for Maneuvering Targets Based on Modified Chirp Fourier Transform

Enhanced Orthogonal Matching Pursuit Algorithm and Its Application in Mechanical Equipment Fault Diagnosis

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