Direction of arrival estimation based on slope fitting of wideband array signal in fractional Fourier transform domain

Zhong, Jun; Chen, Tingting; Peng, Fei; Bi, Xiaojun; Chen, Zhong

doi:10.1049/rsn2.12350

Cited by 3 publications

(3 citation statements)

References 25 publications

(25 reference statements)

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“…When point 𝐶 on the point line is a point on the signal, the slope of line 𝑙 𝐴𝐶 is not zero. When the signal waveform changes suddenly, the slope between adjacent maximum points changes [28]. That is, the slope is an important indicator of waveform change trend.…”

Section: Relationship Between Slope Integral and Waveformmentioning

confidence: 99%

Study of slope integral extension mode decomposition method for bearing-nonlinear vibration signal

Dai¹,

Huang²,

Shi³

2023

J. vibroeng.

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This study aims to solve the problem of extreme point ambiguity caused by energy instability at the signal end. Thus, an adaptive nonlinear signal decomposition method based on motion energy accumulation division is proposed, namely slope integral extension mode decomposition (SIEMD). The proposed method considers the fluctuation rate and vibration energy between the peaks of the waveform as its scale. Firstly, the comprehensive index is defined to adaptively select the ideal interval, and the extension characteristics of the waveform signal are obtained. Secondly, the energy of the waveform interval is iterated. Hence, the optimal extension waveform is fitted by combining the edge position information of the curve. The experimental part verifies that the method can extract 92 % of the fault information, and verifies that the proposed method overcomes the limitation of the previous one-dimensional signal waveform dimension. Moreover, from the perspective of signal energy, it eliminates the false information of the intrinsic modal function (IMF) components, more suitable for the randomness of the signal, thereby providing a new way for fault feature extraction.

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Section: Relationship Between Slope Integral and Waveformmentioning

confidence: 99%

Study of slope integral extension mode decomposition method for bearing-nonlinear vibration signal

Dai¹,

Huang²,

Shi³

2023

J. vibroeng.

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“…In the past decades, time-frequency analysis (TFA) has become an important research topic in modern signal processing [1][2][3]. Time-frequency analysis can reflect the distribution of instantaneous frequencies of non-stationary signals, and has been widely used in biomedicine [4,5], geophysics [6], and electronic communication [7][8][9][10][11]. For example, in electronic countermeasures, TFA is used as an essential tool to detect the signal of interest in a complex electromagnetic environment with a large number of interfering signals.…”

Section: Introductionmentioning

confidence: 99%

WVD‐GAN: A Wigner‐Ville distribution enhancement method based on generative adversarial network

Quan,

Ren,

Wang

et al. 2024

IET Radar Sonar & Navi

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Time‐frequency analysis based on Wigner‐Ville distribution (WVD) plays a significant role in analysing non‐stationary signals, but it is susceptible to interference from cross‐terms (CTs) for multi‐component signals. To address this issue, a novel WVD enhancement method based on generative adversarial networks (namely WVD‐GAN) is proposed, to achieve highly‐concentrated time‐frequency (TF) representation. Specifically, a deep feature extraction module is designed with multiple residual connections in the generator of WVD‐GAN to leverage the latent information encoded in the shallow representations. Meanwhile, a simple and effective attention module is introduced to enhance auto‐term features. Moreover, a multi‐scale discriminator is proposed based on dilated convolutions to guide the generator to reconstruct high‐resolution TF images by discriminating CT. Finally, a comparative analysis is provided to demonstrate the effectiveness and robustness of the proposed method on different simulated and real‐life datasets. Extensive experiments demonstrate that the proposed method outperforms several state‐of‐the‐art methods.

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“…Fortunately, two-dimensional (2-D) DOA estimation can solve the above problem. Now, the 2-D direction of arrival estimation problem is widely used in radar, internet of vehicle (IOV) and the fifth-generation (5 G) mobile communications [ 1 , 2 , 3 , 4 , 5 , 6 ]. And many algorithms have been developed to solve the problem of DOA estimation, such as improved reduced dimension MUSIC (IRD-MUSIC), the reduced-dimension multiple signal classification algorithm, and so on [ 7 , 8 , 9 , 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

An L-Shaped Three-Level and Single Common Element Sparse Sensor Array for 2-D DOA Estimation

Cui

et al. 2023

Sensors

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The degree of freedom (DOF) is an important performance metric for evaluating the design of a sparse array structure. Designing novel sparse arrays with higher degrees of freedom, while ensuring that the array structure can be mathematically represented, is a crucial research direction in the field of direction of arrival (DOA) estimation. In this paper, we propose a novel L-shaped sparse sensor array by adjusting the physical placement of the sensors in the sparse array. The proposed L-shaped sparse array consists of two sets of three-level and single-element sparse arrays (TSESAs), which estimate the azimuth and elevation angles, respectively, through one-dimensional (1-D) spatial spectrum search. Each TSESA is composed of a uniform linear subarray and two sparse subarrays, with one single common element in the two sparse subarrays. Compared to existing L-shaped sparse arrays, the proposed array achieves higher degrees of freedom, up to 4Q1Q2+8Q1−5, when estimating DOA using the received signal covariance. To facilitate the correct matching of azimuth and elevation angles, the cross-covariance between the two TSESA arrays is utilized for estimation. By comparing and analyzing performance parameters with commonly used L-shaped and other sparse arrays, it is found that the proposed L-shaped TSESA has higher degrees of freedom and array aperture, leading to improved two-dimensional (2-D) DOA estimation results. Finally, simulation experiments validate the excellent performance of the L-shaped TSESA in 2-D DOA estimation.

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Direction of arrival estimation based on slope fitting of wideband array signal in fractional Fourier transform domain

Cited by 3 publications

References 25 publications

Study of slope integral extension mode decomposition method for bearing-nonlinear vibration signal

Study of slope integral extension mode decomposition method for bearing-nonlinear vibration signal

WVD‐GAN: A Wigner‐Ville distribution enhancement method based on generative adversarial network

An L-Shaped Three-Level and Single Common Element Sparse Sensor Array for 2-D DOA Estimation

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