Direction Finding for Multiple Wideband Chirp Signal Sources using Blind Signal Separation and Matched Filtering

Kim, Min; Lee, Seong-Hyeon; Choi, In-Oh; Kim, Kyung-Tae

doi:10.1016/j.sigpro.2022.108642

Cited by 4 publications

(3 citation statements)

References 22 publications

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“…Blind source separation (BSS) [1,2] aims to recover or reconstruct the source signal using observed data from the receiver channel, even when the source signal and mixing characteristics are unknown. BSS, as a powerful technology in signal processing, has played a crucial role in various domains, including speech separation [3][4][5], wireless communication [6][7][8], anti-main lobe jamming [9][10][11][12][13], and direction of arrival (DOA) estimation [14,15]. BSS has also provided innovative ideas for ongoing research in integrated arrival (DOA) estimation [14,15].…”

Section: Introductionmentioning

confidence: 99%

“…BSS, as a powerful technology in signal processing, has played a crucial role in various domains, including speech separation [3][4][5], wireless communication [6][7][8], anti-main lobe jamming [9][10][11][12][13], and direction of arrival (DOA) estimation [14,15]. BSS has also provided innovative ideas for ongoing research in integrated arrival (DOA) estimation [14,15]. BSS has also provided innovative ideas for ongoing re search in integrated reception processing.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Complex-Valued Blind Source Separation and Its Applications in Integrated Reception

Luo,

Jin,

et al. 2023

Electronics

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The separation of time–frequency mixing signals composed of radar, communication, and jamming is the first step in integrated reception processing, which requires higher accuracy for complex blind source separation (CVBSS). However, traditional CVBSS methods have limitations such as low separation accuracy, a slow convergence speed, and poor robustness in low signal-to-noise ratio (SNR) and high jamming-to-signal ratio (JSR) scenarios. To address the above issues, this paper firstly establishes a time delay mixing mathematical model. A robust whitening algorithm is proposed by using the time delay correlation matrix of the observed signal, which is insensitive to noise. Secondly, the joint diagonalized F-parametrization is used as the objective function, and the separation matrix is constructed based on the multiple complex-valued Givens matrices. The complex-valued Givens matrix not only ensures orthogonality in the separation matrix but also effectively reduces the number of parameters to be calculated. This approach guarantees accuracy and simplifies the complexity of the separation process. Finally, the nonlinear chaotic grey wolf optimizer is utilized to search for the optimal rotation angle. The simulation results demonstrate that this algorithm offers higher separation accuracy and requires fewer iterations compared to the traditional algorithm. Additionally, it enhances the accuracy of direction of arrival (DOA) estimation, reduces the communication bit error rate, and enables the joint estimation of the target distance and velocity even in the presence of powerful jamming and a low SNR.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Complex-Valued Blind Source Separation and Its Applications in Integrated Reception

Luo,

Jin,

et al. 2023

Electronics

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“…Spatial time–frequency distribution (STFD)-based methods [ 12 , 13 ] can directly exploit the nonstationarity information of LFM signals but are highly dependent on time–frequency point selection [ 12 ]. Matched filtering (MF)-based methods [ 14 , 15 ] possess a high noise resistance by treating MF as pre-processing or post-processing of beamforming.…”

Section: Introductionmentioning

confidence: 99%

Deconvolved Fractional Fourier Domain Beamforming for Linear Frequency Modulation Signals

Liu

Tao

Sun

et al. 2023

Sensors

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To estimate the direction of arrival (DOA) of a linear frequency modulation (LFM) signal in a low signal-to-noise ratio (SNR) hydroacoustic environment by a small aperture array, a novel deconvolved beamforming method based on fractional Fourier domain delay-and-sum beamforming (FrFB) was proposed. Fractional Fourier transform (FrFT) was used to convert the received signal into the fractional Fourier domain, and delay-and-sum beamforming was subsequently performed. Noise resistance was acquired by focusing the energy of the LFM signal distributed in the time–frequency domain. Then, according to the convolution structure of the FrFB complex output, the influence of the fractional Fourier domain complex beam pattern was removed by deconvolution, and the target spatial distribution was restored. Therefore, an improved spatial resolution of DOA estimation was obtained without increasing the array aperture. The simulation and experimental results show that, with a small aperture array at low SNR, the proposed method possesses higher spatial resolution than FrFB and frequency-domain deconvolved conventional beamforming.

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Blind source separation in 3rd generation gravitational-wave detectors

Badaracco,

Banerjee,

Branchesi

et al. 2024

New Astronomy Reviews

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Direction Finding for Multiple Wideband Chirp Signal Sources using Blind Signal Separation and Matched Filtering

Cited by 4 publications

References 22 publications

A Novel Complex-Valued Blind Source Separation and Its Applications in Integrated Reception

A Novel Complex-Valued Blind Source Separation and Its Applications in Integrated Reception

Deconvolved Fractional Fourier Domain Beamforming for Linear Frequency Modulation Signals

Blind source separation in 3rd generation gravitational-wave detectors

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