Online Sequential Compressed Sensing With Multiple Information for Through-the-Wall Radar Imaging

Becquaert, Mathias; Cristofani, Edison; Lauwens, Ben; Vandewal, Marijke; Stiens, Johan; Deligiannis, Nikos

doi:10.1109/jsen.2019.2898274

Cited by 10 publications

(4 citation statements)

References 34 publications

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“…This feature is not present in the echoes of other stationary subjects, and thus human targets can be recognized. Due to the penetrating nature of electromagnetic waves, through-wall detection has been widely used in concealed target detection behind obstacles [5,6]. The elaboration of the concept of small-displacement detection related to human vital signs based on a radar system and the concept of throughwall detection prompted studies to develop methods for detecting living human targets behind walls.…”

Section: Introductionmentioning

confidence: 99%

A Clutter Identification and Removal Method Based on Long Delay Lines and Cross-Correlation in Through-Wall Detection

Yuan,

Ji,

et al. 2024

Applied Sciences

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Life detection is important in earthquake rescue, but weak vital signal is susceptible to interference by clutters. Due to the undesirable characteristics of the hardware, there are two main types of clutter generated by the frequency modulation continuous wave (FMCW) radar when transmitting signals. One is generated by periodic nonlinearity during frequency modulation, and the other is generated by the phase-locked loop spuriousness (PLLS) in frequency division. They cause additional beat frequencies to appear beside those from the target, leading to false alarms. Since the suppression measures for them are different, it is necessary to distinguish the types of clutter and choose appropriate suppression methods. In this paper, the accurate theoretical modeling of the effects of the periodic nonlinearity and phase-locked loop spuriousness on the beat signal is performed to determine distinctions between them. The clutter occurring in the system used is identified as originating from phase-locked loop spuriousness through fiber-optic experiments. A method using long delay lines and cross-correlation is proposed to identify and remove it. In experiments, the false alarm rate is reduced from over 50 percent to nearly 0 percent, providing strong evidence for the effectiveness of the proposed method in through-wall detection.

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Section: Introductionmentioning

confidence: 99%

A Clutter Identification and Removal Method Based on Long Delay Lines and Cross-Correlation in Through-Wall Detection

Yuan,

Ji,

et al. 2024

Applied Sciences

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“…This scenario, known as prior image-constrained reconstruction, is of particular significance when, for instance, the same object evolving over time is to be imaged multiple times. It finds applications in several scientific and medical imaging situations, such as monitoring tumor progression or perfusion (Chen et al, 2008), multi-contrast magnetic resonance imaging (MRI) (Weizman et al, 2016), or sequential radar imaging (Becquaert et al, 2019). Traditionally, this problem has been solved by assuming that the difference between the object of interest and the prior image is sparse in some domain (Chen et al, 2008;Mota et al, 2017), and solving an optimization problem penalizing this difference.…”

Section: Introductionmentioning

confidence: 99%

“…Since the disentangled latent representation of an image is crucial, several studies have focused on stylegan inversion (Wulff & Torralba, 2020;Abdal et al, 2019). Prior image-constrained compressed sensing has been studied previously from the theoretical (Mota et al, 2017) point of view, to applications (Chen et al, 2008;Becquaert et al, 2019). Some studies have used adaptive weights on the prior image and the image estimate to better model the differences between the ground truth and the prior image (Weizman et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Prior Image-Constrained Reconstruction using Style-Based Generative Models

Kelkar¹,

Anastasio²

2021

Preprint

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Obtaining an accurate and reliable estimate of an object from highly incomplete imaging measurements remains a holy grail of imaging science. Deep learning methods have shown promise in learning object priors or constraints to improve the conditioning of an ill-posed imaging inverse problem. In this study, a framework for estimating an object of interest that is semantically related to a known prior image, is proposed. An optimization problem is formulated in the disentangled latent space of a style-based generative model, and semantically meaningful constraints are imposed using the disentangled latent representation of the prior image. Stable recovery from incomplete measurements with the help of a prior image is theoretically analyzed. Numerical experiments demonstrating the superior performance of our approach as compared to related methods are presented.

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“…Compressed sensing (CS) is an efficient theory for signal compression [1], widely applied in medical imaging, radar imaging, and wireless sensors [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Incoherence Analysis of RD-AIC-Based Observation Matrix and Its Application in Power Quality Disturbance Signal

Liu

Tang

2021

Mathematical Problems in Engineering

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In the theory of compressed sensing, restricted isometry property (RIP) decides the universality and reconstruction robustness of an observation matrix. At present, an observation matrix based on RD-AIC (RD-AIC-based observation matrix) can compress sparse continuous signals with a simple structure, but RIP analysis of this matrix is lack and challenging to prove. In this paper, this problem is relaxed. Instead, we demonstrate the incoherence analysis process, derive the orthogonality and nonsingularity of the matrix, propose the generalized relevance calculation steps of the matrix, and propose the hardware parameter design principles to improve the incoherence of the matrix. Moreover, compression and reconstruction experiments used in power quality disturbance signals are developed for testing the incoherence. The results show that the RD-AIC-based observation matrix has substantial incoherence under suitable hardware parameters, equivalent to the Gaussian random matrix and the Bernoulli random matrix.

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Online Sequential Compressed Sensing With Multiple Information for Through-the-Wall Radar Imaging

Cited by 10 publications

References 34 publications

A Clutter Identification and Removal Method Based on Long Delay Lines and Cross-Correlation in Through-Wall Detection

A Clutter Identification and Removal Method Based on Long Delay Lines and Cross-Correlation in Through-Wall Detection

Prior Image-Constrained Reconstruction using Style-Based Generative Models

Incoherence Analysis of RD-AIC-Based Observation Matrix and Its Application in Power Quality Disturbance Signal

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