Performance of STAR-Light receivers during CLPX

England, Anthony W.; Pham, H.; Roo, R.D. De; Nieuwstadt, L. van; Yam, Luis E.

doi:10.1109/igarss.2003.1294068

Cited by 1 publication

(1 citation statement)

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“…Synthetic Aperture Interferometric Radiometer (SAIR) technology represents a promising new approach to passive millimeter wave imaging for high-resolution observations of the target scene, both in near field and far field, which can be applied to areas such as indoor security, aircraft navigation, environment monitoring, atmosphere monitoring and so on [1,2,3]. Based on coherent signal processing, SAIR measures the correlation between pairs of various nondirective antennas to achieve a larger aperture antenna, realizing high-resolution.…”

Section: Introductionmentioning

confidence: 99%

A Robust Reweighted L1-Minimization Imaging Algorithm for Passive Millimeter Wave SAIR in Near Field

Zhang

Zhu

et al. 2015

Sensors

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The Compressive Sensing (CS) approach has proven to be useful for Synthetic Aperture Interferometric Radiometer (SAIR) imaging because it provides the same high-resolution capability while using part of interferometric observations compared to traditional methods using the entirety. However, it cannot always obtain the sparsest solution and may yield outliers with the non-adaptive random measurement matrix adopted by current CS models. To solve those problems, this paper proposes a robust reweighted L1-minimization imaging algorithm, called RRIA, to reconstruct images accurately by combining the sparsity and prior information of SAIR images in near field. RRIA employs iterative reweighted L1-minimization to enhance the sparsity to reconstruct SAIR images by computing a new weight factor in each iteration according to the previous SAIR images. Prior information estimated by the energy functional of SAIR images is introduced to RRIA as an additional constraint condition to make the algorithm more robust for different complex scenes. Compared to the current basic CS approach, our simulation results indicate that RRIA can achieve better recovery with the same amount of interferometric observations. Experimental results of different scenes demonstrate the validity and robustness of RRIA.

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Section: Introductionmentioning

confidence: 99%