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Online Sparse Recon...
Online Sparse Reconstruction for Scanning Radar Using Beam-Updating q-SPICE
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- Zhang, Yongchao (författare)
- University of Electronic Science and Technology of China
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- Li, Jie (författare)
- University of Electronic Science and Technology of China
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- Li, Minghui (författare)
- University of Electronic Science and Technology of China
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- Zhang, Yin (författare)
- University of Electronic Science and Technology of China
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- Luo, Jiawei (författare)
- University of Electronic Science and Technology of China
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- Huang, Yulin (författare)
- University of Electronic Science and Technology of China
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- Yang, Jianyu (författare)
- University of Electronic Science and Technology of China
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- Jakobsson, Andreas (författare)
- Lund University,Lunds universitet,Biomedical Modelling and Computation,Forskargrupper vid Lunds universitet,Statistical Signal Processing Group,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Lund University Research Groups,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
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(creator_code:org_t)
- 2022
- 2022
- Engelska.
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Ingår i: IEEE Geoscience and Remote Sensing Letters. - 1545-598X. ; 19
- Relaterad länk:
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http://dx.doi.org/10...
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https://lup.lub.lu.s...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- The generalized sparse iterative covariance-based estimation ( $q$ -SPICE) algorithm was recently introduced for scanning radar applications, resulting in substantial improvements in the angular resolution and quality of the processed images. Regrettably, the computational complexity and storage cost are high and quickly increase with growing data size, limiting the applicability of the estimator. In this letter, we strive to alleviate this problem, deriving a beam-updating $q$ -SPICE algorithm, allowing for efficiently updating of the sparse reconstruction result for each online radar measurement along the scanned beam. The resulting method is a regularized extension of the current online $q$ -SPICE implementation, which not only offers constant computational and storage cost, independent of the data size, but also provides enhanced robustness over the current online $q$ -SPICE. Our experimental assessment, conducted using both simulated and real data, demonstrates the advantage of the beam-updating $q$ -SPICE method in the task of sparse reconstruction for scanning radar.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
Nyckelord
- Batch processing
- beam-updating q-SPICE
- online sparse reconstruction
- scanning radar
- sparse iterative covariance-based estimation (SPICE)
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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