Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/87738
Title: Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery
Authors: Ma, Changzheng
Yeo, Tat Soon
Ng, Boon Poh
Keywords: Multidimensional Linear Equations
MIMO Radar
Issue Date: 2018
Source: Ma, C., Yeo, T. S., & Ng, B. P. (2018). Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery. IET Radar, Sonar & Navigation, 12(1), 3-10.
Series/Report no.: IET Radar, Sonar & Navigation
Abstract: Multiple input multiple output (MIMO) radar forms large virtual aperture and improves the cross-range resolution of radar imaging. Sparse signal recovery algorithms can be used to improve image quality of target with sparse property in spatial domain. Conventional sparse signal recovery-based MIMO radar imaging method rearranges the received two-dimensional (2D) or 3D signals into a vector, then linear equations describing the relation between the received signal and the reflectivity of the scatterers are solved. However, this method occupies huge memory spaces and increases the computational load. In this study, by introducing synthetic codes, multidimensional linear equations of MIMO radar imaging are derived, which occupy less memory spaces and cost less computationally. A L1 L0 norms homotopy sparse signal recovery algorithm for multidimensional linear equations is used to recover the image. Simulation results verify the high efficiency of using multidimensional linear equations.
URI: https://hdl.handle.net/10356/87738
http://hdl.handle.net/10220/45479
ISSN: 1751-8784
DOI: 10.1049/iet-rsn.2017.0149
Rights: © 2017 Institution of Engineering and Technology. This paper was published in IET Radar, Sonar & Navigation and is made available as an electronic reprint (preprint) with permission of Institution of Engineering and Technology. The published version is available at: [http://dx.doi.org/10.1049/iet-rsn.2017.0149]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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