Sparse decoupling imaging network for wideband two‐dimensional MIMO radar imaging using model‐assisted and attention mechanism

Abstract The problem of sparse decoupling radar imaging methods based on deep learning is researched. An improved model‐driven learning imaging network with a complex‐valued convolution block attention module plugged into each sub‐network is proposed. This method can solve the high sidelobe and coupling problem in sparse wideband Multiple‐Input Multiple‐Output (MIMO) radar. In addition, it can better focus on the target area and capture target information to boost model representation power. Experimental results verify the validity of the proposed method.

Authors

Institutions

Publication Details

Journal
Electronics Letters
Published
2024-08-01
DOI
https://doi.org/10.1049/ell2.70000
Primary Topic
Microwave Imaging and Scattering Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sparse decoupling imaging network for wideband two‐dimensional MIMO radar imaging using model‐assisted and attention mechanism

Zhijin Wen, Yang Liu, Shanshan Ding, Nana Fan
Electronics Letters
Microwave Imaging and Scattering Analysis
article

Sparse decoupling imaging network for wideband two‐dimensional MIMO radar imaging using model‐assisted and attention mechanism

Zhijin Wen, Yang Liu, Shanshan Ding, Nana Fan
article en

Abstract

Abstract The problem of sparse decoupling radar imaging methods based on deep learning is researched. An improved model‐driven learning imaging network with a complex‐valued convolution block attention module plugged into each sub‐network is proposed. This method can solve the high sidelobe and coupling problem in sparse wideband Multiple‐Input Multiple‐Output (MIMO) radar. In addition, it can better focus on the target area and capture target information to boost model representation power. Experimental results verify the validity of the proposed method.

Electronics LettersVol. 60(16)
PLA Academy of Military Science (CN)
Openalex Percentile: Top 88%
Microwave Imaging and Scattering Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.