Near Field 3-D Millimeter-Wave SAR Image Enhancement and Detection with Application of Antenna Pattern Compensation.

Shaoqiu Song, Jie Lu, Shiqi Xing, Sinong Quan, Junpeng Wang, Yongzhen Li, Jing Lian

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

Improved Methods for Fourier-Based Microwave Imaging.Sensors (Basel, Switzerland) · 2023
Article

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5 · Who and what money

Authors and funding

7 authors.

Shaoqiu SongCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.

Jie LuCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.

Shiqi XingCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.

Sinong QuanCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.ORCID 0000-0002-6908-1975

Junpeng WangCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.

Yongzhen LiCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.

Jing LianCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, a novel near-field high-resolution image focusing technique is proposed. With the emergence of Millimeter-wave (mmWave) devices, near-field synthetic aperture radar (SAR) imaging is widely used in automotive-mounted SAR imaging, UAV imaging, concealed threat detection, etc. Current research is mainly confined to the laboratory environment, thus ignoring the adverse effects of the non-ideal experimental environment on imaging and subsequent detection in real scenarios. To address this problem, we propose an optimized Back-Projection Algorithm (BPA) that considers the loss path of signal propagation among space by converting the amplitude factor in the echo model into a beam-weighting. The proposed algorithm is an image focusing algorithm for arbitrary and irregular arrays, and effectively mitigates sparse array imaging ghosts. We apply the 3DRIED dataset to construct image datasets for target detection, comparing the kappa coefficients of the proposed scheme with those obtained from classic BPA and Range Migration Algorithm (RMA) with amplitude loss compensation. The results show that the proposed algorithm attains a high-fidelity image reconstruction focus.

Indexed as

high-fidelityimage reconstruction focusingkappa coefficientsmmWavenear-fieldSAR

Identifiers

PMID35746289

DOI10.3390/s22124509

PMCPMC9229681

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.