Thorough Understanding and 3D Super-Resolution Imaging for Forward-Looking Missile-Borne SAR via a Maneuvering Trajectory

For missile-borne platforms, traditional SAR technology consistently encounters two significant shortcomings: geometric distortion of 2D images and the inability to achieve forward-looking imaging. To address these issues, this paper explores the feasibility of using a maneuvering trajectory to enab...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Vol. 16; no. 18; p. 3378
Main Authors: Gu, Tong, Guo, Yifan, Zhao, Chen, Zhang, Jian, Zhang, Tao, Liao, Guisheng
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.09.2024
Subjects:
Algorithms
axis rotation
Bandwidths
compress sensing
Data reduction
forward-looking
geometry
Guided missiles
Image reconstruction
Image resolution
maneuvering
Maneuvers
Mathematical models
Numerical analysis
Parameters
Position sensing
Rockets (Ordnance)
Rotation
Simulation
Simulation methods
Spectrum allocation
super-resolution
Systems design
Three dimensional analysis
Three dimensional imaging
Two dimensional analysis
Vertical orientation
China
ISSN:2072-4292, 2072-4292
Online Access:Get full text
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Summary:For missile-borne platforms, traditional SAR technology consistently encounters two significant shortcomings: geometric distortion of 2D images and the inability to achieve forward-looking imaging. To address these issues, this paper explores the feasibility of using a maneuvering trajectory to enable forward-looking and three-dimensional imaging by analyzing the maneuvering characteristics of an actual missile-borne platform. Additionally, it derives the corresponding resolution characterization model, which lays a theoretical foundation for future applications. Building on this, the paper proposes a three-dimensional super-resolution imaging algorithm that combines axis rotation with compressed sensing. The axis rotation not only realizes the dimensionality reduction of data, but also can expand the observation scenario in the cross-track dimension. The proposed algorithm first focuses on the track-vertical plane to extract 2D position parameters. Then, a compressed sensing-based process is applied to extract reflection coefficients and super-resolution cross-track position parameters, thereby achieving precise 3D imaging reconstruction. Finally, numerical simulation results confirm the effectiveness and accuracy of the proposed algorithm.
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ISSN:2072-4292
2072-4292
DOI:10.3390/rs16183378