MuA-SAR Fast Imaging Based on UCFFBP Algorithm with Multi-Level Regional Attention Strategy

Multistatic airborne SAR (MuA-SAR) benefits from the ability to flexibly adjust the positions of multiple transmitters and receivers in space, which can shorten the synthetic aperture time to achieve the required resolution. To ensure both imaging efficiency and quality of different system spatial c...

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Bibliographic Details
Published inRemote sensing (Basel, Switzerland) Vol. 15; no. 21; p. 5183
Main Authors Xu, Fanyun, Wang, Rufei, Huang, Yulin, Mao, Deqing, Yang, Jianyu, Zhang, Yongchao, Zhang, Yin
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.11.2023
Subjects
Algorithms
Cartesian coordinates
Communications equipment
Efficiency
GCCS
Imaging
Interpolation
MuA-SAR
multi-level regional attention strategy
Multistatic radar
phase compensation
Polar coordinates
Radar systems
Recursive functions
Regions
Transmitters
UCFFBP
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Summary:Multistatic airborne SAR (MuA-SAR) benefits from the ability to flexibly adjust the positions of multiple transmitters and receivers in space, which can shorten the synthetic aperture time to achieve the required resolution. To ensure both imaging efficiency and quality of different system spatial configurations and trajectories, the fast factorized back projection (FFBP) algorithm is proposed. However, if the FFBP algorithm based on polar coordinates is directly applied to the MuA-SAR system, the interpolation in the recursive fusion process will bring the problem of redundant calculations and error accumulation, leading to a sharp decrease in imaging efficiency and quality. In this paper, a unified Cartesian fast factorized back projection (UCFFBP) algorithm with a multi-level regional attention strategy is proposed for MuA-SAR fast imaging. First, a global Cartesian coordinate system (GCCS) is established. Through designing the rotation mapping matrix and phase compensation factor, data from different bistatic radar pairs can be processed coherently and efficiently. In addition, a multi-level regional attention strategy based on maximally stable extremal regions (MSER) is proposed. In the recursive fusion process, only the suspected target regions are paid more attention and segmented for coherent fusion at each fusion level, which further improves efficiency. The proposed UCFFBP algorithm ensures both the quality and efficiency of MuA-SAR imaging. Simulation experiments verified the effectiveness of the proposed algorithm.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs15215183