High-Efficiency and High-Precision Reconstruction Strategy for P-Band Ultra-Wideband Bistatic Synthetic Aperture Radar Raw Data Including Motion Errors

P-band ultra-wideband bistatic synthetic aperture radar (UWB BSAR) has the well capability of the foliage penetrating, high-resolution imaging and adding the scattered information, which is potential of detecting the concealed target. However, the P-band UWB BSAR raw data is of the huge amount, big...

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Bibliographic Details
Main Authors: Hongtu Xie, Jun Hu, Keqing Duan, Guoqian Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8981957/
Description
Summary:P-band ultra-wideband bistatic synthetic aperture radar (UWB BSAR) has the well capability of the foliage penetrating, high-resolution imaging and adding the scattered information, which is potential of detecting the concealed target. However, the P-band UWB BSAR raw data is of the huge amount, big spatial-variance, significant range azimuth coupling and complicated motion error, which increases the difficulty of the efficient and precise reconstruction. In this paper, we propose a reconstruction strategy for the P-band UWB BSAR raw data including the motion errors, which can solve the above problems with the high-efficiency and high-precision. This method requires the local beamforming from the raw data as an intermediate processing in the slant range plane instead of ground plane, which can be exactly referenced to the tracks of the transmitter and receiver considering platform altitudes. And, it derives the requirement for selecting the subapertures and subimages by analyzing the bistatic range error considering the motion errors, as well as sampling requirement of the beam for the subimages, which offers a near-optimum tradeoff between the precision and efficiency. Simulated and measured results show that the proposed strategy is effective, and can achieve the near optimal performance with the low computational complexity.
ISSN:2169-3536