Imaging algorithm for circular trace scanning synthetic aperture radar using modified hyperbolic range equation

2013 ◽  
Vol 49 (20) ◽  
pp. 1296-1298 ◽  
Author(s):  
Yi Liao ◽  
Mengdao Xing ◽  
Zheng Bao
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Imaging Algorithm ◽  
Range Equation ◽  
Aperture Radar

scholarly journals Frequency Domain Panoramic Imaging Algorithm for Ground-Based ArcSAR

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7027
Author(s):  
Yun Lin ◽  
Yutong Liu ◽  
Yanping Wang ◽  
Shengbo Ye ◽  
Yuan Zhang ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Frequency Domain ◽  
Matched Filter ◽  
Deformation Monitoring ◽  
Polar Coordinates ◽  
Fast Imaging ◽  
Synthetic Aperture ◽  
Imaging Algorithm ◽  
Imaging Algorithms ◽  
Aperture Radar

The ground-based arc-scanning synthetic aperture radar (ArcSAR) is capable of 360° scanning of the surroundings with the antenna fixed on a rotating arm. ArcSAR has much wider field of view when compared with conventional ground-based synthetic aperture radar (GBSAR) scanning on a linear rail. It has already been used in deformation monitoring applications. This paper mainly focuses on the accurate and fast imaging algorithms for ArcSAR. The curvature track makes the image focusing challenging and, in the classical frequency domain, fast imaging algorithms that are designed for linear rail SAR cannot be readily applied. This paper proposed an efficient frequency domain imaging algorithm for ArcSAR. The proposed algorithm takes advantage of the angular shift-invariant property of the ArcSAR signal, and it deduces the accurate matched filter in the angular-frequency domain, so panoramic images in polar coordinates with wide swath can be obtained at one time without segmenting strategy. When compared with existing ArcSAR frequency domain algorithms, the proposed algorithm is more accurate and efficient, because it has neither far range nor narrow beam antenna restrictions. The proposed method is validated by both simulation and real data. The results show that our algorithm brings the quality of image close to the time domain back-projection (BP) algorithm at a processing efficiency about two orders of magnitude better, and it has better image quality than the existing frequency domain Lee’s algorithm at a comparable processing speed.

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