New autofocus technique for wideband wide-angle synthetic aperture radar

1998 ◽  
Author(s):  
David Kirk ◽  
Paul Maloney
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Wide Angle ◽  
Aperture Radar

scholarly journals Adaptive Sub-Aperture Integration for Wide-Angle Synthetic Aperture Radar

2021 ◽  
pp. 1-1
Author(s):  
Shahzad Gishkori ◽  
David Wright ◽  
Liam Daniel ◽  
Mohammed Aasim Shaikh ◽  
Tareq Al-Naffouri ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Wide Angle ◽  
Aperture Radar

scholarly journals A Vehicle Target Recognition Algorithm for Wide-Angle SAR Based on Joint Feature Set Matching

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1252 ◽  
Author(s):  
Rongchun Hu ◽  
Zhenming Peng ◽  
Juan Ma
Keyword(s):  
Synthetic Aperture Radar ◽  
Recognition Accuracy ◽  
Target Recognition ◽  
Recognition Algorithm ◽  
Synthetic Aperture ◽  
Speckle Reduction ◽  
Wide Angle ◽  
Target Imaging ◽  
Standard Orientation ◽  
Aperture Radar

Target recognition is an important area in Synthetic Aperture Radar (SAR) research. Wide-angle Synthetic Aperture Radar (WSAR) has obvious advantages in target imaging resolution. This paper presents a vehicle target recognition algorithm for wide-angle SAR, which is based on joint feature set matching (JFSM). In this algorithm, firstly, the modulus stretch step is added in the imaging process of wide-angle SAR to obtain the thinned image of vehicle contour. Secondly, the gravitational-based speckle reduction algorithm is used to obtain a clearer contour image. Thirdly, the image is rotated to obtain a standard orientation image. Subsequently, the image and projection feature sets are extracted. Finally, the JFSM algorithm, which combines the image and projection sets, is used to identify the vehicle model. Experiments show that the recognition accuracy of the proposed algorithm is up to 85%. The proposed algorithm is demonstrated on the Gotcha WSAR dataset.

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