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Journal of Applied Remote Sensing • Open Access

Fast image-formation algorithm for ultrahigh-resolution airborne squint spotlight synthetic aperture radar based on adaptive sliding receive-window technique

Paper Abstract

Adaptive sliding receive-window (ASRW) technique was usually introduced in airborne squint synthetic aperture radar (SAR) systems. Airborne squint spotlight SAR varies its receive-window starting time pulse-by-pulse as a function of range-walk, namely, the linear term of range cell migration (RCM). As a result, a huge data volume of the highly squint spotlight SAR echo signal can be significantly reduced. Because the ASRW technique changes the echo-receive starting time and Doppler history, the conventional image algorithm cannot be employed to directly focus airborne squint spotlight ASRW-SAR data. Therefore, a fast image-formation algorithm, based on the principle of the wave number domain algorithm (WDA) and azimuth deramping processing, was proposed for accurately and efficiently focusing the squint spotlight ASRW-SAR data. Azimuth deramping preprocessing was implemented for eliminating azimuth spectrum aliasing. Moreover, bulk compression and modified Stolt mapping were utilized for high-precision focusing. Additionally, geometric correction was employed for compensating the image distortion resulting from the ASRW technique. The proposed algorithm was verified by evaluating the image performance of point targets in different squint angles. In addition, a detailed analysis of computation loads in the appendix indicates that the processing efficiency can be greatly improved, e.g., the processing efficiency could be improved by 17 times in the 70-deg squint angle by applying the proposed image algorithm to the squint spotlight ASRW-SAR data.

Paper Details

Date Published: 4 June 2014
PDF: 13 pages
J. Appl. Remote Sens. 8(1) 083620 doi: 10.1117/1.JRS.8.083620
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Wei Yang, BeiHang Univ. (China)
Hong-cheng Zeng, BeiHang Univ. (China)
Jie Chen, BeiHang Univ. (China)
Peng-bo Wang, BeiHang Univ. (China)

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