Improved Channel Error Calibration Algorithm for Azimuth Multichannel SAR Systems

• Published in: IEEE geoscience and remote sensing letters Vol. 13; no. 7; pp. 1022 - 1026
• Main Authors: Guo, Xiaojiang, Gao, Yesheng, Wang, Kaizhi, Liu, Xingzhao
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Azimuth; Calibration; Channel error calibration; Channels; computational load; Covariance matrices; Covariance matrix; Doppler; Doppler effect; Errors; Estimating techniques; Estimation; high accuracy; high-resolution wide-swath (HRWS); multichannel synthetic aperture radar (SAR); Receivers; Synthetic aperture radar; high accuracy; Channel error calibration; multichannel synthetic aperture radar (SAR); computational load; high-resolution wide-swath (HRWS)
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2016.2561961

Multichannel synthetic aperture radar systems in azimuth can effectively suppress azimuth ambiguity and are promising in high-resolution wide-swath imaging. However, unavoidable channel errors will significantly degrade the performance of ambiguity suppression. Conventional subspace calibration methods usually estimate phase error via decomposing a Doppler-variant covariance matrix from one Doppler bin, and then average these errors estimated from several Doppler bins to improve the estimation accuracy, which will result in a large computational load. This letter presents an improved channel error calibration method, which works on the undersampled data of the individual azimuth channel. By a proposed matrix transformation method, the Doppler-variant covariance matrices will be transformed into a constant covariance matrix. Therefore, the improved calibration algorithm needs to estimate and decompose the new covariance matrix only once. The computation load could be greatly reduced. Moreover, the new covariance matrix can be estimated by training samples not only from range bins but also from Doppler bins, which will improve the estimation accuracy. Theoretical analysis and experiments based on simulations and measurements showed the high accuracy, efficiency, and robustness of the improved method, particularly in low signal-to-noise ratio.