Abstract
To obtain a high-resolution and wide-swath image, the azimuth multichannel technique has been widely used in synthetic aperture radar (SAR) systems to overcome the contradiction between the wide swath and high pulse repetition frequency. For a high image quality, channel mismatch correction is an essential step in the multichannel SAR data imaging. However, in the case of airborne multichannel SAR, motion errors will severely degrade the performance of channel mismatch correction. To deal with this problem, this article proposes an improved airborne multichannel SAR imaging method with motion compensation, and range-variant channel mismatch correction. First, motion errors are compensated based on resampling and phase compensation. Then, the time-delay and constant gain-phase errors between channels are estimated and corrected, followed by the range-variant phase error correction based on a novel range-down-sampling method, which reduces the influence of motion errors on the channel mismatch correction significantly. Finally, simulated and real data processing results are used to demonstrate the effectiveness of the proposed method.
Highlights
H IGH-RESOLUTION and wide-swath (HRWS) synthetic aperture radar (SAR) image formation has a wide range of applications in both military and civilian fields [1]
The errors analyzed in this article include motion errors, time-delay error, constant gain-phase error, and range-variant phase error
Only constant phase error and motion errors are added to simulated data
Summary
H IGH-RESOLUTION and wide-swath (HRWS) SAR image formation has a wide range of applications in both military and civilian fields [1]. An improved two-step MOCO method for multichannel SAR is proposed in [14], which corrects the LOS displacement error of different channels, respectively On this basis, the along-track position error is eliminated by resampling received data, which is adopted in this article. By adopting the multiple signal classification (MUSIC) technique, several advanced methods are developed [21]–[24], through extracting the signal subspace and noise subspace from the covariance matrix of the Doppler spectrum, and the orthogonality between subspaces is used to estimate the phase error This method does not need to estimate the Doppler centroid frequency but requires that the Doppler ambiguity number is smaller than the number of receiving channels.
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