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Adaptive Channel Balancing Algorithm Based on 2-D Gaussian Kernel Function
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DOI：10.1109/LGRS.2021.3063103.png)
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Abstract
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The inherent magnitude and phase errors between channels in the multichannel synthetic aperture radar/ground moving target indication (SAR/GMTI) system will affect the clutter suppression and moving target detection performance of the system. To solve this problem, this letter proposes an adaptive channel balancing algorithm based on the 2-D Gaussian kernel function. First, the iterative reweighted least squares (IRLS) algorithm is used to estimate and compensate the inherent linear phase error that varies with the Doppler frequency in the range-Doppler domain. Then the Gaussian statistical analysis of the residual phase errors is performed in the image domain after the azimuth processing. According to the coupling characteristics of the range and azimuth of the SAR image, the correlation coefficient and the standard deviations of the phase errors in the range and azimuth directions are computed, and a 2-D Gaussian kernel function is constructed to estimate and compensate the residual phase errors. Finally, a mean filter is used to compensate the 2-D magnitude errors. This algorithm can eliminate the magnitude and phase errors and improve the coherence between different channels. The real airborne SAR data demonstrate the effectiveness of the proposed algorithm.
Keywords:
Synthetic aperture radar
Azimuth
Clutter
Kernel
Doppler effect
Coherence
Correlation
Channel imbalances
clutter suppression
coherence of images
synthetic aperture radar (SAR)
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