An Improved Adaptive Regularization Method for Forward Looking Azimuth Super-Resolution of a Dual-Frequency Polarized Scatterometer

Abstract

Dual-frequency polarized scatterometer (DFPSCAT) is a pencil-beam rotating scatterometer which is designed for snow water equivalent (SWE) measurement, and Doppler beam sharpening (DBS) technique is proposed for DFPSCAT to achieve the azimuth resolution. However, the DBS technique is inapplicable for the forward-looking and afterward-looking regions. Based on an approximate aperiodic model of scatterometer echo signal, an improved adaptive regularization deconvolution algorithm with gradient histogram preservation (GHP) constraint is implemented to settle the problem. To investigate its performance of resolution enhancement and resulted accuracy, both a synthetic backscattering coefficient ( $\sigma^{0}$ ) field reconstruction and SWE $\sigma^{0}$ reconstruction are carried out. The results show that the proposed method can recover the truth signal and achieve azimuth resolution of 2 km with the designed scatterometer system, which is required by the SWE retrieval. Moreover, the relative errors of reconstructed $\sigma^{0}$ are less than 0.5 dB that satisfy the accuracy requirement for SWE retrieval, and comparisons with observed results show that the error reduction is more than 0.03 dB. Meanwhile, a comparison between the proposed algorithm and some existing resolution enhancement methods is analyzed, which concludes that the proposed method can obtain a comparable resolution enhancement as $L_{1}$ method and has less noise. The technique is also verified with advanced scatterometer (ASCAT) scatterometer data.