Subjects: Geosciences >> Space Physics submitted time 2017-03-10
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 (σ0field reconstruction and SWE σ0reconstruction 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 σ0are 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 L1method and has less noise. The technique is also verified with advanced scatterometer (ASCAT) scatterometer data. © 2016 IEEE.
Peer Review Status:
Awaiting Review
Subjects: Geosciences >> Space Physics submitted time 2017-03-10
Abstract： Dual-Frequency Polarized Scatterometer (DFPSCAT) is a pencil-beam rotating scatterometer which is used to measure snow water equivalence (SWE). Respecting the low azimuth resolution of its forward-looking region, an adaptive regularization deconvolution super-resolution method, based on the scatterometer echo signal model, is proposed. Compared with the classical SIR and MAP algorithms, the proposed method can better reconstruct the original signal, and has less noise amplification. The algorithm processing accuracy with different Kpcis also studied, and the results show that when the value of Kpcis less than 0.1, nearly the entire restored data can satisfy the requirement of 0.5dB accuracy. �2015 IEEE.
Peer Review Status:Awaiting Review
Subjects: Geosciences >> Space Physics submitted time 2017-03-10
Abstract： Dual-Frequency Polarized Scatterometer (DFPSCAT) is a new system utilizing Doppler beam sharpening (DBS) technology for azimuthal resolution enhancement. Considering the DBS technology is inapplicable for the middle areas of the swath, a theoretical framework of deconvolution signal processing is proposed to improve resolution. A deconvolution method of the nonlocally centralized sparse representation (NCSR) is adopted to verify its feasibility, and simulation results show that the deconvolution method have obviously better resolution enhancement and higher recovery accuracy than these of the classical scatterometer image reconstruction (SIR) method. �2016 IEEE.
Peer Review Status:Awaiting Review
Subjects: Geosciences >> Space Physics submitted time 2016-05-03
Abstract： Dual-Frequency Polarized Scatterometer (DFPSCAT) is a pencil-beam rotating scatterometer which is used to measure snow water equivalence (SWE). Respecting the low azimuth resolution of its forward-looking region, an adaptive regularization deconvolution super-resolution method, based on the scatterometer echo signal model, is proposed. Compared with the classical SIR and MAP algorithms, the proposed method can better reconstruct the original signal, and has less noise amplification. The algorithm processing accuracy with different K-pc is also studied, and the results show that when the value of K-pc is less than 0.1, nearly the entire restored data can satisfy the requirement of 0.5dB accuracy.
Peer Review Status:Awaiting Review
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