An approach to estimate tree height using PolInSAR data constructed by the Sentinel-1 dual-pol SAR data and RVoG model

We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.

High Sensitivity Acquisition Algorithm for DSSS Signal with Data Modulation

In direct sequence spread spectrum communication both for satelliteto-ground and inter-satellite links, the system constrains due to radio frequency spectral occupation, channel data throughput and link performances in terms of data channel coding which might result in a signal structure where the symbol duration is shorter than the pseudo code period. This can generate some difficulties in the DSSS signal acquisition due to the polarity inversion caused by the data modulation. To eliminate the influence due to polarity inversion, this paper proposes a novel acquisition algorithm based on the simultaneous search of the code phase, data phase and Doppler frequency. In the proposed algorithm the data phase is predicted and the correlation period for the coherent integration can be set equal to the symbol duration. Then non-coherent accumulation over different symbol is implemented in order to enhance the acquisition algorithm sensitivity; the interval of non-coherent accumulation is the least common multiple between the symbol duration and the pseudo code period. The algorithm proposed can largely minimize the SNR loss caused by data polarity inversion and enhance acquisition performance without a noticeable increase in hardware complexity. Theoretical analysis, simulation and measured results verify the validity of the algorithm.

Polarization readout analysis for multilevel phase change recording by crystallization degree modulation

Four different states of Si15Sb85 and Ge2Sb2Te5 phase change memory thin films are obtained by crystallization degree modulation through laser initialization at different powers or annealing at different temperatures. The polarization characteristics of these two four-level phase change recording media are analyzed systematically. A simple and effective readout scheme is then proposed, and the readout signal is numerically simulated. The results show that a high-contrast polarization readout can be obtained in an extensive wavelength range for the four-level phase change recording media using common phase change materials. This study will help in-depth understanding of the physical mechanisms and provide technical approaches to multilevel phase change recording.

3-D visualizations of coastal bathymetry by utilization of airborne TOPSAR polarized data

Multi-frequency C and L bands in the TOPSAR data have been utilized to reconstruct three-dimensional(3-D)bathymetry pattern.The main objective of this study is to utilize fuzzy arithmetic to reduce the errors arising from speckle in synthetic aperture radar(SAR)data when constructing ocean bathymetry from polarized SAR data.In doing so,two 3-D surface models,the Volterra algorithm and a fuzzy B-spline(FBS)algorithm,which construct a global topological structure between the data points,were used to support an approximation to the real surface.Volterra algorithm was used to express the non-linearity of TOPSAR data intensity gradient based on the action balance equation(ABC).In this context,a first-order kernel of Volterra algorithm was used to express ABC equation.The inverse of Volterra algorithm then performed to simulate 2-D current velocities from CVV and LHH band.Furthermore,the 2-D continuity equation then used to estimate the water depth.In order to reconstruct 3-D bathymetry pattern,the FBS has been performed to water depth information which was estimated from 2-D continuity equation.The best reconstruction of coastal bathymetry of the test site in Kuala Terengganu,Malaysia,was obtained with polarized L and C bands SAR acquired with HH and VV polarizations,respectively.With 10 m spatial resolution of TOPSAR data,bias of
0.004 m,the standard error mean of 0.023 m,r2 value of 0.95,and 90%confidence intervals in depth determination was obtained with LHH band.