Outboard abnormal noise source localization method with curved surface projection based on time delay matching and weighting criterion

An improved localization method consisting of ＂filtering-time delay estimationhyperbolic localization＂ is proposed. Combining the empirical mode decomposition（EMD）and time delay estimation method based on generalized average magnitude difference function,the original signals are decomposed into intrinsic mode function（IMF） components. The energy distribution criterion and spectrum consistency criterion are used to select the IMFs, which can represent the physical characteristics of the source signal. Several sets of signals are applied to estimate the time delay, and then a vector matching criterion is proposed to select the correct time delay estimation. Considering the hydrophones location, a shell model is established and projected to a plane according to the quadrant before the hyperbolic localization. Results of mooring and sailing tests show that the proposed method improves the localization accuracy,and reduces the error caused by time delay estimation.

Research on synthetic aperture radar imaging technology of one-dimensional layered rough surfaces

A quick and exact imaging method for one-dimensional layered rough surfaces is proposed in this paper to study the scattering characteristics of a layered medium that exists widely in nature.The boundary integral equations of layered rough surfaces are solved by using the propagation-inside-layer expansion combined with the forward and backward spectral acceleration method（PILE＋FB-SA）,and the back scattering data are obtained.Then,a conventional synthetic aperture radar（SAR） imaging procedure called back projection method is used to generate a two-dimensional（2D） image of the layered rough surfaces.Combined with the relative dielectric permittivity of realistic soil,the random rough surfaces with Gauss spectrum are used to simulate the layered medium with rough interfaces.Since the back scattering data are computed by using the fast numerical method,this method can be used to study layered rough surfaces with any parameter,which has a great application value in the detection and remote sensing areas.

Future Changes and Uncertainties in Temperature and Precipitation over China Based on CMIP5 Models

Climate changes in future 21 st century China and their uncertainties are evaluated based on 22 climate models from the Coupled Model Intercomparison Project Phase 5（CMIP5）. By 2081–2100, the annual mean surface air temperature（SAT） is predicted to increase by 1.3℃± 0.7℃, 2.6℃± 0.8℃ and 5.2℃± 1.2℃ under the Representative Concentration Pathway（RCP） scenarios RCP2.6, RCP4.5 and RCP8.5, relative to 1986–2005, respectively. The future change in SAT averaged over China increases the most in autumn/winter and the least in spring, while the uncertainty shows little seasonal variation.Spatially, the annual and seasonal mean SAT both show a homogeneous warming pattern across China, with a warming rate increasing from southeastern China to the Tibetan Plateau and northern China, invariant with time and emissions scenario.The associated uncertainty in SAT decreases from northern to southern China. Meanwhile, by 2081–2100, the annual mean precipitation increases by 5% ± 5%, 8% ± 6% and 12% ± 8% under RCP2.6, RCP4.5 and RCP8.5, respectively. The national average precipitation anomaly percentage, largest in spring and smallest in winter, and its uncertainty, largest in winter and smallest in autumn, show visible seasonal variations. Although at a low confidence level, a homogeneous wetting pattern is projected across China on the annual mean scale, with a larger increasing percentage in northern China and a weak drying in southern China in the early 21 st century. The associated uncertainty is also generally larger in northern China and smaller in southwestern China. In addition, both SAT and precipitation usually show larger seasonal variability on the sub-regional scale compared with the national average.

Sheaves on non-reduced curves in a projective surface

Sheaves on non-reduced curves can appear in moduli spaces of 1-dimensional semistable sheaves over a surface and moduli spaces of Higgs bundles as well.We estimate the dimension of the stack M_(X)(nC,χ)of pure sheaves supported at the non-reduced curve nC(n≥2)with C an integral curve on X.We prove that the Hilbert-Chow morphism h_(L,χ):M_(X)^(H)(L,χ)→|L|sending each semistable 1-dimensional sheaf to its support has all its fibers of the same dimension for X Fano or with the trivial canonical line bundle and|L|contains integral curves.