In practice, airborne gravimetry is a sub-Nyquist sampling method because of the restrictions imposed by national boundaries, financial cost, and database size. In this study, we analyze the sparsity of airborne gravi...In practice, airborne gravimetry is a sub-Nyquist sampling method because of the restrictions imposed by national boundaries, financial cost, and database size. In this study, we analyze the sparsity of airborne gravimetry data by using the discrete Fourier transform and propose a reconstruction method based on the theory of compressed sensing for large- scale gravity anomaly data. Consequently, the reconstruction of the gravity anomaly data is transformed to a Ll-norm convex quadratic programming problem. We combine the preconditioned conjugate gradient algorithm （PCG） and the improved interior-point method （IPM） to solve the convex quadratic programming problem. Furthermore, a flight test was carried out with the homegrown strapdown airborne gravimeter SGA-WZ. Subsequently, we reconstructed the gravity anomaly data of the flight test, and then, we compared the proposed method with the linear interpolation method, which is commonly used in airborne gravimetry. The test results show that the PCG-IPM algorithm can be used to reconstruct large-scale gravity anomaly data with higher accuracy and more effectiveness than the linear interpolation method.展开更多
A series of polyester, cotton, and polyester/cotton blend fabrics were evaluated in a subjective wear. Subjective trial data were correlated with the results of in-house laboratory tests with the regression methods. E...A series of polyester, cotton, and polyester/cotton blend fabrics were evaluated in a subjective wear. Subjective trial data were correlated with the results of in-house laboratory tests with the regression methods. Experimental results indicate that clothing-comfort assessment by human perception provides a sound basis for comparison of apparel garments under combined microclimates and human-activity levels of展开更多
基金supported by the National High Technology Research and Development Program of China(No.SS2013AA060402)
文摘In practice, airborne gravimetry is a sub-Nyquist sampling method because of the restrictions imposed by national boundaries, financial cost, and database size. In this study, we analyze the sparsity of airborne gravimetry data by using the discrete Fourier transform and propose a reconstruction method based on the theory of compressed sensing for large- scale gravity anomaly data. Consequently, the reconstruction of the gravity anomaly data is transformed to a Ll-norm convex quadratic programming problem. We combine the preconditioned conjugate gradient algorithm （PCG） and the improved interior-point method （IPM） to solve the convex quadratic programming problem. Furthermore, a flight test was carried out with the homegrown strapdown airborne gravimeter SGA-WZ. Subsequently, we reconstructed the gravity anomaly data of the flight test, and then, we compared the proposed method with the linear interpolation method, which is commonly used in airborne gravimetry. The test results show that the PCG-IPM algorithm can be used to reconstruct large-scale gravity anomaly data with higher accuracy and more effectiveness than the linear interpolation method.
文摘A series of polyester, cotton, and polyester/cotton blend fabrics were evaluated in a subjective wear. Subjective trial data were correlated with the results of in-house laboratory tests with the regression methods. Experimental results indicate that clothing-comfort assessment by human perception provides a sound basis for comparison of apparel garments under combined microclimates and human-activity levels of
