Title :
Sparsification of the Impedance Matrix in the Solution of the Integral Equation by Using the Maximally Orthogonalized Basis Functions
Author :
Ren, Yi ; Nie, Zaiping ; Zhao, Yanwen ; Ma, Wenmin
Author_Institution :
Dept. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
fDate :
7/1/2008 12:00:00 AM
Abstract :
The higher order vector basis functions defined in large patches have been utilized in the numerical solution of integral equations in this paper to sparsify the impedance matrix and relieve the memory pressure. The physical explanation for the sparsification of the impedance matrix is also elucidated. Furthermore, the maximally orthogonalized bases have been applied to improve the condition number of the impedance matrix. The scaling factor was reformed to speed up the iteration convergence in the numerical solution. Finally, the iterative method for sparse matrix equations is applied to improve the solution efficiency. Some numerical results are provided to illustrate the excellent performance both in the sparsification of the impedance matrix and solution efficiency for numerical analysis of the scattering problem.
Keywords :
convergence of numerical methods; electromagnetic wave scattering; geophysical signal processing; impedance matrix; integral equations; iterative methods; microwave imaging; remote sensing; higher order vector basis functions; impedance matrix condition number; impedance matrix sparsification; integral equation numerical solution; integral equation solution; maximally orthogonalized basis functions; numerical solution iteration convergence; scaling factor; scattering problem numerical analysis; sparse matrix equation iterative method; Higher order basis functions; matrix sparsification; maximum orthogonalization; scaling factor;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2008.916636