No abstract

Aiming at fast analysis of wide angle electromagnetic scattering problems, compressed sensing theory is introduced and applied, and a new kind of sparse representation of induced currents is constructed based on prior knowledge that originates from excitation vectors in method of moments. Using the new kind of sparse representation in conjugation with compressed sensing, one can recover unknown currents accurately with fewer measurements than some conventional sparse representations in mathematical sense. Hence, times of calculation by traditional method of moments used to obtain the required measurements can be reduced, which will improve the computational efficiency.

Under the theory structure of compressive sensing (CS), an underdetermined equation is deduced for describing the discrete solution of the electromagnetic integral equation of body of revolution (BOR), which will result in a small-scale impedance matrix. In the new linear equation system, the small-scale impedance matrix can be regarded as the measurement matrix in CS, while the excited vector is the measurement of unknown currents. Instead of solving dense full rank matrix equations by the iterative method, with suitable sparse representation, for unknown currents on the surface of BOR, the entire current can be accurately obtained by reconstructed algorithms in CS for small-scale undetermined equations. Numerical results show that the proposed method can greatly improve the computational efficiency and can decrease memory consumed.