volume | PIER Journals

Abstract

This paper proposes a hybrid method to accelerate the calculation of the monostatic radar cross section (RCS) of perfect electric conducting (PEC) targets. In a sense, the proposed method can be considered as a fast adaptive cross approximation (FACA)-based method. The FACA is firstly used to compress the excitation matrix which come from the beforehand defined incident plane waves. It decreases the time and memory on the generation of decomposition form matrices throughout the comparison with the conventional adaptive cross approximation (ACA). Furthermore, the computational complexity of solution is further reduced by using the sparsified ACA (SPACA) algorithm after dividing the target into blocks. Consequently, the proposed method turns out to be efficient and accurate for calculating two-dimensional (2D) monostatic RCS.

1. Zhao, K., M. N. Vouvalis, and J. Lee, "The adaptive cross approximation algorithm for accelerated method of moments computations of EMC problems," IEEE Trans. Electromagnetic Compatibility, Vol. 13, No. 4, 763-772, Nov. 2005. Google Scholar

2. Heldring, A., J. M. Rius, J. M. Tanayo, J. Parron, and E. Ubeda, "Multiscale compressed block decomposition for fast direct solution of method of moments linear system," IEEE Trans. Antennas and Propag., Vol. 59, No. 2, 526-536, Feb. 2011.
doi:10.1109/TAP.2010.2096385 Google Scholar

3. Tanayo, J. M., A. Heldring, and J. M. Rius, "Multilevel adaptive cross approximation (MLACA)," IEEE Trans. Antennas and Propag., Vol. 59, No. 12, 4600-4608, Dec. 2011.
doi:10.1109/TAP.2011.2165476 Google Scholar

4. Heldring, A., J. M. Tanayo, C. Simon, E. Ubeda, and J. M. Rius, "Sparsified adaptive cross approximation algorithm for accelerated method of moments computations," IEEE Trans. Antennas and Propag., Vol. 61, No. 1, 526-536, Jan. 2013.
doi:10.1109/TAP.2012.2215292 Google Scholar

5. Chen, X., C. Gu, Z. Niu, and Z. Li, "Fast adaptive cross-sampling scheme for the sparsified adaptive cross approximation," IEEE Antennas and Wireless Propagation Letters, Vol. 13, 1061-1064, 2014.
doi:10.1109/LAWP.2014.2328354 Google Scholar

6. Chen, X., C. Gu, Z. Li, and Z. Niu, "Sparsified multilevel adaptive cross approximation," IEEE Asia-Pacific Conference on Antennas and Propagation, 971-973, 2014. Google Scholar

7. Chen, X., C. Gu, J. Ding, Z. Li, and Z. Niu, "Multilevel fast adaptive cross-approximation algorithm with characteristic basis functions," IEEE Trans. Antennas and Propag., Vol. 63, No. 9, 3994-4002, Sep. 2015.
doi:10.1109/TAP.2015.2447033 Google Scholar

8. Schroder, A., H. D. Bruns, and C. Schuster, "A hybrid approach for rapid computation of two-dimensional monostatic radar cross section problems with the multilevel algorithm," IEEE Trans. Antennas and Propag., Vol. 60, No. 12, Dec. 2012.
doi:10.1109/TAP.2012.2209858 Google Scholar

9. Rao, S. M., D. R. Wilton, and A. W. Glisson, "Electromagnetic scattering by surfaces of arbitrary shape," IEEE Trans. Antennas and Propag., Vol. 30, No. 2, 409-418, May 1982.
doi:10.1109/TAP.1982.1142818 Google Scholar

10. Michielssen, E. and A. Boag, "A multilevel matrix decomposition algorithm for analyzing scattering from large structures," IEEE Trans. Antennas and Propag., Vol. 44, No. 8, 1086-1093, Aug. 1996.
doi:10.1109/8.511816 Google Scholar

Dr. Chao Fei

Prof. Xinlei Chen

Dr. Yang Zhang

Prof. Zhuo Li

Prof. Chang Qing Gu