Fast Adaptive Cross-Sampling Scheme for the Sparsified Adaptive Cross Approximation

被引：15

作者：

Chen, Xinlei ^{[1
]}

Gu, Changqing ^{[1
]}

Niu, Zhenyi ^{[1
]}

Li, Zhuo ^{[1
,2
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Elect & Informat Engn, Minist Educ, Key Lab Radar Imaging & Microwave Photon, Nanjing 210016, Jiangsu, Peoples R China

[2] Southeast Univ, State Key Lab Millimeter Waves, Nanjing 210096, Jiangsu, Peoples R China

来源：

IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS | 2014年 / 13卷

关键词：

Fast adaptive cross sampling (FACS); method of moments (MoM); sparsified adaptive cross approximation (SPACA); ELECTROMAGNETIC SCATTERING; MATRIX DECOMPOSITION; MOMENTS COMPUTATIONS; ACCELERATED METHOD; ALGORITHM;

D O I：

10.1109/LAWP.2014.2328354

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A fast adaptive cross-sampling (FACS) scheme for the sparsified adaptive cross approximation (SPACA) algorithm is proposed to improve the conventional uniform spatial sampling. The FACS adaptively samples each well-separated block pair in an iterative manner to reach a given sampling error. At each iteration, the FACS first selects a set of initial samples with uniform spatial distribution for each block, and then uses the adaptive cross approximation (ACA) to find the important samples from the initial samples. Compared to the uniform spatial sampling, the FACS is easier to control the sampling error and needs fewer samples for the same sampling error. By reducing the number of samples, the FACS can enhance the efficiency of the SPACA. Numerical results are shown to demonstrate the merits of the proposed scheme.

引用

页码：1061 / 1064

页数：4

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