A GPU implementation of the inverse fast multipole method for multi-bistatic imaging applications

Author

Tirado, Luis E. ; Ghazi, Galia ; Martinez-Lorenzo, Jose Angel ; Rappaport, Carey M. ; Alvarez, Yuri ; Las-Heras, Fernando

Author_Institution

Dept. of Electr. Eng., Northeastern Univ., Boston, MA, USA

fYear

2014

fDate

6-11 July 2014

Firstpage

874

Lastpage

875

Abstract

This paper presents a parallel implementation of the Inverse Fast Multipole Method (IFMM) for multi-bistatic imaging configurations. NVIDIA´s Compute Unified Device Architecture (CUDA) is used to parallelize and accelerate the imaging algorithm in a Graphics Processing Unit (GPU). The algorithm is validated with experimental data, collected by a Frequency-Modulated Continuous Wave (FMCW) radar system operating in the 70-77 GHz frequency band. The proposed GPU-based IFMM algorithm accelerated the single-core CPU version by a factor of 46.

Keywords

CW radar; FM radar; graphics processing units; parallel architectures; radar imaging; CUDA; FMCW radar system; GPU-based IFMM algorithm; NVIDIA compute unified device architecture; frequency 70 GHz to 77 GHz; frequency-modulated continuous wave radar system; graphics processing unit; inverse fast multipole method; multibistatic imaging configurations; the single-core CPU version; Algorithm design and analysis; Computer architecture; Graphics processing units; Image reconstruction; Imaging; Radar imaging; Receivers;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation Society International Symposium (APSURSI), 2014 IEEE

Conference_Location

Memphis, TN

ISSN

1522-3965

Print_ISBN

978-1-4799-3538-3

Type

conf

DOI

10.1109/APS.2014.6904765

Filename

6904765