DocumentCode
749279
Title
Antenna Mask Design for SAR Performance Optimization
Author
Kim, Se Young ; Myung, Noh Hoon ; Kang, Min Jeong
Author_Institution
Sch. of Electr. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Daejeon
Volume
6
Issue
3
fYear
2009
fDate
7/1/2009 12:00:00 AM
Firstpage
443
Lastpage
447
Abstract
In this letter, an effective technique for synthetic aperture radar (SAR) antenna mask design is presented for optimizing the system performance of an active phased array SAR. The SAR antenna radiation pattern has an important effect on the system performance. Therefore, the authors derived the quantitative equations for the SAR antenna mainlobe and sidelobe mask design on the basis of the system performance measures such as the range-to-ambiguity ratio (RAR), the noise-equivalent sigma zero (NESZ), and the radiometric accuracy. The antenna mask template should be designed to minimize the ambiguous signals reflected from the antenna sidelobes and maximize the system sensitivity, i.e., the NESZ, determined by the antenna mainlobe. The simple iterative method such as random-mutation hill climbing was utilized to successfully assign the sidelobe level at each ambiguous area using the derived equations. Finally, the antenna patterns were synthesized with reference to the optimized antenna mask templates using the particle swarm optimization, and the swath width, RAR, and NESZ performances were evaluated in order to confirm the effectiveness of the proposed technique.
Keywords
antenna radiation patterns; iterative methods; particle swarm optimisation; phased array radar; radar antennas; radiometry; synthetic aperture radar; SAR antenna mainlobe; SAR antenna radiation pattern; active phased array SAR performance optimization; antenna mask design; iterative method; noise-equivalent sigma zero; particle swarm optimization; radiometry; sidelobe mask design; synthetic aperture radar; Active phased array synthetic aperture radar; antenna mask; noise-equivalent sigma zero (NESZ); particle swarm optimization (PSO); range-to-ambiguity ratio (RAR);
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2009.2016356
Filename
4838926
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