Title :
Research on thinned antenna array of spaceborne SAR
Author :
Xu, Hui ; Li, Jian-Xin
Author_Institution :
CETC, Nanjing
Abstract :
This paper presents a novel mixed genetic algorithm - active mutating anneal genetic algorithm (AMAGA) based on sorting and describes the part elements density weighting thinning method for the spaceborne synthetic aperture radar (SAR) antenna. This method can not only reduce the antenna load weight and cost with the same beam width, but also can control the sparse rate. Moreover, the maximum relative sidelobe is also improved best. In comparison with the full elements density weighting method, the former is more realizable and flexible. Simulations in this paper can show lower sidelobes than the uniform arrays.
Keywords :
antenna arrays; genetic algorithms; radar antennas; spaceborne radar; synthetic aperture radar; active mutating anneal genetic algorithm; density weighting thinning method; mixed genetic algorithm; spaceborne SAR antenna; synthetic aperture radar; thinned antenna array; Annealing; Antenna arrays; Aperture antennas; Costs; Genetic algorithms; Loaded antennas; Radar antennas; Sorting; Spaceborne radar; Synthetic aperture radar; Mixed genetic algorithm; Part elements density weighted array; SAR; Sparse rate;
Conference_Titel :
Synthetic Aperture Radar, 2007. APSAR 2007. 1st Asian and Pacific Conference on
Conference_Location :
Huangshan
Print_ISBN :
978-1-4244-1188-7
Electronic_ISBN :
978-1-4244-1188-7
DOI :
10.1109/APSAR.2007.4418582