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System parameter optimisation for moving target detection and imaging in multi‐band synthetic aperture radar based on genetic algorithm
Author(s) -
Wang Jinwei,
Zhou Feng,
Tao Mingliang,
Zhang Zijing,
Sun Guangcai
Publication year - 2016
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2015.0080
Subject(s) - synthetic aperture radar , genetic algorithm , computer science , inverse synthetic aperture radar , radar , radar imaging , algorithm , artificial intelligence , computer vision , remote sensing , geology , telecommunications , machine learning
To overcome the shortcomings of the conventional moving target detection method in single‐channel synthetic aperture radar (SAR), this study proposes a novel method for moving target detection in single‐channel multi‐band SAR. In this method, according to the detectable velocity in different bands, the genetic algorithm is applied to optimise the choice of radar band parameters, for example, wavelength and pulse repetition frequency. With the obtained optimal parameter combinations, the multi‐band SAR system could achieve the highest velocity detection rate and the maximal bands utilisation rate. Then, moving target detection, imaging and location could be accomplished with the radon transform and the deramp method. Finally, simulation results are presented to demonstrate the effectiveness and feasibility of the proposed method.

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