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Research On Distributed Imaging Technologies Based On Direct Broadcast Satellite Signal

Posted on:2016-12-29Degree:MasterType:Thesis
Country:ChinaCandidate:X F YuFull Text:PDF
GTID:2308330470957762Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
Passive radar uses non-cooperative illuminator of opportunity as a transmitter to detect targets. Compared with active radar, passive radar is virtually undetectable because of its peculiarity of having no transmitter and its battlefield viability is greatly increased. Thus passive radar has become a field which attracts more and more attention. This paper uses direct broadcast satellite as the illuminator of passive radar and does some research on technologies of distributed imaging based on direct broadcast satellite signal. The main work of this paper is as follows:Firstly, carry out research on algorithms of distributed radar imaging based on sparse Bayesian learning method. This research establishes the model of distributed radar imaging based on direct broadcast satellite signal, gives the limiting resolution using the spatial spectrum theory, proposes two methods of distributed radar imaging based on sparse Bayesian method under the condition of sparse priori, which follows a p-norm distribution:sparse Bayesian learning method based on p-norm distribution and matching pursuit method based on p-norm distribution and makes simulations and analysis of proposed methods.Secondly, design and establish a passive radar experimental system using the satellite China Sat-9as the illuminator and conduct experiments in which metal object and typical buildings were measured. Speed up the method of ECA, which is used to suppress the interference of direct wave in surveillance channel.Finally, conduct indoor distributed imaging experiments based on simulative direct broadcast satellite signal. Use step-frequency signal and simulative direct broadcast satellite signal (QPSK signal) for the sake of contrastive analysis and analyze the experiment results using the spatial spectrum theory. Prove that the support domain of spatial spectrum determines the limiting resolution and spatial spectrum’s filling degree determines the actual resolution under the same support domain.
Keywords/Search Tags:Passive radar, signal of broadcast satellite, distributed radar imaging, sparse Bayesian, target detection, ECA algorithm, imaging experiment
PDF Full Text Request
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