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The Direction Of Arrival Estimation For Ultra Wideband Signals

Posted on:2012-09-26Degree:MasterType:Thesis
Country:ChinaCandidate:J Q SunFull Text:PDF
GTID:2178330332987496Subject:Electromagnetic field and microwave technology
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Estimation of signal parameters is an important research area of signal processing with growing applications in engineering and intensive research in theory. In recent years, much interest focuses on research and development of parameter estimation based on different application background, such as radar, sonar, communication, biomedicine, etc. This dissertation concentrates on the study of Direction-of-Arrival (DOA)for wideband signals. The Incoherent Signal-subspace Method(ISM)is analyzed, and Modified Music algorithm is used to improve the resolution of ISM and make it work in the presence of coherent wideband signals. Then the Coherent Signal-subspace Method(CSM) is discussed. The performance of DOA estimation affecting by the focusing matrix and focusing frequency has been studied. Rules of selecting the optimal focusing matrix and focusing frequency are investigated.In UWB antenna array, the impact of mutual coupling between array elements, in particular, for ultra-wideband low frequency band, is very serious. If you want to use the ISM method or CSM method to go on DOA estimation, the mutual coupling matrix should carefully be built; because the very wide bandwidth of UWB, the establishment of exact mutual compensation matrix will be a very difficult task., even can't be accomplished. In view of this, the paper proposes the radial basis function neural network (Radial-basis Function Neural Network, RBFNN) to the introduction of DOA estimation, avoiding the exact building for this matrix. Since ambient temperature and humidity on Measurement disturbances as well is present, the RBFNN. offer a best choice for the practical use. Extensive simulations demonstrate the performance of the proposed methods.
Keywords/Search Tags:Ultra Wideband Signal Processing Direction-of-arrival(DOA), Incoherent Signal-Subspace Method(ISM), Coherent Signal-Subspace Method(CSM), Radial Basis Function Neural Network(RBFNN)
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