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Study and Simulation on Parameters Joint Estimation Algorithms of Near-field Source

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Tutor: WangXiangHong
School: Harbin Engineering University
Course: Underwater Acoustics
Keywords: higher order statistics,near field,joint estimation,SVD denoise
CLC: TN911.7
Type: Master's thesis
Year:  2011
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Abstract:
Parameter estimation is an important aspect in array signal processing research, and it is applied in the field of radar, sonar, seismic exploration, communication, positioning and so on. Traditional DOA estimation algorithm is based on the assumption that source is in the far field condition relative to the array aperture, namely array receives the plane wave. Under this assumption, the main parameter is the signals arriving direction (one dimension or two dimensions) of the source, and the time delay of different array elements changes in linear way, which is convenient for the analysis of the problems. But when source located in (Fresnel) area relative to the array aperture, the far field assumption can not be used as array receives spherical waves. The time delay of different array elements changes in nonlinear way, so the corresponding algorithms will fail and the study for the near field source will be more complicated. Under near field assumptions, the main parameters of source to be estimated is the frequency, signal arriving direction and distance. So it is necessary to study the problem of multidimensional parameters estimation under near field conditions.This paper discusses the superior performance of higher order statistics in signal processing field firstly. As higher order statistics has properties of blind characteristics to additive white Gaussian noise, it is applied in the parameter estimation field widely. Secondly through modeling, the property and performance of near field source DOA and distance joint estimation algorithm are analyzed under frequency known conditions. Then under frequency unknown conditions, the basic principles and performance of near field source frequency, DOA and distance joint estimation algorithm is considered. Parameter estimation algorithm of Based on symmetrical arrays was improve, and improve the utilization ratio of the array, reduce the number of fourth-order cumulants matrix and computational cost. Finally, according to the theory of SVD denoise, improve gaussian noise suppression effect of fourth-order cumulant in low SNR, small data number case, and improve the performance of the algorithm.
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