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A cumulant-based parameter estimation algorithm for near-field sources
作者姓名:Liang Junli  Yang Shuyuan and Zhang Junying
作者单位:Liang Junli~(1,2*) Yang Shuyuan~(1,2) Zhang Junying~3 (1.Institute of Acoustics,Chinese Academy of Sciences,Beijing 100080,China;2.Graduate School,Chinese Academy of Sciences,Beijing 100039,China;3.National Laboratory of Radar Signal Processing,Xidian University,Xi'an 710071,China)
摘    要:To efficiently use the array aperture and avoid the complicated parameter pairing computation,this paper proposes a new cumulant-based algorithm for localizing near-field narrowband sources.Firstly,this algorithm proposes a symmetric uniform linear ar- ray (ULA),and constructs three cumulant matrices by using the fourth-order cumulants of some properly chosen sensor outputs;second- ly,unlike the conventional parallel factor (PARAFAC) analysis models in data or subspace domain,it forms a three-way array (TWA) in the fourth-order cumulant domain using the three matrices,and analyzes the uniqueness of its low-rank decomposition;thirdly,it jointly estimates the frequency,the direction-of-arrival (DOA),and the range of each near-field source from the matrices via the low-rank de- composition of the TWA.The simulation results are presented to validate the performance of our proposed method.


A cumulant-based parameter estimation algorithm for near-field sources
Liang Junli,Yang Shuyuan,Zhang Junying.A cumulant-based parameter estimation algorithm for near-field sources[J].Progress in Natural Science,2007,17(8):900-905.
Authors:Liang Junli  Yang Shuyuan  Zhang Junying
Abstract:To efficiently use the array aperture and avoid the complicated parameter pairing computation,this paper proposes a new cumulant-based algorithm for localizing near-field narrowband sources.Firstly,this algorithm proposes a symmetric uniform linear ar- ray (ULA),and constructs three cumulant matrices by using the fourth-order cumulants of some properly chosen sensor outputs;second- ly,unlike the conventional parallel factor (PARAFAC) analysis models in data or subspace domain,it forms a three-way array (TWA) in the fourth-order cumulant domain using the three matrices,and analyzes the uniqueness of its low-rank decomposition;thirdly,it jointly estimates the frequency,the direction-of-arrival (DOA),and the range of each near-field source from the matrices via the low-rank de- composition of the TWA.The simulation results are presented to validate the performance of our proposed method.
Keywords:array signal processing  localization  cumulant  parallel factor (PARAFAC) analysis  three-way array (TWA)
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