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	1. Target Parameters Estimation of Frequency Diverse Array based on Preprocessing l1-SVD Algorithm
	Liao Yanping,Pan Yue
	Electrics, Communication and Autocontrol Technology 04 March 2020
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (377K B)

	Abstract:Due to too much data, the efficiency of l1 norm-Singular Value Decomposition (l1-SVD) algorithm becomes poor, this paper proposes a Preprocessing l1-SVD algorithm. This method is based on the frequency diversity array of L-type array. Firstly, the search space of the target position is preprocessed to reduce the search space by the inner product of the received data and the perception matrix. Then, l1-SVD algorithm is used to estimate the search space after proposed preprocessing. The simulation results show that the algorithm has better efficiency in the face of large amount of data, and the estimation accuracy is also improved compared with that without processing.
	TO cite this article:Liao Yanping,Pan Yue. Target Parameters Estimation of Frequency Diverse Array based on Preprocessing l1-SVD Algorithm[OL].[ 4 March 2020] http://en.paper.edu.cn/en_releasepaper/content/4751024


	2. Near-Field Source Localization in Unknown Nonuniform Noise
	ZUO Weiliang,XIN Jingmin
	Electrics, Communication and Autocontrol Technology 29 June 2017
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (4K B)

	Abstract:In this paper, we consider the source localizationfor the multiple near-field narrowband signals impinging on a symmetricuniform linear array (ULA) in nonuniform noise. We introduce the matrix completion (MC) approach to reconstruct the noise-freecovariance matrix for estimating the signal subspace. Then, some existingsource localization methods can be applied immediately. Finally, the effectivenessof the proposed method is verified through numerical examples.
	TO cite this article:ZUO Weiliang,XIN Jingmin. Near-Field Source Localization in Unknown Nonuniform Noise[OL].[29 June 2017] http://en.paper.edu.cn/en_releasepaper/content/4738005


	3. Efficient Method for Localization of Mixed Far-Field and Near-Field Signals
	ZUO Weiliang,XIN Jingmin
	Electrics, Communication and Autocontrol Technology 29 June 2017
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (4K B)

	Abstract:In this paper, we deal with the problem of localizing mixed far-field (FF)and near-field (NF) sources impinging on a uniform linear arraywith the symmetrical geometric configuration.An efficient method for localization of the mixed FF and NF sources is proposed,where the direction-of-arrivals (DOAs) of the mixed sources are estimated separately by using the oblique projection,and then the ranges of the NF sources are obtained through a polynomial rooting,while the computationally burdensome eigendecomposition and pair-matching are avoided.The effectiveness of the proposed method is verified through numerical examples,and the simulation results show that the proposed method has better estimation performancethan some existing methods.
	TO cite this article:ZUO Weiliang,XIN Jingmin. Efficient Method for Localization of Mixed Far-Field and Near-Field Signals[OL].[29 June 2017] http://en.paper.edu.cn/en_releasepaper/content/4738008


	4. Algebraic Connectivity Estimation Based On Decentralized Inverse Power Iteration
	Yue Wei, Hao Fang, Jie Chen, Bin Xin
	Electrics, Communication and Autocontrol Technology 29 December 2015
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (4K B)

	Abstract:In this work we propose a new scheme to estimate the algebraic connectivity of the Laplacian matrix associated with the graph describing the network topology of a multi-agent system. We consider network topologies modelled by undirected graphs. The main idea is to propose a new decentralized conjugate gradient algorithm and a decentralized compound inverse power iteration scheme is built, in which the matrix inversion computation is replaced by solving the non-homogeneous linear equations relying on the proposed decentralized conjugate gradient algorithm. With this scheme, we can achieve a fast convergence rate in algebraic connectivity estimation by setting the parameter $mu$ properly. Simulation results demonstrate the effectiveness of the proposed scheme.
	TO cite this article:Yue Wei, Hao Fang, Jie Chen, et al. Algebraic Connectivity Estimation Based On Decentralized Inverse Power Iteration[OL].[29 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4673942


	5. A Novel Joint Block Diagonalization Algorithm for Convolutive BSS with Limited Constraint
	ZHANG Wei-Tao
	Electrics, Communication and Autocontrol Technology 08 December 2015
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (4K B)

	Abstract:In this paper, the convolutive blind source separation (CBSS) via joint block diagonalization (JBD) technique is revisited to reduce the rigorous constraint. As is known that the CBSS signal

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