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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
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	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
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	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

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	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
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	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
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	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
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	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 model under the JBD framework is equivalent to an instantaneous mixture model, where the mixing matrix is almost always non-square. This considerably restricts the applicability of existing JBD algorithms in CBSS problem for non-square mixing cases. In this paper the nonunitary JBD problem is reformulated as a multicriteria optimization model, where the mixing matrix can be non-square. Moreover, by optimizing the proposed model the resulting algorithm can eliminate the degenerate solutions in nonunitary JBD. The simulation results show that the proposed algorithm outperforms the existing JBD algorithms in terms of separation accuracy and stability.
	TO cite this article:ZHANG Wei-Tao. A Novel Joint Block Diagonalization Algorithm for Convolutive BSS with Limited Constraint[OL].[ 8 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4670351


	6. Block sparse signal recovery with a Block-Toeplitz structured measurement matrix
	HUANG Bo-Xue,ZHOU Tong
	Electrics, Communication and Autocontrol Technology 24 February 2014
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	Abstract:Recently, many applications about the recovery of block sparse signals have arisen, which can be casted as the recovery of a block sparse signal $x$ from a measurement equation $y=Phi x $. Here, $Phi$ is a known measurement matrix, and assumed to be a block-concatenation of Toeplitz matrices. In this paper, StOMP is extended to the block sparse case, and an algorithm tBlock-StOMP is proposed. Specifically, tBlock-StOMP combines advantages of StOMP with the structural characteristics of $x$ and $Phi$ to pursue high efficiency in block sparse signal recovery. Furthermore, a modification to the tBlock-StOMP is proposed, termed mtBlock-StOMP. Compared with many other recovery algorithms, numerical simulations demonstrate that tBlock-StOMP as well as mtBlock-StOMP results in evident effectiveness in block sparse reconstruction problems.
	TO cite this article:HUANG Bo-Xue,ZHOU Tong. Block sparse signal recovery with a Block-Toeplitz structured measurement matrix[OL].[24 February 2014] http://en.paper.edu.cn/en_releasepaper/content/4586269


	7. Parameter Estimation of Moving Target on Non-uniform Stereo Distributed SAR using FrFT-subspace Method
	LIU Mei,LI Chenlei,GU Guanglin
	Electrics, Communication and Autocontrol Technology 26 September 2013
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	Abstract:The geometry of spaceborne distributed synthetic aperture radar (SAR) is generally non-uniform three-dimensional (3D) stereo, under which the conventional linear array processing algorithms are invalid to estimate motion parameters of ground moving target. To solve this problem, a novel parameter estimation method is presented in this paper. First, a novel signal model is derived for non-uniform stereo distributed SAR, then a method of space-time-frequency distribution (STFD) based on fractional Fourier transform (FrFT) and MUSIC is presented to estimate the azimuth initial location and range velocity, next a method of FrFT-CROCOSMUSIC is presented to estimate the azimuth velocity, finally the performances of the method is studied via computer simulations. Comparing with conventinonal FrFT method, the presented method is more effective.
	TO cite this article:LIU Mei,LI Chenlei,GU Guanglin. Parameter Estimation of Moving Target on Non-uniform Stereo Distributed SAR using FrFT-subspace Method[OL].[26 September 2013] http://en.paper.edu.cn/en_releasepaper/content/4561333


	8. Low Complexity Method for Spreading Sequence Estimation of DSSS signal in Non-Cooperative Communication Systems
	cang liang,wang fuping,Wang Zanji
	Electrics, Communication and Autocontrol Technology 18 December 2008
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	Abstract:It is a necessary step to estimate the spreading sequence of direct sequence spread spectrum (DSSS) signal for blind despreading and demodulation in non-cooperative communications. The article proposes two innovative and effective detection statistics to implement the synchronization and spreading sequence estimation procedure. The proposed algorithm also has a low computational complexity with only linear additions and modifications. Theoretical analysis and simulation results show that the algorithm performs quite well in low SNR environment, and is much better than all the existing typical algorithms with a comprehensive consideration both in performance and computational complexity.
	TO cite this article:cang liang,wang fuping,Wang Zanji. Low Complexity Method for Spreading Sequence Estimation of DSSS signal in Non-Cooperative Communication Systems[OL].[18 December 2008] http://en.paper.edu.cn/en_releasepaper/content/26731


	9. Quad-quaternion MUSIC for DOA Estimation Using Electromagnetic Vector-Sensors
	Xiaofeng Gong,Yougen Xu,Zhiwen Liu
	Electrics, Communication and Autocontrol Technology 03 April 2008
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	Abstract:A new quad-quaternion model is herein established for a six-component electro-magnetic vector-sensor array, under which a multidimensional-algebra based direc-tion-of-arrival (DOA) estimation algorithm, termed as quad-quaternion MUSIC (QQ-MUSIC), is proposed. This method provides DOA estimation (decoupled from polarization) by exploiting the orthogonality of the newly defined ‘quad-quaternion’ signal and noise subspaces. Due to the stronger constraints that quad-quaternion or-thogonality imposes on quad-quaternion vectors, QQ-MUSIC is shown to offer great robustness to model errors, and thus is very competent in practice. Simulation results have validated the proposed method.
	TO cite this article:Xiaofeng Gong,Yougen Xu,Zhiwen Liu. Quad-quaternion MUSIC for DOA Estimation Using Electromagnetic Vector-Sensors[OL].[ 3 April 2008] http://en.paper.edu.cn/en_releasepaper/content/20106


	10. Performance Analysis of Angular-Smoothing Based Root-MUSIC for an L-Shaped Acoustic Vector-Sensor Array
	Yougen Xu,Zhiwen Liu
	Electrics, Communication and Autocontrol Technology 20 July 2007
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	Abstract:Eigenstructure-based direction-of-arrival (DOA) estimation algorithms such as Multiple Signal Classification (MUSIC), Root-MUSIC, Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT), encounter great difficulty in the presence of perfectly correlated incident signals. For an array composed of a number of translational invariant subarrays such as a uniform linear scalar-sensor array, this problem can be solved by spatial smoothing. An array of identically oriented acoustic vector-sensors can be grouped into four coupled subarrays of identical grid geometry, respectively corresponding to the pressure sensors and differently oriented velocity-sensors. These four subarrays are angular invariant dependent only on signals’ direction cosines and an angular smoothing can be exploited for source decorrelation. In this paper, the performance of root-MUSIC incorporated with angular smoothing for correlated source direction finding with an L-shaped acoustic vector-sensor array is analyzed in terms of the overall root mean-square errors (RMSE) of DOA estimates. We derive the analytical expression of the RMSE and compare it with simulation results and that of spatial smoothing for a rectangular pressure-sensor array instead.
	TO cite this article:Yougen Xu,Zhiwen Liu. Performance Analysis of Angular-Smoothing Based Root-MUSIC for an L-Shaped Acoustic Vector-Sensor Array[OL].[20 July 2007] http://en.paper.edu.cn/en_releasepaper/content/14177

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