|本期目录/Table of Contents|

[1]王 彪*,蒋亚立,戴跃伟. 基于l0范数的匹配场源定位方法[J].南京大学学报(自然科学),2017,53(4):675.[doi:10.13232/j.cnki.jnju.2017.04.008]
 Wang Biao*,Jiang Yali,Dai Yuewei. A matched field source localization method based on sparse structure[J].Journal of Nanjing University(Natural Sciences),2017,53(4):675.[doi:10.13232/j.cnki.jnju.2017.04.008]





 A matched field source localization method based on sparse structure
 王 彪12*蒋亚立1戴跃伟1
 Wang Biao12*Jiang Yali1Dai Yuewei1
 1.College of Electronic Information,Jiangsu University of Science and Technology,Zhenjiang,212003,China;
2.Key Laboratory of Underwater Acoustic Warfare Technology,System Engineering Research Institute,Beijing,100036,China
 Matched Field Processinguniform linear arrayspace sparsitysmooth l0 norm
 Matched field processing techniques have been studied extensively in recent decades,and a lot of detail algorithms have been put forward for practical use.With the rapid development of the theory and algorithms for sparse recovery in finite dimension,compressive sensing(CS)has become an exciting field that has attracted considerable attention in signal processing,such as sound imaging and reconstruction,compressive sensor networks,and so on.We try to locate and match the field sound source by using the compressed sensing method,and find that it can get a better positioning effect than traditional methods.Prior research has established CS as a valuable tool for array signal processing,but it is mainly from a theoretical point of view,and its application to underwater acoustic sources localization has been developed only for very limited scenarios.In this paper,In order to solve the problems of the traditional Matched Field Processing(MFP)method,such as for a long time and which is not suitable for applications with small number of snapshot and array elements,etc.Compared with the traditional compressive sensing algorithm,Matched Field Processing based on smooth l0 norm is proposed from analysis of the characteristics of uniform linear array model and sparse characteristics of matched field,which is combining with smooth l0 norm algorithm.For reconstructing the signal,the method uses combined continuous function as the approximation to smooth l0 norm by sparse matrix processing array manifold,which improves the convergence speed.This method avoids feature decomposition and spectral peak searching process of the traditional algorithm.On the premise of guarantee the estimation precision,it effectively reduces the amount of calculation and the number of the antenna array.At last,by comparing with other source localization methods,such as Bartlett,Minimum variance distortionless response(MVDR),Basis Pursuit(BP) and smooth l0 norm algorithm,simulation results show the effectiveness of the proposed algorithm.


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更新日期/Last Update: 2017-08-02