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作 者:WU Tao DENG Zhenghong HU Xiaoxiang LI Ao XU Jiwei
机构地区:[1]School of Automation,Northwestern Polytechnical University,Xi’an 710072,China [2]Equipment Management and UAV College,Air Force Engineering University,Xi’an 710051,China [3]School of Information Engineering,Xi’an University of Posts and Telecommunications,Xi’an 710061,China
出 处:《Journal of Systems Engineering and Electronics》2022年第4期845-855,共11页系统工程与电子技术(英文版)
基 金:supported by the basic research program of Natural Science in Shannxi province of China (2021JQ-369)。
摘 要:In this paper, an importance sampling maximum likelihood(ISML) estimator for direction-of-arrival(DOA) of incoherently distributed(ID) sources is proposed. Starting from the maximum likelihood estimation description of the uniform linear array(ULA), a decoupled concentrated likelihood function(CLF) is presented. A new objective function based on CLF which can obtain a closed-form solution of global maximum is constructed according to Pincus theorem. To obtain the optimal value of the objective function which is a complex high-dimensional integral,we propose an importance sampling approach based on Monte Carlo random calculation. Next, an importance function is derived, which can simplify the problem of generating random vector from a high-dimensional probability density function(PDF) to generate random variable from a one-dimensional PDF. Compared with the existing maximum likelihood(ML) algorithms for DOA estimation of ID sources, the proposed algorithm does not require initial estimates, and its performance is closer to CramerRao lower bound(CRLB). The proposed algorithm performs better than the existing methods when the interval between sources to be estimated is small and in low signal to noise ratio(SNR)scenarios.
关 键 词:direction-of-arrival(DOA)estimation incoherently distributed(ID)sources importance sampling maximum likelihood(ISML) Monte Carlo random calculation
分 类 号:TN911.7[电子电信—通信与信息系统]
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